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Ox=class{supported;querySet=null;resolveBuffer=null;resultBuffer=null;constructor(e,t){this.supported=t,t&&(this.querySet=e.createQuerySet({type:`timestamp`,count:2}),this.resolveBuffer=e.createBuffer({size:16,usage:GPUBufferUsage.QUERY_RESOLVE|GPUBufferUsage.COPY_SRC}),this.resultBuffer=e.createBuffer({size:16,usage:GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ}))}get timestampWrites(){if(!(!this.supported||!this.querySet))return{querySet:this.querySet,beginningOfPassWriteIndex:0,endOfPassWriteIndex:1}}resolve(e){!this.supported||!this.querySet||!this.resolveBuffer||!this.resultBuffer||(e.resolveQuerySet(this.querySet,0,2,this.resolveBuffer,0),e.copyBufferToBuffer(this.resolveBuffer,0,this.resultBuffer,0,16))}async readElapsedMs(){if(!this.supported||!this.resultBuffer)return NaN;await this.resultBuffer.mapAsync(GPUMapMode.READ);let e=new BigInt64Array(this.resultBuffer.getMappedRange().slice(0));this.resultBuffer.unmap();let t=e[0],n=e[1];return Number(n-t)/1e6}destroy(){this.querySet?.destroy(),this.resolveBuffer?.destroy(),this.resultBuffer?.destroy()}},kx={targetMs:100,targetDispatchMs:10,warmups:1,maxIterations:2e5},Ax=4,jx=12,Mx=4,Nx=2,Px=2,Fx=3,Ix=new WeakMap;function Lx(e,t){let n=Ix.get(e);return n||(n=new Ox(e,t),Ix.set(e,n)),n}var Rx=class{h;timer;iterations=0;currentWork;trustTimestamps;timestampStrikes=0;overheadMs=0;constructor(e){this.h=e,this.timer=Lx(e.device,e.useTimestamps),this.trustTimestamps=this.timer.supported}get timingMethod(){return this.trustTimestamps?`gpu-timestamp`:`cpu-wallclock`}get innerIterations(){return this.iterations}get work(){return this.currentWork}async calibrate(){let e=this.h.targetMs??kx.targetMs,t=this.h.targetDispatchMs??kx.targetDispatchMs,n=this.h.warmups??kx.warmups,r=this.h.maxIterations??kx.maxIterations;this.overheadMs=1/0;for(let e=0;e<Fx;e++)this.overheadMs=Math.min(this.overheadMs,(await this.measureRaw(0)).wallMs);let i=this.h.work;if(i){let e=Math.max(1,Math.floor(i.min));i.apply(e);let n=async()=>{let{gpuMs:e,wallMs:t}=await this.measureRaw(1);return e??t},r=await n();for(;e<i.max&&r<t;){let a=e*t/Math.max(r,1e-6),o=Math.min(i.max,Math.floor(Math.min(a,e*Ax)));if(o<=e)break;e=o,i.apply(e),r=await n()}this.currentWork=e}let a=1;for(let t=0;t<jx;t++){let{wallMs:n}=await this.measureRaw(a);if(t>0&&n>=e/2||a>=r)break;let i=n>0?a*e/n:a*Ax,o=Math.min(r,Math.floor(Math.min(i,a*Ax)));if(o<=a)break;a=o}this.iterations=a;for(let e=0;e<n;e++)await this.measureRaw(this.iterations)}async sample(){if(this.iterations===0)throw Error(`KernelSampler.sample() called before calibrate()`);let{gpuMs:e,wallMs:t}=await this.measureRaw(this.iterations);return(e??t)/this.iterations}destroy(){}async measureRaw(e){let{h:t,timer:n}=this,r=this.trustTimestamps,i=t.device.createCommandEncoder(),a=i.beginComputePass({timestampWrites:r?n.timestampWrites:void 0});t.encode(a,e),a.end(),r&&n.resolve(i);let o=performance.now();if(t.device.queue.submit([i.finish()]),!r)return await t.device.queue.onSubmittedWorkDone(),{gpuMs:null,wallMs:performance.now()-o};let s=await n.readElapsedMs(),c=performance.now()-o,l=c-this.overheadMs;return e>0&&l>=Mx&&!(s*Nx>=l)?(this.timestampStrikes+=1,this.timestampStrikes>=Px&&(this.trustTimestamps=!1),{gpuMs:null,wallMs:c}):(this.timestampStrikes=0,{gpuMs:s,wallMs:c})}},zx=[12.706,4.303,3.182,2.776,2.571,2.447,2.365,2.306,2.262,2.228,2.201,2.179,2.16,2.145,2.131,2.12,2.11,2.101,2.093,2.086,2.08,2.074,2.069,2.064,2.06,2.056,2.052,2.048,2.045,2.042];function Bx(e){return e<1?1/0:zx[Math.min(e,zx.length)-1]}function Vx(e){if(e.length===0)throw Error(`computeStats: values must be non-empty`);let t=e.length,n=e.toSorted((e,t)=>e-t),r=e.reduce((e,t)=>
69e+t,0)/t,i=n[0],a=n[t-1],o=Math.floor(t/2),s=t%2==0?(n[o-1]+n[o])/2:n[o],c=t>1?e.reduce((e,t)=>e+(t-r)**2,0)/(t-1):0,l=Math.sqrt(c);return{mean:r,min:i,max:a,median:s,stddev:l,ci95:t>1?Bx(t-1)*l/Math.sqrt(t):1/0}}function Hx(e,t){let n=e.length;if(n<Math.max(t.stableRuns+1,t.minRuns,2))return!1;let r=Math.min(...e);return!Number.isFinite(r)||r<=0?!1:r>=Math.min(...e.slice(0,n-t.stableRuns))*(1-t.tolerance)}function Ux(e,t,n){return!Number.isFinite(t)||t<=0?!1:e>t*(1+n)}var Wx={minRounds:3,maxRounds:10,stableRounds:2,improvementTolerance:.01,throttleThreshold:.2,idleMs:100,cooldownMs:3e3,maxCooldowns:3},Gx=e=>e.stopReason===void 0&&e.error===void 0,Kx=e=>new Promise(t=>setTimeout(()=>{typeof requestIdleCallback==`function`?requestIdleCallback(()=>t(),{timeout:1e3}):t()},e));function qx(e){let t=typeof document>`u`?void 0:document,n=!1,r=()=>{t?.hidden&&(n=!0,e())};return t?.addEventListener(`visibilitychange`,r),{mark:()=>{n=!!t?.hidden},hiddenSince:()=>n||!!t?.hidden,waitVisible:()=>new Promise(e=>{if(!t?.hidden)return e();let n=()=>{t.hidden||(t.removeEventListener(`visibilitychange`,n),e())};t.addEventListener(`visibilitychange`,n)}),dispose:()=>t?.removeEventListener(`visibilitychange`,r)}}function Jx(e,t,n){return Ux(t,e.bestMs,n.throttleThreshold)?(e.throttledMs.push(t),e.timesMs.length+e.throttledMs.length>=2*n.maxRounds&&(e.stopReason=`max-rounds`),!1):(e.timesMs.push(t),t<e.bestMs&&(e.bestMs=t),Hx(e.timesMs,{minRuns:n.minRounds,stableRuns:n.stableRounds,tolerance:n.improvementTolerance})?e.stopReason=`converged`:e.timesMs.length>=n.maxRounds&&(e.stopReason=`max-rounds`),!0)}function Yx(e){return{...e,timesMs:[...e.timesMs],throttledMs:[...e.throttledMs],stats:e.timesMs.length>0?Vx(e.timesMs):void 0}}async function Xx(e,t={}){let n=Zx(t),r=t.sleep??Kx,i=t.now??(()=>performance.now()),a=t.onUpdate??(()=>{}),o=t.onProgress??(()=>{}),s=new Map,c=qx(()=>o({type:`pause`})),l=0,u=!1,d=0;try{for(let f of e){let e={id:f.id,timesMs:[],throttledMs:[],bestMs:1/0},p=!1,m=0;for(o({type:`benchmark-start`,id:e.id});Gx(e);){o({type:`round`,round:++d,active:1,estimatedRemainingUnits:Math.max(n.minRounds+n.stableRounds-e.timesMs.length,1),activeIds:[e.id],sampling:n,sampleBudgetMs:t.targetMs??100,calibrationBudgetMs:(t.targetMs??100)*(2+(t.warmups??1))});let s=0;try{p||=(await c.waitVisible(),await f.calibrate(),!0),u&&n.idleMs>0&&await r(n.idleMs),await c.waitVisible(),c.mark(),u=!0;let t=i(),a=await f.sample();if(s=i()-t,c.hiddenSince())continue;if(!Number.isFinite(a)||a<=0)throw Error(`measured a per-op time of ${a}ms â the GPU pass likely did no work (check for an 'uncapturederror' in the console).`);m=Jx(e,a,n)?0:m+1}catch(t){e.error=t}if(o({type:`sample`,id:e.id,durationMs:s,timesMs:[...e.timesMs],throttledMs:[...e.throttledMs],done:!Gx(e)}),await a(Yx(e)),m>=2&&Gx(e)){let t=[e.id];if(l>=n.maxCooldowns){o({type:`throttle-abort`,throttledIds:t}),e.stopReason=`throttled`,await a(Yx(e));break}m=0,o({type:`cooldown`,attempt:++l,maxAttempts:n.maxCooldowns,ms:n.cooldownMs,throttledIds:t}),await r(n.cooldownMs)}}s.set(e.id,Yx(e))}}finally{c.dispose()}return s}function Zx(e){let t=Math.max(1,e.minRounds??Wx.minRounds);return{minRounds:t,maxRounds:Math.max(t,e.maxRounds??Wx.maxRounds),stableRounds:Math.max(1,e.stableRounds??Wx.stableRounds),improvementTolerance:e.improvementTolerance??Wx.improvementTolerance,throttleThreshold:e.throttleThreshold??Wx.throttleThreshold,idleMs:e.idleMs??Wx.idleMs,cooldownMs:e.cooldownMs??Wx.cooldownMs,maxCooldowns:e.maxCooldowns??Wx.maxCooldowns}}var Qx={key:`flops`,unit:`FLOP`,name:`Floating-point ops`},$x={key:`ops`,unit:`OP`,name:`Operations`},eS={key:`bytes`,unit:`B`,name:`Bandwidth`};async function tS(e,t,n,r,i=`main`){e.pushErrorScope(`validation`);let a=e.createShaderModule({label:t,code:n}),o=e.popErrorScope();try{let[n,s]=await Promise.all([o,e.createComputePipelineAsync({label:t,layout:`auto`,compute:{module:a,entryPoint:i,constants:r}})]);if(n)throw n;return s}catch(e){let n=e&&typeof e==`object`&&`message`in e?String(e.message):String(e);throw Error(`Failed to create pipeline "${t}": ${n}`,{cause:e})}}function nS(e,t){return e/(t/1e3)}function rS(e){let{ctx:t,pipeline:n,bindGroup:r,workgroupsPerIteration:i}=e;return{kind:`kernel`,meta:{id:e.id,category:e.category,rows:e.rows,cols:e.cols,amountPerOp:e.amountPerOp},metaAtWork:e.metaAtWork,harness:{device:t.device,useTimestamps:t.info.supportsTimestampQuery,targetMs:e.targetMs,targetDispatchMs:e.targetDispatchMs,warmups:e.warmups,maxIterations:e.maxIterations,work:e.work,encode:(e,t)=>{e.setPipeline(n),e.setBindGroup(0,r);for(let n=0;n<t;n++)e.dispatchWorkgroups(...i)}}}}function iS(e,t){return{...oS(e),status:`skipped`,message:t}}function aS(e,t){return{...oS(e),status:`error`,message:t instanceof Error?t.message:String(t)}}function oS(e){return{id:e.id,category:e.category,status:`running`,rows:e.rows,cols:e.cols,innerIterations:0,timesMs:[],throttledMs:[],timingMethod:`cpu-wallclock`}}function sS(e,t,n,r){let i=e.createBuffer({label:r,size:Math.max(4,Math.ceil(t.byteLength/4)*4),usage:n,mappedAtCreation:!0});return new Uint8Array(i.getMappedRange()).set(new Uint8Array(t.buffer,t.byteOffset,t.byteLength)),i.unmap(),i}function cS(e,t,n){return sS(e,t,GPUBufferUsage.STORAGE|GPUBufferUsage.COPY_SRC|GPUBufferUsage.COPY_DST,n)}
69function lS(e,t,n){return sS(e,t,GPUBufferUsage.UNIFORM|GPUBufferUsage.COPY_DST,n)}function uS(e,t,n){return e.createBuffer({label:n,size:Math.max(4,Math.ceil(t/4)*4),usage:GPUBufferUsage.STORAGE|GPUBufferUsage.COPY_SRC|GPUBufferUsage.COPY_DST})}var dS=` 70struct Params { count: u32, rounds: u32, padded: u32, shards: u32 }; 71@group(0) @binding(0) var<uniform> params: Params; 72`;function fS(e){return`${dS} 73@group(0) @binding(1) var<storage, read> input: array<f32>; 74@group(0) @binding(2) var<storage, read_write> output: array<f32>; 75@compute @workgroup_size(${e}) 76fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 77 let i = gid.x; 78 if (i >= params.count) { return; } 79 var x = input[i]; 80 for (var k = 0u; k < params.rounds; k++) { 81 x = x * 0.75 + 0.125; 82 } 83 output[i] = x; 84} 85`}function pS(e){return`${dS} 86// Eight scalar fields: position.xyz, velocity.xyz, mass, lifetime. 87@group(0) @binding(1) var<storage, read> input: array<f32>; 88@group(0) @binding(2) var<storage, read_write> output: array<f32>; 89fn address(i: u32, field: u32) -> u32 { return ${e===`aos`?`i * 8u + field`:e===`soa`?`field * params.padded + i`:`(i / 32u) * 256u + field * 32u + i % 32u`}; } 90@compute @workgroup_size(128) 91fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 92 let i = gid.x; 93 if (i >= params.count) { return; } 94 // Only positions change; other fields remain immutable in the input. 95 for (var field = 0u; field < 3u; field++) { 96 output[address(i, field)] = input[address(i, field)] + input[address(i, field + 3u)] * 0.125; 97 } 98} 99`}function mS(e){let t=e===`shared-padded`?17:16,n=e!==`direct`;return`${dS} 100@group(0) @binding(1) var<storage, read> input: array<f32>; 101@group(0) @binding(2) var<storage, read_write> output: array<f32>; 102${n?`var<workgroup> tile: array<f32, ${16*t}>;`:``} 103@compute @workgroup_size(256) 104fn main(@builtin(workgroup_id) group: vec3<u32>, @builtin(local_invocation_index) lane: u32) { 105 let base = group.x * 256u; 106 let row = lane / 16u; 107 let col = lane % 16u; 108 ${n?`tile[row * ${t}u + col] = input[base + lane]; 109 workgroupBarrier();`:``} 110 // Padding lanes must participate in the cooperative load and barrier. 111 if (base + lane >= params.count) { return; } 112 var sum = 0.0; 113 // A fixed 3x3 box stencil, with wraparound within each 16x16 tile. 114 for (var dy = 0u; dy < 3u; dy++) { 115 for (var dx = 0u; dx < 3u; dx++) { 116 let y = (row + dy + 15u) % 16u; 117 let x = (col + dx + 15u) % 16u; 118 sum += ${n?`tile[y * ${t}u + x]`:`input[base + y * 16u + x]`}; 119 } 120 } 121 output[base + lane] = sum * (1.0 / 9.0); 122} 123`}function hS(e){let t=`${dS} 124@group(0) @binding(1) var<storage, read> input: array<u32>; 125@group(0) @binding(2) var<storage, read_write> output: array<u32>; 126`;return e===`serial`?`${t} 127@compute @workgroup_size(64) 128fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 129 let segment = gid.x; 130 if (segment * 256u >= params.count) { return; } 131 var sum = 0u; 132 for (var k = 0u; k < 256u; k++) { 133 let i = segment * 256u + k; 134 if (i < params.count) { sum += input[i]; } 135 } 136 output[segment] = sum; 137} 138`:e===`subgroup`?`enable subgroups; 139${t} 140var<workgroup> total: atomic<u32>; 141@compute @workgroup_size(256) 142fn main(@builtin(workgroup_id) group: vec3<u32>, @builtin(local_invocation_index) lane: u32, 143 @builtin(subgroup_invocation_id) subgroupLane: u32) { 144 if (lane == 0u) { atomicStore(&total, 0u); } 145 workgroupBarrier(); 146 let i = group.x * 256u + lane; 147 var value = 0u; 148 if (i < params.count) { value = input[i]; } 149 let partial = subgroupAdd(value); 150 // All lanes participate, including zero-padded tails. No mapping between 151 // workgroup indices and subgroup lanes or a fixed subgroup width is assumed. 152 if (subgroupLane == 0u) { atomicAdd(&total, partial); } 153 workgroupBarrier(); 154 if (lane == 0u) { output[group.x] = atomicLoad(&total); } 155} 156`:`${t} 157var<workgroup> partial: array<u32, 256>; 158@compute @workgroup_size(256) 159fn main(@builtin(workgroup_id) group: vec3<u32>, @builtin(local_invocation_index) lane: u32) { 160 let i = group.x * 256u + lane; 161 var value = 0u; 162 if (i < params.count) { value = input[i]; } 163 partial[lane] = value; 164 workgroupBarrier(); 165 for (var stride = 128u; stride > 0u; stride /= 2u) { 166 if (lane < stride) { partial[lane] += partial[lane + stride]; } 167 workgroupBarrier(); 168 } 169 if (lane == 0u) { output[group.x] = partial[0]; } 170} 171`}function gS(e){return`${dS} 172@group(0) @binding(1) var<storage, read> input: array<vec4<f32>>; 173@group(0) @binding(2) var<storage, read_write> output: array<vec4<f32>>; 174@compute @workgroup_size(128) 175fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 176 if (gid.x >= params.count) { return; } 177 var x = input[gid.x];
178 var h = gid.x * 2654435761u; 179 for (var k = 0u; k < params.rounds; k++) { 180 h = h * 1664525u + 1013904223u; 181 let mask = ((vec4<u32>(h) >> vec4<u32>(0u, 8u, 16u, 24u)) & vec4<u32>(1u)) != vec4<u32>(0u); 182 ${e?`x = select(x * 0.75 + vec4<f32>(0.25), x * 0.5 - vec4<f32>(0.5), mask);`:[`x`,`y`,`z`,`w`].map(e=>`if (mask.${e}) { x.${e} = x.${e} * 0.5 - 0.5; } 183 else { x.${e} = x.${e} * 0.75 + 0.25; }`).join(` 184 `)} 185 } 186 output[gid.x] = x; 187} 188`}function _S(e){return`${dS} 189@group(0) @binding(1) var<storage, read> input: array<u32>; 190@group(0) @binding(2) var<storage, read_write> scratch: array<atomic<u32>>; 191@group(0) @binding(3) var<storage, read_write> output: array<u32>; 192${e===`workgroup`?`var<workgroup> bins: array<atomic<u32>, 32>;`:``} 193@compute @workgroup_size(256) 194fn reset(@builtin(global_invocation_id) gid: vec3<u32>) { 195 if (gid.x < params.shards * 32u) { atomicStore(&scratch[gid.x], 0u); } 196} 197@compute @workgroup_size(256) 198fn main(@builtin(global_invocation_id) gid: vec3<u32>, 199 @builtin(local_invocation_index) lane: u32, @builtin(workgroup_id) group: vec3<u32>) { 200 ${e===`workgroup`?`if (lane < 32u) { atomicStore(&bins[lane], 0u); } 201 workgroupBarrier();`:``} 202 // Sixteen grid-stride updates per invocation for a full workgroup. 203 for (var k = 0u; k < 16u; k++) { 204 let i = group.x * 4096u + lane + k * 256u; 205 if (i < params.count) {
206 let bin = input[i]; 207 ${e===`workgroup`?`atomicAdd(&bins[bin], 1u);`:`atomicAdd(&scratch[${e===`sharded`?`(group.x % params.shards) * 32u + `:``}bin], 1u);`} 208 } 209 } 210 ${e===`workgroup`?`workgroupBarrier(); 211 if (lane < 32u) { atomicAdd(&scratch[lane], atomicLoad(&bins[lane])); }`:``} 212} 213@compute @workgroup_size(32) 214fn merge(@builtin(local_invocation_index) bin: u32) { 215 var sum = 0u; 216 for (var shard = 0u; shard < params.shards; shard++) { 217 sum += atomicLoad(&scratch[shard * 32u + bin]); 218 } 219 output[bin] = sum; 220} 221`}var vS=`${dS} 222@group(0) @binding(1) var<storage, read> next: array<u32>; 223@group(0) @binding(2) var<storage, read_write> output: array<u32>; 224// Exactly one active invocation and one chain, not one chain per GPU lane. 225@compute @workgroup_size(1) 226fn main() { 227 var index = 0u; 228 for (var hop = 0u; hop < params.rounds; hop++) { index = next[index]; } 229 output[0] = index; 230} 231`,yS=[{family:`workgroup`,variant:64},{family:`workgroup`,variant:128},{family:`workgroup`,variant:256},{family:`layout`,variant:`aos`},{family:`layout`,variant:`soa`},{family:`layout`,variant:`aosoa`},{family:`tile`,variant:`direct`},{family:`tile`,variant:`shared`},{family:`tile`,variant:`shared-padded`},{family:`reduction`,variant:`serial`},{family:`reduction`,variant:`workgroup`},{family:`reduction`,variant:`subgroup`},{family:`branch`,variant:`select`},{family:`branch`,variant:`if`},{family:`atomic`,variant:`direct`},{family:`atomic`,variant:`workgroup`},{family:`atomic`,variant:`sharded`},{family:`dependent`,variant:`chain`}];function bS(e){return e.family===`branch`?`branch-vec4-${e.variant}`:e.family===`dependent`?`read-dependent-chain`:`${e.family}-${e.variant}`}function xS(e){switch(e.family){case`workgroup`:return fS(e.variant);case`layout`:return pS(e.variant);case`tile`:return mS(e.variant);case`reduction`:return hS(e.variant);case`branch`:return gS(e.variant===`select`);case`atomic`:return _S(e.variant);case`dependent`:return vS}}var SS=(e,t,n)=>({key:e,unit:t,name:n}),CS={workgroup:SS(`elements`,`element`,`Transformed elements`),layout:SS(`particles`,`particle`,`Updated particles`),tile:SS(`outputs`,`output`,`Stencil outputs`),reduction:SS(`elements`,`element`,`Reduced input elements`),branch:SS(`choices`,`choice`,`Component choices`),atomic:SS(`updates`,`update`,`Histogram inputs`),dependent:SS(`hops`,`hop`,`Dependent memory hops`)};function wS(e){switch(e.family){case`workgroup`:return`65,536 scalar elements, one per invocation, with 16 multiply-add steps each. Only workgroup size (${e.variant}) changes; the input, arithmetic and output count match. Reports elements/s.`;case`layout`:return`Identical position.xyz += velocity.xyz * 0.125 updates for 65,536 eight-field particles stored as ${e.variant}. AoSoA uses 32-particle blocks. Reads immutable input and writes positions in the same layout; other fields are preserved. Reports particles/s, excluding CPU packing.`;case`tile`:return`The same 3x3 box stencil on 256 independent 16x16 tiles, wrapping within each tile. ${e.variant===`direct`?`Loads all nine neighbors directly from storage.`:`Cooperatively stages the tile in workgroup memory with row stride ${e.variant===`shared`?16:17}; includes loading and synchronization.`} Reports outputs/s. A fixed reuse pattern, not a reuse sweep.`;case`reduction`:return`Sums 65,536 bounded u32 inputs into 256 independent 256-element segment sums. ${e.variant===`serial`?`One invocation sums each segment serially.`:e.variant===`workgroup`?`One 256-invocation workgroup per segment uses a shared-memory tree.`:`Uses subgroupAdd with one workgroup atomic addition per subgroup; requires subgroups, assumes no subgroup width.`} Reports input elements/s; all variants produce complete segment sums.`;case`branch`:return`65,536 vec4 values, 64 steps with the same seeded component masks and bounded arithmetic. ${e.variant===`select`?`One vector select per step.`:`Four scalar if/else statements per step.`} Reports component choices/s. Measures source alternatives as compiled; does not guarantee native branches.`;case`atomic`:return`A complete 32-bin histogram of 65,536 identical seeded keys (about half target bin zero). ${e.variant===`direct`?`Direct global atomic updates.`:e.variant===`workgroup`?`Aggregates in workgroup-local atomics before global merging.`:`Upd
231ates eight global shards, then sums them.`} Includes reset, 16 inputs per invocation, and final merge in every timed repetition. Reports histogram inputs/s.`;case`dependent`:return`One active invocation follows one dependent chain for 4,096 hops through a seeded single-cycle permutation of 1,048,576 u32 entries (4 MiB). Every address comes from the preceding load. Reports hops/s; reciprocal rate is amortized ns/hop, including loop/dispatch cost, not raw memory latency. Repeated batches reuse the same chain.`}}function TS(e,t=e.family===`dependent`?1048576:65536){if(!Number.isSafeInteger(t)||t<1||t>1048576)throw Error(`Technique count must be an integer in [1, 1048576].`);let n=Math.ceil(t/256)*256,r=Tx(24301),i=e.family===`branch`?64:e.family===`workgroup`?16:e.family===`dependent`?4096:1,a=e.family===`atomic`&&e.variant===`sharded`?8:1,o=e.family===`atomic`||e.family===`reduction`||e.family===`dependent`,s,c;if(e.family===`layout`){s=new Float32Array(n*8);for(let i=0;i<t;i++)for(let t=0;t<8;t++)s[ES(e.variant,i,t,n)]=r()*2-1;c=s.slice()}else if(e.family===`dependent`){let e=Uint32Array.from({length:t},(e,t)=>t);for(let n=t-1;n>0;n--){let t=Math.floor(r()*(n+1)),i=e[n];e[n]=e[t],e[t]=i}s=new Uint32Array(t);for(let n=0;n<t;n++)s[e[n]]=e[(n+1)%t];c=new Uint32Array(1).fill(4294967295)}else if(o){s=new Uint32Array(n);for(let n=0;n<t;n++)s[n]=e.family===`atomic`?r()<.5?0:1+Math.floor(r()*31):Math.floor(r()*16);c=new Uint32Array(e.family===`atomic`?32:n/256).fill(4294967295)}else{let i=e.family===`branch`?4:1;s=new Float32Array(n*i);for(let e=0;e<t*i;e++)s[e]=r()*2-1;c=new Float32Array(t*i).fill(NaN)}return{count:t,padded:n,rounds:i,shards:a,integer:o,input:s,initialOutput:c}}function ES(e,t,n,r){return e===`aos`?t*8+n:e===`soa`?n*r+t:Math.floor(t/32)*256+n*32+t%32}async function DS(e,t,n={},r){let i=bS(t),a=TS(t,r),o={id:i,category:`algorithm`,rows:a.count,cols:t.family===`reduction`?256:a.rounds,amountPerOp:t.family===`dependent`?a.rounds:a.count*(t.family===`branch`?a.rounds*4:1)};if(t.family===`reduction`&&t.variant===`subgroup`&&!e.device.features.has(`subgroups`))return{prepared:{kind:`skipped`,result:iS(o,`Device/browser does not support the "subgroups" WebGPU feature.`)},data:a,output:void 0,destroy(){}};let s=[],c=e=>(s.push(e),e),l=()=>{for(let e of s)e.destroy()};try{let r=c(lS(e.device,new Uint32Array([a.count,a.rounds,a.padded,a.shards]))),s=c(cS(e.device,a.input)),u=c(cS(e.device,a.initialOutput)),d=xS(t),f=[],p=async(t,n,r)=>{let a=await tS(e.device,`${i}-${t}`,d,void 0,t),o=e.device.createBindGroup({layout:a.getBindGroupLayout(0),entries:n.map(([e,t])=>({binding:e,resource:{buffer:t}}))});f.push({pipeline:a,bindGroup:o,workgroups:r})};if(t.family===`atomic`){let t=c(cS(e.device,new Uint32Array(a.shards*32)));await p(`reset`,[[0,r],[2,t]],1),await p(`main`,[[0,r],[1,s],[2,t]],Math.ceil(a.count/4096)),await p(`merge`,[[0,r],[2,t],[3,u]],1)}else{let e=t.family===`dependent`?1:t.family===`reduction`?t.variant===`serial`?Math.ceil(Math.ceil(a.count/256)/64):Math.ceil(a.count/256):Math.ceil(a.count/(t.family===`workgroup`?t.variant:t.family===`tile`?256:128));await p(`main`,[[0,r],[1,s],[2,u]],e)}return{prepared:{kind:`kernel`,meta:o,harness:{...n,device:e.device,useTimestamps:e.info.supportsTimestampQuery,encode(e,t){for(let n=0;n<t;n++)for(let t of f)e.setPipeline(t.pipeline),e.setBindGroup(0,t.bindGroup),e.dispatchWorkgroups(t.workgroups)}}},data:a,output:u,destroy:l}}catch(e){throw l(),e}}var OS=yS.map(e=>({id:bS(e),label:bS(e).replaceAll(`-`,` `),description:wS(e),source:xS(e),category:`algorithm`,metric:CS[e.family],prepare:async({ctx:t,harness:n})=>(await DS(t,e,n)).prepared})),kS=` 232struct Params { 233 count: u32, 234 threads: u32, 235}; 236 237@group(0) @binding(0) var<uniform> params: Params; 238@group(0) @binding(1) var<storage, read> data: array<vec4<f32>>; 239@group(0) @binding(2) var<storage, read_write> out: array<f32>; 240 241@compute @workgroup_size(256) 242fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 243 let t = gid.x; 244 var sum: vec4<f32> = vec4<f32>(0.0, 0.0, 0.0, 0.0); 245 for (var i: u32 = t; i < params.count; i = i + params.threads) { 246 sum = sum + data[i]; 247 } 248 out[t] = sum.x + sum.y + sum.z + sum.w; 249} 250`,AS=` 251struct Params { 252 count: u32, 253 threads: u32, 254}; 255 256@group(0) @binding(0) var<uniform> params: Params; 257@group(0) @binding(1) var<storage, read_write> out: array<vec4<f32>>; 258 259@compute @workgroup_size(256) 260fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 261 let t = gid.x; 262 let v = vec4<f32>(f32(t), f32(t), f32(t), f32(t)); 263 for (var i: u32 = t; i < params.count; i = i + params.threads) { 264 out[i] = v; 265 } 266} 267`,jS=` 268struct Params { 269 count: u32, 270 threads: u32, 271 mask: u32, 272}; 273 274@group(0) @binding(0) var<uniform> params: Params; 275@group(0) @binding(1) var<storage, read> data: array<vec4<f32>>; 276@group(0) @binding(2) var<storage, read_write> out: array<f32>; 277 278@compute @workgroup_size(256) 279fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 280 let t = gid.x; 281 var h: u32 = t * 2654435761u; 282 var sum: vec4<f32> = vec4<f32>(0.0, 0.0, 0.0, 0.0); 283 for (var i: u32 = t; i < params.count; i = i + params.threads) { 284 h = h * 1664525u + 1013904223u; 285 sum = sum + data[(h >> 8u) & params.mask]; 286 } 287 out[t] = sum.x + sum.y + sum.z + sum.w; 288} 289`,MS=` 290struct Params { 291 count: u32, 292 threads: u32, 293 mask: u32, 294}; 295 296@group(0) @binding(0) var<uniform> params: Params; 297@group(0) @binding(1) var<storage, read_write> out: array<vec4<f32>>; 298 299@compute @workgroup_size(256) 300fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 301 let t = gid.x; 302 for (var i: u32 = t; i < params.count; i = i + params.threads) { 303 let destination = (i * 2654435761u + 1013904223u) & params.mask; 304 out[destination] = vec4<f32>(f32(i)); 305 } 306} 307`,NS=256,PS=16;function FS(e){let t=e.matrix.length/4,n=Math.max(1,Math.ceil(t/PS/NS));return{count:t,threads:n*NS,workgroups:n}}async function IS(e,t,n={}){let{device:r}=e,{count:i,threads:a,workgroups:o}=FS(t),s=await tS(r,`stream-read`,kS),c=lS(r,new Uint32Array([i,a]),`params`),l=cS(r,t.matrix,`data`),u=uS(r,a*4,`out`),d=r.createBindGroup({layout:s.getBindGroupLayout(0),entries:[{binding:0,resource:{buffer:c}},{binding:1,resource:{buffer:l}},{binding:2,resource:{buffer:u}}]});return rS({id:`read-linear`,category:`bandwidth`,ctx:e,rows:t.rows,cols:t.cols,amountPerOp:t.matrix.byteLength,workgroupsPerIteration:[o,1,1],pipeline:s,bindGroup:d,...n})}async function LS(e,t,n={}){let{device:r}=e,{count:i,threads:a,workgroups:o}=FS(t),s=await tS(r,`stream-write`,AS),c=lS(r,new Uint32Array([i,a]),`params`),l=uS(r,t.matrix.byteLength,`out`),u=r.createBindGroup({layout:s.getBindGroupLayout(0),entries:[{binding:0,resource:{buffer:c}},{binding:1,resource:{buffer:l}}]});return rS({id:`write-linear`,category:`bandwidth`,ctx:e,rows:t.rows,cols:t.cols,amountPerOp:t.matrix.byteLength,workgroupsPerIteration:[o,1,1],pipeline:s,bindGroup:u,...n})}function RS(e,t){let n=2**Math.floor(Math.log2(e));return Math.min(t/16,n)-1}async function zS(e,t,n,r,i){let{device:a}=e,{count:o,threads:s,workgroups:c}=FS(t),l=await tS(a,r,jS),u=lS(a,new Uint32Array([o,s,RS(o,i)]),`params`),d=cS(a,t.matrix,`data`),f=uS(a,s*4,`out`),p=a.createBindGroup({layout:l.getBindGroupLayout(0),entries:[{binding:0,resource:{buffer:u}},{binding:1,resource:{buffer:d}},{binding:2,resource:{buffer:f}}]});return rS({id:r,category:`bandwidth`,ctx:e,rows:t.rows,cols:t.cols,amountPerOp:t.matrix.byteLength,workgroupsPerIteration:[c,1,1],pipeline:l,bindGroup:p,...n})}async function BS(e,t,n,r,i){let{device:a}=e,o=RS(t.matrix.length/4,i),s=o+1,c=Math.max(1,Math.ceil(s/PS/NS)),l=c*NS,u=await tS(a,r,MS),d=lS(a,new Uint32Array([s,l,o]),`params`),f=uS(a,s*16,`out`),p=a.createBindGroup({layout:u.getBindGroupLayout(0),entries:[{binding:0,resource:{buffer:d}},{binding:1,resource:{buffer:f}}]});return rS({id:r,category:`bandwidth`,ctx:e,rows:t.rows,cols:t.cols,amountPerOp:s*16,workgroupsPerIteration:[c,1,1],pipeline:u,bindGroup:p,...n})}var VS=` 308struct Params { 309 threads: u32, 310 iterations: u32, 311}; 312 313@group(0) @binding(0) var<uniform> params: Params; 314@group(0) @binding(1) var<storage, read_write> out: array<f32>; 315 316@compute @workgroup_size(64) 317fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 318 let idx = gid.x; 319 if (idx >= params.threads) { 320 return; 321 } 322 let a: f32 = 1.0 - f32(idx & 15u) * 0.001; 323 let b: f32 = 0.5 + f32(idx & 7u) * 0.001; 324 var x0: f32 = f32(idx & 255u) * 0.0001 + 0.01; 325 var x1: f32 = f32(idx & 255u) * 0.0001 + 0.02; 326 var x2: f32 = f32(idx & 255u) * 0.0001 + 0.03; 327 var x3: f32 = f32(idx & 255u) * 0.0001 + 0.04; 328 var x4: f32 = f32(idx & 255u) * 0.0001 + 0.05; 329 var x5: f32 = f32(idx & 255u) * 0.0001 + 0.06; 330 var x6: f32 = f32(idx & 255u) * 0.0001 + 0.07; 331 var x7: f32 = f32(idx & 255u) * 0.0001 + 0.08; 332 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 333 x0 = x0 * a + b; 334 x1 = x1 * a + b; 335 x2 = x2 * a + b; 336 x3 = x3 * a + b; 337 x4 = x4 * a + b; 338 x5 = x5 * a + b; 339 x6 = x6 * a + b; 340 x7 = x7 * a + b; 341 x0 = x0 * a + b; 342 x1 = x1 * a + b; 343 x2 = x2 * a + b; 344 x3 = x3 * a + b; 345 x4 = x4 * a + b; 346 x5 = x5 * a + b; 347 x6 = x6 * a + b; 348 x7 = x7 * a + b; 349 x0 = x0 * a + b; 350 x1 = x1 * a + b; 351 x2 = x2 * a + b; 352 x3 = x3 * a + b; 353 x4 = x4 * a + b; 354 x5 = x5 * a + b; 355 x6 = x6 * a + b; 356 x7 = x7 * a + b; 357 x0 = x0 * a + b; 358 x1 = x1 * a + b; 359 x2 = x2 * a + b; 360 x3 = x3 * a + b; 361 x4 = x4 * a + b; 362 x5 = x5 * a + b; 363 x6 = x6 * a + b; 364 x7 = x7 * a + b; 365 } 366 out[idx] = x0 + x1 + x2 + x3 + x4 + x5 + x6 + x7; 367} 368`,HS=` 369struct Params { 370 threads: u32, 371 iterations: u32, 372}; 373 374@group(0) @binding(0) var<uniform> params: Params; 375@group(0) @binding(1) var<storage, read_write> out: array<f32>; 376 377@compute @workgroup_size(64) 378fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 379 let idx = gid.x; 380 if (idx >= params.threads) { 381 return; 382 } 383 let s: f32 = f32(idx & 15u) * 0.001; 384 let a: vec4<f32> = vec4<f32>
384(1.0 - s, 1.0 - 2.0 * s, 1.0 - 3.0 * s, 1.0 - 4.0 * s); 385 let b: vec4<f32> = vec4<f32>(0.5 + s, 0.5 + 2.0 * s, 0.5 + 3.0 * s, 0.5 + 4.0 * s); 386 var x0: vec4<f32> = vec4<f32>(f32(idx & 255u) * 0.0001 + 0.01); 387 var x1: vec4<f32> = vec4<f32>(f32(idx & 255u) * 0.0001 + 0.02); 388 var x2: vec4<f32> = vec4<f32>(f32(idx & 255u) * 0.0001 + 0.03); 389 var x3: vec4<f32> = vec4<f32>(f32(idx & 255u) * 0.0001 + 0.04); 390 var x4: vec4<f32> = vec4<f32>(f32(idx & 255u) * 0.0001 + 0.05); 391 var x5: vec4<f32> = vec4<f32>(f32(idx & 255u) * 0.0001 + 0.06); 392 var x6: vec4<f32> = vec4<f32>(f32(idx & 255u) * 0.0001 + 0.07); 393 var x7: vec4<f32> = vec4<f32>(f32(idx & 255u) * 0.0001 + 0.08); 394 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 395 x0 = x0 * a + b; 396 x1 = x1 * a + b; 397 x2 = x2 * a + b; 398 x3 = x3 * a + b; 399 x4 = x4 * a + b; 400 x5 = x5 * a + b; 401 x6 = x6 * a + b; 402 x7 = x7 * a + b; 403 x0 = x0 * a + b; 404 x1 = x1 * a + b; 405 x2 = x2 * a + b; 406 x3 = x3 * a + b; 407 x4 = x4 * a + b; 408 x5 = x5 * a + b; 409 x6 = x6 * a + b; 410 x7 = x7 * a + b; 411 x0 = x0 * a + b; 412 x1 = x1 * a + b; 413 x2 = x2 * a + b; 414 x3 = x3 * a + b; 415 x4 = x4 * a + b; 416 x5 = x5 * a + b; 417 x6 = x6 * a + b; 418 x7 = x7 * a + b; 419 x0 = x0 * a + b; 420 x1 = x1 * a + b; 421 x2 = x2 * a + b; 422 x3 = x3 * a + b; 423 x4 = x4 * a + b; 424 x5 = x5 * a + b; 425 x6 = x6 * a + b; 426 x7 = x7 * a + b; 427 } 428 let t = x0 + x1 + x2 + x3 + x4 + x5 + x6 + x7; 429 out[idx] = t.x + t.y + t.z + t.w; 430} 431`,US=` 432struct Params { 433 threads: u32, 434 iterations: u32, 435}; 436 437@group(0) @binding(0) var<uniform> params: Params; 438@group(0) @binding(1) var<storage, read_write> out: array<f32>; 439 440fn weights(seed: u32) -> vec4<f32> { 441 let h = seed * 0x9e3779b1u; 442 let bytes = vec4<u32>(h & 255u, (h >> 8u) & 255u, (h >> 16u) & 255u, h >> 24u); 443 return (vec4<f32>(bytes) + vec4<f32>(32.0)) * f32(1.0 / 4096.0); 444} 445 446@compute @workgroup_size(64) 447fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 448 let idx = gid.x; 449 if (idx >= params.threads) { 450 return; 451 } 452 let seed = idx * 4u; 453 // Every entry is in [1/128, 1/8): each absolute row sum is < 1/2. 454 let m = mat4x4<f32>(weights(seed + 1u), weights(seed + 2u), weights(seed + 3u), weights(seed + 4u)); 455 var c = vec4<f32>(0.125, 0.25, 0.375, 0.5); 456 var x = vec4<f32>(0.1, 0.2, 0.3, 0.4) + vec4<f32>(f32(idx & 255u) * f32(0.0001)); 457 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 458 x = m * x + c; 459 c = c.yzwx; // A four-step forcing cycle avoids a constant fixed point. 460 } 461 out[idx] = x.x + x.y + x.z + x.w; 462} 463`,WS=` 464struct Params { 465 threads: u32, 466 iterations: u32, 467}; 468 469@group(0) @binding(0) var<uniform> params: Params; 470@group(0) @binding(1) var<storage, read_write> out: array<f32>; 471 472// Hashes a seed into four pseudo-random weights in about [-1/32, 1/32] (small 473// enough that the 8-wide dot products below are a contraction, so the 474// recurrence stays bounded for any iteration count). 475fn weights(seed: u32) -> vec4<f32> { 476 let h = seed * 0x9e3779b1u; 477 let bytes = vec4<u32>(h & 0xffu, (h >> 8u) & 0xffu, (h >> 16u) & 0xffu, h >> 24u); 478 return (vec4<f32>(bytes) - vec4<f32>(127.5)) * (1.0 / 4096.0); 479} 480 481@compute @workgroup_size(64) 482fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 483 let idx = gid.x; 484 if (idx >= params.threads) { 485 return; 486 } 487 let w00: vec4<f32> = weights(idx * 8u + 1u); 488 let w01: vec4<f32> = weights(idx * 8u + 2u); 489 let w10: vec4<f32> = weights(idx * 8u + 3u); 490 let w11: vec4<f32> = weights(idx * 8u + 4u); 491 let w20: vec4<f32> = weights(idx * 8u + 5u); 492 let w21: vec4<f32> = weights(idx * 8u + 6u); 493 let w30: vec4<f32> = weights(idx * 8u + 7u); 494 let w31: vec4<f32> = weights(idx * 8u + 8u); 495 var x0: vec4<f32> = vec4<f32>(f32(idx & 255u) * 0.001 + 0.1, 0.2, 0.3, 0.4); 496 var x1: vec4<f32> = vec4<f32>(f32(idx & 255u) * 0.001 + 0.2, 0.4, 0.6, 0.8); 497 var c = vec4<f32>(0.125, 0.25, 0.375, 0.5); 498 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 499 let o0 = dot(w00, x0) + dot(w01, x1) + c.x; 500 let o1 = dot(w10, x0) + dot(w11, x1) + c.y; 501 let o2 = dot(w20, x0) + dot(w21, x1) + c.z; 502 let o3 = dot(w30, x0) + dot(w31, x1) + c.w; 503 x0 = x1; 504 x1 = vec4<f32>(o0, o1, o2, o3); 505 c = c.yzwx; // Nonzero rotating forcing prevents decay to zero. 506 } 507 out[idx] = x0.x + x0.y + x0.z + x0.w + x1.x + x1.y + x1.z + x1.w; 508} 509`,GS=1024*1024,KS=1024,qS=16;async function JS(e,t,n={}){let r=n.threads??GS,i=n.iterations??t.defaultIterations??KS,a=e=>({id:t.id,category:`compute`,rows:r,cols:e,amountPerOp:r*e*t.flopsPerIteration}),o=a(i);if(t.requiresF16&&!e.info.supportsF16)return{kind:`skipped`,result:iS(o,`Device/browser does not support the "shader-f16" WebGPU feature.`)};if(t.requiresI8Dot&&!e.info.supportsI8Dot)return{kind:`skipped`,result:iS(o,`Device/browser does not support the "packed_4x8_integer_dot_product" WebGPU feature.`)};let{device:s}=e,c=await tS(s,t.id,t.wgsl),l=lS(s,new Uint32Array([r,i]),`params`),u=uS(s,r*4,`out`),d=s.createBindGroup({layout:c.getBindGroupLayout(0),entries:[{binding:0,resource:{buffer:l}},{binding:1,resource:{buffer:u}}]}),f=n.iterations===void 0?{min:Math.min(i,t.minIterations??qS),max:i,apply:e=>s.queue.writeBuffer(l,0,new Uint32Array([r,e]))}:void 0;return rS({...o,ctx:e,workgroupsPerIteration:[Math.ceil(r/64),1,1],pipeline:c,bindGroup:d,work:f,metaAtWork:a,targetMs:n.targetMs,targetDispatchMs:n.targetDispatchMs,warmups:n.warmups,maxIterations:n.maxIterations})}function YS(e,t={}){return JS(e,{id:`f32-fma-scalar`,wgsl:VS,flopsPerIteration:64,defaultIterations:256},t)}function XS(e,t={}){return JS(e,{id:`f32-fma-vec4`,wgsl:HS,flopsPerIteration:256,defaultIterations:256},t)}function ZS(e,t={}){return JS(e,{id:`f32-fma-mat4`,wgsl:US,flopsPerIteration:32,defaultIterations:1024},t)}function QS(e,t={}){return JS(e,{id:`f32-fma-matvec`,wgsl:WS,flopsPerIteration:64,defaultIterations:512},t)}var $S=` 510enable f16; 511 512struct Params { 513 threads: u32, 514 iterations: u32, 515}; 516 517@group(0) @binding(0) var<uniform> params: Params; 518@group(0) @binding(1) var<storage, read_write> out: array<f32>; 519 520@compute @workgroup_size(64) 521fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 522 let idx = gid.x; 523 if (idx >= params.threads) { 524 return; 525 } 526 let a: f16 = f16(1.0) - f16(idx & 15u) * f16(0.001); 527 let b: f16 = f16(0.5) + f16(idx & 7u) * f16(0.001); 528 var x0: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.01); 529 var x1: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.02); 530 var x2: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.03); 531 var x3: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.04); 532 var x4: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.05); 533 var x5: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.06); 534 var x6: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.07); 535 var x7: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.08); 536 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 537 x0 = x0 * a + b; 538 x1 = x1 * a + b; 539 x2 = x2 * a + b; 540 x3 = x3 * a + b; 541 x4 = x4 * a + b; 542 x5 = x5 * a + b; 543 x6 = x6 * a + b; 544 x7 = x7 * a + b; 545 x0 = x0 * a + b; 546 x1 = x1 * a + b; 547 x2 = x2 * a + b; 548 x3 = x3 * a + b; 549 x4 = x4 * a + b; 550 x5 = x5 * a + b; 551 x6 = x6 * a + b; 552 x7 = x7 * a + b; 553 x0 = x0 * a + b; 554 x1 = x1 * a + b; 555 x2 = x2 * a + b; 556 x3 = x3 * a + b; 557 x4 = x4 * a + b; 558 x5 = x5 * a + b; 559 x6 = x6 * a + b; 560 x7 = x7 * a + b; 561 x0 = x0 * a + b; 562 x1 = x1 * a + b; 563 x2 = x2 * a + b; 564 x3 = x3 * a + b; 565 x4 = x4 * a + b; 566 x5 = x5 * a + b; 567 x6 = x6 * a + b; 568 x7 = x7 * a + b; 569 } 570 out[idx] = f32(x0 + x1 + x2 + x3 + x4 + x5 + x6 + x7); 571} 572`,eC=` 573enable f16; 574 575struct Params { 576 threads: u32, 577 iterations: u32, 578}; 579 580@group(0) @binding(0) var<uniform> params: Params; 581@group(0) @binding(1) var<storage, read_write> out: array<f32>; 582 583@compute @workgroup_size(64) 584fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 585 let idx = gid.x; 586 if (idx >= params.threads) { 587 return; 588 } 589 let s: f16 = f16(idx & 15u) * f16(0.001); 590 let half: f16 = f16(0.5); 591 let one: f16 = f16(1.0); 592 let a: vec4<f16> = vec4<f16>(one - s, one - f16(2.0) * s, one - f16(3.0) * s, one - f16(4.0) * s); 593 let b: vec4<f16> = vec4<f16>(half + s, half + f16(2.0) * s, half + f16(3.0) * s, half + f16(4.0) * s); 594 var x0: vec4<f16> = vec4<f16>(f16(idx & 255u) * f16(0.0001) + f16(0.01)); 595 var x1: vec4<f16> = vec4<f16>(f16(idx & 255u) * f16(0.0001) + f16(0.02)); 596 var x2: vec4<f16> = vec4<f16>(f16(idx & 255u) * f16(0.0001) + f16(0.03)); 597 var x3: vec4<f16> = vec4<f16>(f16(idx & 255u) * f16(0.0001) + f16(0.04)); 598 var x4: vec4<f16> = vec4<f16>(f16(idx & 255u) * f16(0.0001) + f16(0.05)); 599 var x5: vec4<f16> = vec4<f16>(f16(idx & 255u) * f16(0.0001) + f16(0.06)); 600 var x6: vec4<f16> = vec4<f16>(f16(idx & 255u) * f16(0.0001) + f16(0.07)); 601 var x7: vec4<f16> = vec4<f16>(f16(idx & 255u) * f16(0.0001) + f16(0.08)); 602 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 603 x0 = x0 * a + b; 604 x1 = x1 * a + b; 605 x2 = x2 * a + b; 606 x3 = x3 * a + b; 607 x4 = x4 * a + b; 608 x5 = x5 * a + b; 609 x6 = x6 * a + b; 610 x7 = x7 * a + b; 611 x0 = x0 * a + b; 612 x1 = x1 * a + b; 613 x2 = x2 * a + b; 614 x3 = x3 * a + b; 615 x4 = x4 * a + b; 616 x5 = x5 * a + b; 617 x6 = x6 * a + b; 618 x7 = x7 * a + b; 619 x0 = x0 * a + b; 620 x1 = x1 * a + b; 621 x2 = x2 * a + b; 622 x3 = x3 * a + b; 623 x4 = x4 * a + b; 624 x5 = x5 * a + b; 625 x6 = x6 * a + b; 626 x7 = x7 * a + b; 627 x0 = x0 * a + b; 628 x1 = x1 * a + b; 629 x2 = x2 * a + b; 630 x3 = x3 * a + b; 631 x4 = x4 * a + b; 632 x5 = x5 * a + b; 633 x6 = x6 * a + b; 634 x7 = x7 * a + b; 635 } 636 let t = x0 + x1 + x2 + x3 + x4 + x5 + x6 + x7; 637 out[idx] = f32(t.x + t.y + t.z + t.w); 638} 639`,tC=` 640enable f16; 641 642struct Params { 643 threads: u32, 644 iterations: u32, 645}; 646 647@group(0) @binding(0) var<uniform> params: Params; 648@group(0) @binding(1) var<storage, read_write> out: array<f32>; 649 650fn weights(seed: u32) -> vec4<f16> { 651 let h = seed * 0x9e3779b1u; 652 let bytes = vec4<u32>(h & 255u, (h >> 8u) & 255u, (h >> 16u) & 255u, h >> 24u); 653 return (vec4<f16>(bytes) + vec4<f16>(32.0)) * f16(1.0 / 4096.0); 654} 655 656@compute @workgroup_size(64) 657fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 658 let idx = gid.x; 659 if (idx >= params.threads) { 660 return; 661 } 662 let seed = idx * 4u; 663 // Every entry is in [1/128, 1/8): each absolute row sum is < 1/2. 664 let m = mat4x4<f16>(weights(seed + 1u), weights(seed + 2u), weights(seed + 3u), weights(seed + 4u)); 665 var c = vec4<f16>(0.125, 0.25, 0.375, 0.5); 666 var x = vec4<f16>(0.1, 0.2, 0.3, 0.4) + vec4<f16>(f16(idx & 255u) * f16(0.0001)); 667 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 668 x = m * x + c; 669 c = c.yzwx; // A four-step forcing cycle avoids a constant fixed point. 670 } 671 out[idx] = f32(x.x + x.y + x.z + x.w); 672} 673`,nC=` 674enable f16; 675 676struct Params { 677 threads: u32, 678 iterations: u32, 679}; 680 681@group(0) @binding(0) var<uniform> params: Params; 682@group(0) @binding(1) var<storage, read_write> out: array<f32>; 683 684// Same weight hash as the fp32 kernel, but producing vec4<f16>. 685fn weights(seed: u32) -> vec4<f16> { 686 let h = seed * 0x9e3779b1u; 687 let bytes = vec4<u32>(h & 0xffu, (h >> 8u) & 0xffu, (h >> 16u) & 0xffu, h >> 24u); 688 return (vec4<f16>(bytes) - vec4<f16>(127.5)) * f16(1.0 / 4096.0); 689} 690 691@compute @workgroup_size(64) 692fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 693 let idx = gid.x; 694 if (idx >= params.threads) { 695 return; 696 } 697 let w00: vec4<f16>
697 = weights(idx * 8u + 1u); 698 let w01: vec4<f16> = weights(idx * 8u + 2u); 699 let w10: vec4<f16> = weights(idx * 8u + 3u); 700 let w11: vec4<f16> = weights(idx * 8u + 4u); 701 let w20: vec4<f16> = weights(idx * 8u + 5u); 702 let w21: vec4<f16> = weights(idx * 8u + 6u); 703 let w30: vec4<f16> = weights(idx * 8u + 7u); 704 let w31: vec4<f16> = weights(idx * 8u + 8u); 705 var x0: vec4<f16> = vec4<f16>(f16(idx & 255u) * f16(0.001) + f16(0.1), f16(0.2), f16(0.3), f16(0.4)); 706 var x1: vec4<f16> = vec4<f16>(f16(idx & 255u) * f16(0.001) + f16(0.2), f16(0.4), f16(0.6), f16(0.8)); 707 var c = vec4<f16>(0.125, 0.25, 0.375, 0.5); 708 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 709 let o0 = dot(w00, x0) + dot(w01, x1) + c.x; 710 let o1 = dot(w10, x0) + dot(w11, x1) + c.y; 711 let o2 = dot(w20, x0) + dot(w21, x1) + c.z; 712 let o3 = dot(w30, x0) + dot(w31, x1) + c.w; 713 x0 = x1; 714 x1 = vec4<f16>(o0, o1, o2, o3); 715 c = c.yzwx; // Nonzero rotating forcing prevents decay to zero. 716 } 717 out[idx] = f32(x0.x + x0.y + x0.z + x0.w + x1.x + x1.y + x1.z + x1.w); 718} 719`;function rC(e,t={}){return JS(e,{id:`f16-fma-scalar`,wgsl:$S,flopsPerIteration:64,defaultIterations:256,requiresF16:!0},t)}function iC(e,t={}){return JS(e,{id:`f16-fma-vec4`,wgsl:eC,flopsPerIteration:256,defaultIterations:256,requiresF16:!0},t)}function aC(e,t={}){return JS(e,{id:`f16-fma-mat4`,wgsl:tC,flopsPerIteration:32,defaultIterations:1024,requiresF16:!0},t)}function oC(e,t={}){return JS(e,{id:`f16-fma-matvec`,wgsl:nC,flopsPerIteration:64,defaultIterations:512,requiresF16:!0},t)}var sC=` 720struct Params { 721 threads: u32, 722 iterations: u32, 723}; 724 725@group(0) @binding(0) var<uniform> params: Params; 726@group(0) @binding(1) var<storage, read_write> out: array<f32>; 727 728@compute @workgroup_size(64) 729fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 730 let idx = gid.x; 731 if (idx >= params.threads) { 732 return; 733 } 734 let a: i32 = 3 + i32(idx & 15u); 735 let b: i32 = 5 + i32(idx & 7u); 736 var x0: i32 = i32(idx & 255u) + 1; 737 var x1: i32 = i32(idx & 255u) + 2; 738 var x2: i32 = i32(idx & 255u) + 3; 739 var x3: i32 = i32(idx & 255u) + 4; 740 var x4: i32 = i32(idx & 255u) + 5; 741 var x5: i32 = i32(idx & 255u) + 6; 742 var x6: i32 = i32(idx & 255u) + 7; 743 var x7: i32 = i32(idx & 255u) + 8; 744 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 745 x0 = x0 * a + b; 746 x1 = x1 * a + b; 747 x2 = x2 * a + b; 748 x3 = x3 * a + b; 749 x4 = x4 * a + b; 750 x5 = x5 * a + b; 751 x6 = x6 * a + b; 752 x7 = x7 * a + b; 753 x0 = x0 * a + b; 754 x1 = x1 * a + b; 755 x2 = x2 * a + b; 756 x3 = x3 * a + b; 757 x4 = x4 * a + b; 758 x5 = x5 * a + b; 759 x6 = x6 * a + b; 760 x7 = x7 * a + b; 761 x0 = x0 * a + b; 762 x1 = x1 * a + b; 763 x2 = x2 * a + b; 764 x3 = x3 * a + b; 765 x4 = x4 * a + b; 766 x5 = x5 * a + b; 767 x6 = x6 * a + b; 768 x7 = x7 * a + b; 769 x0 = x0 * a + b; 770 x1 = x1 * a + b; 771 x2 = x2 * a + b; 772 x3 = x3 * a + b; 773 x4 = x4 * a + b; 774 x5 = x5 * a + b; 775 x6 = x6 * a + b; 776 x7 = x7 * a + b; 777 } 778 out[idx] = f32(x0 + x1 + x2 + x3 + x4 + x5 + x6 + x7); 779} 780`,cC=` 781struct Params { 782 threads: u32, 783 iterations: u32, 784}; 785 786@group(0) @binding(0) var<uniform> params: Params; 787@group(0) @binding(1) var<storage, read_write> out: array<f32>; 788 789@compute @workgroup_size(64) 790fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 791 let idx = gid.x; 792 if (idx >= params.threads) { 793 return; 794 } 795 let s: i32 = i32(idx & 15u); 796 let a: vec4<i32> = vec4<i32>(3 + s, 5 + s, 7 + s, 9 + s); 797 let b: vec4<i32> = vec4<i32>(11 - s, 13 - s, 17 - s, 19 - s); 798 var x0: vec4<i32> = vec4<i32>(i32(idx & 255u) + 1); 799 var x1: vec4<i32> = vec4<i32>(i32(idx & 255u) + 2); 800 var x2: vec4<i32> = vec4<i32>(i32(idx & 255u) + 3); 801 var x3: vec4<i32> = vec4<i32>(i32(idx & 255u) + 4); 802 var x4: vec4<i32> = vec4<i32>(i32(idx & 255u) + 5); 803 var x5: vec4<i32> = vec4<i32>(i32(idx & 255u) + 6); 804 var x6: vec4<i32> = vec4<i32>(i32(idx & 255u) + 7); 805 var x7: vec4<i32> = vec4<i32>(i32(idx & 255u) + 8); 806 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 807 x0 = x0 * a + b; 808 x1 = x1 * a + b; 809 x2 = x2 * a + b; 810 x3 = x3 * a + b; 811 x4 = x4 * a + b; 812 x5 = x5 * a + b; 813 x6 = x6 * a + b; 814 x7 = x7 * a + b; 815 x0 = x0 * a + b; 816 x1 = x1 * a + b; 817 x2 = x2 * a + b; 818 x3 = x3 * a + b; 819 x4 = x4 * a + b; 820 x5 = x5 * a + b; 821 x6 = x6 * a + b; 822 x7 = x7 * a + b; 823 x0 = x0 * a + b; 824 x1 = x1 * a + b; 825 x2 = x2 * a + b; 826 x3 = x3 * a + b; 827 x4 = x4 * a + b; 828 x5 = x5 * a + b; 829 x6 = x6 * a + b; 830 x7 = x7 * a + b; 831 x0 = x0 * a + b; 832 x1 = x1 * a + b; 833 x2 = x2 * a + b; 834 x3 = x3 * a + b; 835 x4 = x4 * a + b; 836 x5 = x5 * a + b; 837 x6 = x6 * a + b; 838 x7 = x7 * a + b; 839 } 840 let t = x0 + x1 + x2 + x3 + x4 + x5 + x6 + x7; 841 out[idx] = f32(t.x + t.y + t.z + t.w); 842} 843`,lC=` 844struct Params { 845 threads: u32, 846 iterations: u32, 847}; 848 849@group(0) @binding(0) var<uniform> params: Params; 850@group(0) @binding(1) var<storage, read_write> out: array<f32>; 851 852@compute @workgroup_size(64) 853fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 854 let idx = gid.x; 855 if (idx >= params.threads) { 856 return; 857 } 858 // Every matrix entry is runtime-derived: a literal 1 here would let the 859 // compiler fold 1 * x away and skip three quarters of the multiplies. 860 let s: i32 = i32(idx & 15u) + 1; 861 let t: i32 = i32((idx >> 4u) & 15u) + 2; 862 let u: i32 = i32((idx >> 8u) & 15u) + 3; 863 let v: i32 = i32((idx >> 12u) & 15u) + 4;
864 let m0: vec4<i32> = vec4<i32>(s, t, u, v); 865 let m1: vec4<i32> = vec4<i32>(v, s, t, u); 866 let m2: vec4<i32> = vec4<i32>(u, v, s, t); 867 let m3: vec4<i32> = vec4<i32>(t, u, v, s); 868 let c: vec4<i32> = vec4<i32>(s, t, u, v); 869 var x: vec4<i32> = vec4<i32>(i32(idx & 255u)); 870 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 871 x = vec4<i32>(dot(m0, x), dot(m1, x), dot(m2, x), dot(m3, x)) + c; 872 } 873 out[idx] = f32(x.x + x.y + x.z + x.w); 874} 875`,uC=` 876struct Params { 877 threads: u32, 878 iterations: u32, 879}; 880 881@group(0) @binding(0) var<uniform> params: Params; 882@group(0) @binding(1) var<storage, read_write> out: array<f32>; 883 884// Hashes a seed into four int8-range weights, held unpacked as a vec4<i32> 885// (what a dequantize-on-load kernel holds after unpack4xI8). 886fn weights(seed: u32) -> vec4<i32> { 887 return unpack4xI8(seed * 0x9e3779b1u); 888} 889 890@compute @workgroup_size(64) 891fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 892 let idx = gid.x; 893 if (idx >= params.threads) { 894 return; 895 } 896 let w00: vec4<i32> = weights(idx * 8u + 1u); 897 let w01: vec4<i32> = weights(idx * 8u + 2u); 898 let w10: vec4<i32> = weights(idx * 8u + 3u); 899 let w11: vec4<i32> = weights(idx * 8u + 4u); 900 let w20: vec4<i32> = weights(idx * 8u + 5u); 901 let w21: vec4<i32> = weights(idx * 8u + 6u); 902 let w30: vec4<i32> = weights(idx * 8u + 7u); 903 let w31: vec4<i32> = weights(idx * 8u + 8u); 904 var x0: vec4<i32> = vec4<i32>(i32(idx & 255u) + 1, 2, 3, 4); 905 var x1: vec4<i32> = vec4<i32>(i32(idx & 255u) + 2, 4, 6, 8); 906 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 907 let o0 = dot(w00, x0) + dot(w01, x1); 908 let o1 = dot(w10, x0) + dot(w11, x1); 909 let o2 = dot(w20, x0) + dot(w21, x1); 910 let o3 = dot(w30, x0) + dot(w31, x1); 911 x0 = x1; 912 x1 = vec4<i32>(o0, o1, o2, o3) >> vec4<u32>(4u); 913 } 914 out[idx] = f32(x0.x + x0.y + x0.z + x0.w + x1.x + x1.y + x1.z + x1.w); 915} 916`,dC=` 917requires packed_4x8_integer_dot_product; 918 919struct Params { 920 threads: u32, 921 iterations: u32, 922}; 923 924@group(0) @binding(0) var<uniform> params: Params; 925@group(0) @binding(1) var<storage, read_write> out: array<f32>; 926 927// Hashes a seed into a u32 holding four packed int8 weights, exactly the 928// storage format dot4I8Packed consumes. 929fn weights(seed: u32) -> u32 { 930 return seed * 0x9e3779b1u; 931} 932 933@compute @workgroup_size(64) 934fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 935 let idx = gid.x; 936 if (idx >= params.threads) { 937 return; 938 } 939 let w00: u32 = weights(idx * 8u + 1u); 940 let w01: u32 = weights(idx * 8u + 2u); 941 let w10: u32 = weights(idx * 8u + 3u); 942 let w11: u32 = weights(idx * 8u + 4u); 943 let w20: u32 = weights(idx * 8u + 5u); 944 let w21: u32 = weights(idx * 8u + 6u); 945 let w30: u32 = weights(idx * 8u + 7u); 946 let w31: u32 = weights(idx * 8u + 8u); 947 var x0: u32 = (idx * 0x85ebca6bu) ^ 0x01020304u; 948 var x1: u32 = (idx * 0x85ebca6bu) ^ 0x02040608u; 949 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 950 let o0 = dot4I8Packed(w00, x0) + dot4I8Packed(w01, x1); 951 let o1 = dot4I8Packed(w10, x0) + dot4I8Packed(w11, x1); 952 let o2 = dot4I8Packed(w20, x0) + dot4I8Packed(w21, x1); 953 let o3 = dot4I8Packed(w30, x0) + dot4I8Packed(w31, x1); 954 x0 = x1; 955 x1 = pack4xI8(vec4<i32>(o0, o1, o2, o3) >> vec4<u32>(4u)); 956 } 957 out[idx] = f32(i32(x0) + i32(x1)); 958} 959`,fC=` 960requires packed_4x8_integer_dot_product; 961 962struct Params { 963 threads: u32, 964 iterations: u32, 965}; 966 967@group(0) @binding(0) var<uniform> params: Params; 968@group(0) @binding(1) var<storage, read_write> out: array<f32>; 969 970@compute @workgroup_size(64) 971fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 972 let idx = gid.x; 973 if (idx >= params.threads) { 974 return; 975 } 976 let b: u32 = 0x05060708u ^ (idx * 0x85ebca6bu); 977 var a0: u32 = 0x01020300u ^ (idx * 0x9e3779b1u); 978 var acc0: i32 = i32(idx & 255u) + 0; 979 var a1: u32 = 0x01020301u ^ (idx * 0x9e3779b1u); 980 var acc1: i32 = i32(idx & 255u) + 1; 981 var a2: u32 = 0x01020302u ^ (idx * 0x9e3779b1u); 982 var acc2: i32 = i32(idx & 255u) + 2; 983 var a3: u32 = 0x01020303u ^ (idx * 0x9e3779b1u); 984 var acc3: i32 = i32(idx & 255u) + 3; 985 var a4: u32 = 0x01020304u ^ (idx * 0x9e3779b1u); 986 var acc4: i32 = i32(idx & 255u) + 4;
987 var a5: u32 = 0x01020305u ^ (idx * 0x9e3779b1u); 988 var acc5: i32 = i32(idx & 255u) + 5; 989 var a6: u32 = 0x01020306u ^ (idx * 0x9e3779b1u); 990 var acc6: i32 = i32(idx & 255u) + 6; 991 var a7: u32 = 0x01020307u ^ (idx * 0x9e3779b1u); 992 var acc7: i32 = i32(idx & 255u) + 7; 993 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 994 acc0 = acc0 + dot4I8Packed(a0, b); 995 a0 = a0 ^ u32(acc0); 996 acc1 = acc1 + dot4I8Packed(a1, b); 997 a1 = a1 ^ u32(acc1); 998 acc2 = acc2 + dot4I8Packed(a2, b); 999 a2 = a2 ^ u32(acc2); 1000 acc3 = acc3 + dot4I8Packed(a3, b); 1001 a3 = a3 ^ u32(acc3); 1002 acc4 = acc4 + dot4I8Packed(a4, b); 1003 a4 = a4 ^ u32(acc4); 1004 acc5 = acc5 + dot4I8Packed(a5, b); 1005 a5 = a5 ^ u32(acc5); 1006 acc6 = acc6 + dot4I8Packed(a6, b); 1007 a6 = a6 ^ u32(acc6); 1008 acc7 = acc7 + dot4I8Packed(a7, b); 1009 a7 = a7 ^ u32(acc7); 1010 } 1011 out[idx] = f32(acc0 + acc1 + acc2 + acc3 + acc4 + acc5 + acc6 + acc7); 1012} 1013`;function pC(e,t={}){return JS(e,{id:`i32-mad-scalar`,wgsl:sC,flopsPerIteration:64,defaultIterations:256},t)}function mC(e,t={}){return JS(e,{id:`i32-mad-vec4`,wgsl:cC,flopsPerIteration:256,defaultIterations:256},t)}function hC(e,t={}){return JS(e,{id:`i32-mad-mat4`,wgsl:lC,flopsPerIteration:32,defaultIterations:1024},t)}function gC(e,t={}){return JS(e,{id:`i32-mad-matvec`,wgsl:uC,flopsPerIteration:64,defaultIterations:512},t)}function _C(e,t={}){return JS(e,{id:`i8-dp4a-matvec`,wgsl:dC,flopsPerIteration:64,defaultIterations:512,requiresI8Dot:!0},t)}function vC(e,t={}){return JS(e,{id:`i8-dp4a`,wgsl:fC,flopsPerIteration:64,defaultIterations:256,requiresI8Dot:!0},t)}var yC=` 1014struct Params { 1015 threads: u32, 1016 iterations: u32, 1017}; 1018 1019@group(0) @binding(0) var<uniform> params: Params; 1020@group(0) @binding(1) var<storage, read_write> out: array<f32>; 1021 1022@compute @workgroup_size(64) 1023fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 1024 let idx = gid.x; 1025 if (idx >= params.threads) { 1026 return; 1027 } 1028 let a: f32 = 1.2 + f32(idx & 15u) * 0.05; 1029 let b: f32 = 0.5 + f32(idx & 7u) * 0.001; 1030 var x0: f32 = f32(idx & 255u) * 0.0001 + 0.01; 1031 var x1: f32 = f32(idx & 255u) * 0.0001 + 0.02; 1032 var x2: f32 = f32(idx & 255u) * 0.0001 + 0.03; 1033 var x3: f32 = f32(idx & 255u) * 0.0001 + 0.04; 1034 var x4: f32 = f32(idx & 255u) * 0.0001 + 0.05; 1035 var x5: f32 = f32(idx & 255u) * 0.0001 + 0.06; 1036 var x6: f32 = f32(idx & 255u) * 0.0001 + 0.07; 1037 var x7: f32 = f32(idx & 255u) * 0.0001 + 0.08; 1038 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 1039 x0 = a / x0 + b; 1040 x1 = a / x1 + b; 1041 x2 = a / x2 + b; 1042 x3 = a / x3 + b; 1043 x4 = a / x4 + b; 1044 x5 = a / x5 + b; 1045 x6 = a / x6 + b; 1046 x7 = a / x7 + b; 1047 x0 = a / x0 + b; 1048 x1 = a / x1 + b; 1049 x2 = a / x2 + b; 1050 x3 = a / x3 + b; 1051 x4 = a / x4 + b; 1052 x5 = a / x5 + b; 1053 x6 = a / x6 + b; 1054 x7 = a / x7 + b; 1055 x0 = a / x0 + b; 1056 x1 = a / x1 + b; 1057 x2 = a / x2 + b; 1058 x3 = a / x3 + b; 1059 x4 = a / x4 + b; 1060 x5 = a / x5 + b; 1061 x6 = a / x6 + b; 1062 x7 = a / x7 + b; 1063 x0 = a / x0 + b; 1064 x1 = a / x1 + b; 1065 x2 = a / x2 + b; 1066 x3 = a / x3 + b; 1067 x4 = a / x4 + b; 1068 x5 = a / x5 + b; 1069 x6 = a / x6 + b; 1070 x7 = a / x7 + b; 1071 } 1072 out[idx] = x0 + x1 + x2 + x3 + x4 + x5 + x6 + x7; 1073} 1074`,bC=` 1075struct Params { 1076 threads: u32, 1077 iterations: u32, 1078}; 1079 1080@group(0) @binding(0) var<uniform> params: Params; 1081@group(0) @binding(1) var<storage, read_write> out: array<f32>; 1082 1083@compute @workgroup_size(64) 1084fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 1085 let idx = gid.x; 1086 if (idx >= params.threads) { 1087 return; 1088 } 1089 let a: i32 = 100003 + i32(idx & 255u) * 7; 1090 let b: i32 = 5 + i32(idx & 7u); 1091 var x0: i32 = i32(idx & 255u) + 1000; 1092 var x1: i32 = i32(idx & 255u) + 2000; 1093 var x2: i32 = i32(idx & 255u) + 3000; 1094 var x3: i32 = i32(idx & 255u) + 4000; 1095 var x4: i32 = i32(idx & 255u) + 5000; 1096 var x5: i32 = i32(idx & 255u) + 6000; 1097 var x6: i32 = i32(idx & 255u) + 7000; 1098 var x7: i32 = i32(idx & 255u) + 8000; 1099 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 1100 x0 = a / x0 + b; 1101 x1 = a / x1 + b; 1102 x2 = a / x2 + b; 1103 x3 = a / x3 + b; 1104 x4 = a / x4 + b; 1105 x5 = a / x5 + b; 1106 x6 = a / x6 + b; 1107 x7 = a / x7 + b; 1108 x0 = a / x0 + b; 1109 x1 = a / x1 + b; 1110 x2 = a / x2 + b; 1111 x3 = a / x3 + b; 1112 x4 = a / x4 + b; 1113 x5 = a / x5 + b; 1114 x6 = a / x6 + b; 1115 x7 = a / x7 + b; 1116 x0 = a / x0 + b; 1117 x1 = a / x1 + b; 1118 x2 = a / x2 + b; 1119 x3 = a / x3 + b; 1120 x4 = a / x4 + b; 1121 x5 = a / x5 + b; 1122 x6 = a / x6 + b; 1123 x7 = a / x7 + b; 1124 x0 = a / x0 + b; 1125 x1 = a / x1 + b; 1126 x2 = a / x2 + b; 1127 x3 = a / x3 + b; 1128 x4 = a / x4 + b; 1129 x5 = a / x5 + b; 1130 x6 = a / x6 + b; 1131 x7 = a / x7 + b; 1132 } 1133 out[idx] = f32(x0 + x1 + x2 + x3 + x4 + x5 + x6 + x7); 1134} 1135`,xC=` 1136struct Params { 1137 threads: u32, 1138 iterations: u32, 1139}; 1140 1141@group(0) @binding(0) var<uniform> params: Params; 1142@group(0) @binding(1) var<storage, read_write> out: array<f32>; 1143 1144@compute @workgroup_size(64) 1145fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 1146 let idx = gid.x; 1147 if (idx >= params.threads) { 1148 return; 1149 } 1150 let b: f32 = 0.5 + f32(idx & 7u) * 0.001; 1151 var x0: f32 = f32(idx & 255u) * 0.0001 + 0.01; 1152 var x1: f32 = f32(idx & 255u) * 0.0001 + 0.02; 1153 var x2: f32 = f32(idx & 255u) * 0.0001 + 0.03; 1154 var x3: f32 = f32(idx & 255u) * 0.0001 + 0.04; 1155 var x4: f32 = f32(idx & 255u) * 0.0001 + 0.05; 1156 var x5: f32 = f32(idx & 255u) * 0.0001 + 0.06; 1157 var x6: f32 = f32(idx & 255u) * 0.0001 + 0.07; 1158 var x7: f32 = f32(idx & 255u) * 0.0001 + 0.08; 1159 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 1160 x0 = sqrt(x0) + b; 1161 x1 = sqrt(x1) + b; 1162 x2 = sqrt(x2) + b; 1163 x3 = sqrt(x3) + b; 1164 x4 = sqrt(x4) + b; 1165 x5 = sqrt(x5) + b; 1166 x6 = sqrt(x6) + b; 1167 x7 = sqrt(x7) + b; 1168 x0 = sqrt(x0) + b; 1169 x1 = sqrt(x1) + b; 1170 x2 = sqrt(x2) + b; 1171 x3 = sqrt(x3) + b; 1172 x4 = sqrt(x4) + b; 1173 x5 = sqrt(x5) + b; 1174 x6 = sqrt(x6) + b; 1175 x7 = sqrt(x7) + b; 1176 x0 = sqrt(x0) + b; 1177 x1 = sqrt(x1) + b; 1178 x2 = sqrt(x2) + b; 1179 x3 = sqrt(x3) + b; 1180 x4 = sqrt(x4) + b; 1181 x5 = sqrt(x5) + b; 1182 x6 = sqrt(x6) + b; 1183 x7 = sqrt(x7) + b; 1184 x0 = sqrt(x0) + b; 1185 x1 = sqrt(x1) + b; 1186 x2 = sqrt(x2) + b; 1187 x3 = sqrt(x3) + b; 1188 x4 = sqrt(x4) + b; 1189 x5 = sqrt(x5) + b; 1190 x6 = sqrt(x6) + b; 1191 x7 = sqrt(x7) + b; 1192 } 1193 out[idx] = x0 + x1 + x2 + x3 + x4 + x5 + x6 + x7; 1194} 1195`,SC=` 1196struct Params { 1197 threads: u32, 1198 iterations: u32, 1199}; 1200 1201@group(0) @binding(0) var<uniform> params: Params; 1202@group(0) @binding(1) var<storage, read_write> out: array<f32>; 1203 1204@compute @workgroup_size(64) 1205fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 1206 let idx = gid.x; 1207 if (idx >= params.threads) { 1208 return; 1209 } 1210 let b: f32 = 0.5 + f32(idx & 7u) * 0.001; 1211 var x0: f32 = f32(idx & 255u) * 0.0001 + 0.01; 1212 var x1: f32 = f32(idx & 255u) * 0.0001 + 0.02; 1213 var x2: f32 = f32(idx & 255u) * 0.0001 + 0.03; 1214 var x3: f32 = f32(idx & 255u) * 0.0001 + 0.04; 1215 var x4: f32 = f32(idx & 255u) * 0.0001 + 0.05; 1216 var x5: f32 = f32(idx & 255u) * 0.0001 + 0.06; 1217 var x6: f32 = f32(idx & 255u) * 0.0001 + 0.07; 1218 var x7: f32 = f32(idx & 255u) * 0.0001 + 0.08; 1219 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 1220 x0 = inverseSqrt(x0) + b; 1221 x1 = inverseSqrt(x1) + b; 1222 x2 = inverseSqrt(x2) + b; 1223 x3 = inverseSqrt(x3) + b; 1224 x4 = inverseSqrt(x4) + b; 1225 x5 = inverseSqrt(x5) + b; 1226 x6 = inverseSqrt(x6) + b; 1227 x7 = inverseSqrt(x7) + b; 1228 x0 = inverseSqrt(x0) + b; 1229 x1 = inverseSqrt(x1) + b; 1230 x2 = inverseSqrt(x2) + b; 1231 x3 = inverseSqrt(x3) + b; 1232 x4 = inverseSqrt(x4) + b; 1233 x5 = inverseSqrt(x5) + b; 1234 x6 = inverseSqrt(x6) + b; 1235 x7 = inverseSqrt(x7) + b; 1236 x0 = inverseSqrt(x0) + b; 1237 x1 = inverseSqrt(x1) + b; 1238 x2 = inverseSqrt(x2) + b; 1239 x3 = inverseSqrt(x3) + b; 1240 x4 = inverseSqrt(x4) + b; 1241 x5 = inverseSqrt(x5) + b; 1242 x6 = inverseSqrt(x6) + b; 1243 x7 = inverseSqrt(x7) + b; 1244 x0 = inverseSqrt(x0) + b; 1245 x1 = inverseSqrt(x1) + b; 1246 x2 = inverseSqrt(x2) + b; 1247 x3 = inverseSqrt(x3) + b; 1248 x4 = inverseSqrt(x4) + b; 1249 x5 = inverseSqrt(x5) + b; 1250 x6 = inverseSqrt(x6) + b; 1251 x7 = inverseSqrt(x7) + b; 1252 } 1253 out[idx] = x0 + x1 + x2 + x3 + x4 + x5 + x6 + x7; 1254} 1255`,CC=` 1256struct Params { 1257 threads: u32, 1258 iterations: u32, 1259}; 1260 1261@group(0) @binding(0) var<uniform> params: Params; 1262@group(0) @binding(1) var<storage, read_write> out: array<f32>; 1263 1264@compute @workgroup_size(64) 1265fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 1266 let idx = gid.x; 1267 if (idx >= params.threads) { 1268 return; 1269 } 1270 let e: f32 = 0.4 + f32(idx & 15u) * 0.02; 1271 let b: f32 = 0.5 + f32(idx & 7u) * 0.001; 1272 var x0: f32 = f32(idx & 255u) * 0.0001 + 0.01; 1273 var x1: f32 = f32(idx & 255u) * 0.0001 + 0.02; 1274 var x2: f32 = f32(idx & 255u) * 0.0001 + 0.03; 1275 var x3: f32 = f32(idx & 255u) * 0.0001 + 0.04; 1276 var x4: f32 = f32(idx & 255u) * 0.0001 + 0.05; 1277 var x5: f32 = f32(idx & 255u) * 0.0001 + 0.06; 1278 var x6: f32 = f32(idx & 255u) * 0.0001 + 0.07; 1279 var x7: f32 = f32(idx & 255u) * 0.0001 + 0.08; 1280 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 1281 x0 = pow(x0, e) + b; 1282 x1 = pow(x1, e) + b; 1283 x2 = pow(x2, e) + b; 1284 x3 = pow(x3, e) + b; 1285 x4 = pow(x4, e) + b; 1286 x5 = pow(x5, e) + b; 1287 x6 = pow(x6, e) + b; 1288 x7 = pow(x7, e) + b; 1289 x0 = pow(x0, e) + b; 1290 x1 = pow(x1, e) + b; 1291 x2 = pow(x2, e) + b; 1292 x3 = pow(x3, e) + b; 1293 x4 = pow(x4, e) + b; 1294 x5 = pow(x5, e) + b; 1295 x6 = pow(x6, e) + b; 1296 x7 = pow(x7, e) + b; 1297 x0 = pow(x0, e) + b; 1298 x1 = pow(x1, e) + b; 1299 x2 = pow(x2, e) + b; 1300 x3 = pow(x3, e) + b; 1301 x4 = pow(x4, e) + b; 1302 x5 = pow(x5, e) + b; 1303 x6 = pow(x6, e) + b; 1304 x7 = pow(x7, e) + b; 1305 x0 = pow(x0, e) + b; 1306 x1 = pow(x1, e) + b; 1307 x2 = pow(x2, e) + b; 1308 x3 = pow(x3, e) + b; 1309 x4 = pow(x4, e) + b; 1310 x5 = pow(x5, e) + b; 1311 x6 = pow(x6, e) + b; 1312 x7 = pow(x7, e) + b; 1313 } 1314 out[idx] = x0 + x1 + x2 + x3 + x4 + x5 + x6 + x7; 1315} 1316`,wC=` 1317struct Params { 1318 threads: u32, 1319 iterations: u32, 1320}; 1321 1322@group(0) @binding(0) var<uniform> params: Params; 1323@group(0) @binding(1) var<storage, read_write> out: array<f32>; 1324 1325@compute @workgroup_size(64) 1326fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 1327 let idx = gid.x; 1328 if (idx >= params.threads) { 1329 return; 1330 } 1331 var x0: f32 = f32(idx & 255u) * 0.01 + 0.1; 1332 var x1: f32 = f32(idx & 255u) * 0.01 + 0.2; 1333 var x2: f32 = f32(idx & 255u) * 0.01 + 0.3; 1334 var x3: f32 = f32(idx & 255u) * 0.01 + 0.4; 1335 var x4: f32 = f32(idx & 255u) * 0.01 + 0.5; 1336 var x5: f32 = f32(idx & 255u) * 0.01 + 0.6; 1337 var x6: f32 = f32(idx & 255u) * 0.01 + 0.7; 1338 var x7: f32 = f32(idx & 255u) * 0.01 + 0.8; 1339 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 1340 x0 = cos(sin(x0)); 1341 x1 = cos(sin(x1)); 1342 x2 = cos(sin(x2)); 1343 x3 = cos(sin(x3)); 1344 x4 = cos(sin(x4)); 1345 x5 = cos(sin(x5)); 1346 x6 = cos(sin(x6)); 1347 x7 = cos(sin(x7)); 1348 x0 = cos(sin(x0)); 1349 x1 = cos(sin(x1)); 1350 x2 = cos(sin(x2)); 1351 x3 = cos(sin(x3)); 1352 x4 = cos(sin(x4)); 1353 x5 = cos(sin(x5)); 1354 x6 = cos(sin(x6)); 1355 x7 = cos(sin(x7)); 1356 x0 = cos(sin(x0)); 1357 x1 = cos(sin(x1)); 1358 x2 = cos(sin(x2)); 1359 x3 = cos(sin(x3)); 1360 x4 = cos(sin(x4)); 1361 x5 = cos(sin(x5)); 1362 x6 = cos(sin(x6)); 1363 x7 = cos(sin(x7)); 1364 x0 = cos(sin(x0)); 1365 x1 = cos(sin(x1)); 1366 x2 = cos(sin(x2)); 1367 x3 = cos(sin(x3)); 1368 x4 = cos(sin(x4)); 1369 x5 = cos(sin(x5)); 1370 x6 = cos(sin(x6)); 1371 x7 = cos(sin(x7)); 1372 } 1373 out[idx] = x0 + x1 + x2 + x3 + x4 + x5 + x6 + x7; 1374} 1375`,TC=` 1376struct Params { 1377 threads: u32, 1378 iterations: u32, 1379}; 1380 1381@group(0) @binding(0) var<uniform> params: Params; 1382@group(0) @binding(1) var<storage, read_write> out: array<f32>; 1383 1384@compute @workgroup_size(64) 1385fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 1386 let idx = gid.x; 1387 if (idx >= params.threads) { 1388 return; 1389 } 1390 let b: f32 = 10.0 + f32(idx & 7u); 1391 var x0: f32 = 10.0 + f32(idx & 255u) * 0.01; 1392 var x1: f32 = 11.0 + f32(idx & 255u) * 0.01; 1393 var x2: f32 = 12.0 + f32(idx & 255u) * 0.01; 1394 var x3: f32 = 13.0 + f32(idx & 255u) * 0.01; 1395 var x4: f32 = 14.0 + f32(idx & 255u) * 0.01; 1396 var x5: f32 = 15.0 + f32(idx & 255u) * 0.01; 1397 var x6: f32 = 16.0 + f32(idx & 255u) * 0.01; 1398 var x7: f32 = 17.0 + f32(idx & 255u) * 0.01; 1399 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 1400 x0 = log(x0) + b; 1401 x1 = log(x1) + b; 1402 x2 = log(x2) + b; 1403 x3 = log(x3) + b; 1404 x4 = log(x4) + b; 1405 x5 = log(x5) + b; 1406 x6 = log(x6) + b; 1407 x7 = log(x7) + b; 1408 x0 = log(x0) + b; 1409 x1 = log(x1) + b; 1410 x2 = log(x2) + b; 1411 x3 = log(x3) + b; 1412 x4 = log(x4) + b; 1413 x5 = log(x5) + b; 1414 x6 = log(x6) + b; 1415 x7 = log(x7) + b; 1416 x0 = log(x0) + b; 1417 x1 = log(x1) + b; 1418 x2 = log(x2) + b; 1419 x3 = log(x3) + b; 1420 x4 = log(x4) + b; 1421 x5 = log(x5) + b; 1422 x6 = log(x6) + b; 1423 x7 = log(x7) + b; 1424 x0 = log(x0) + b; 1425 x1 = log(x1) + b; 1426 x2 = log(x2) + b; 1427 x3 = log(x3) + b; 1428 x4 = log(x4) + b; 1429 x5 = log(x5) + b; 1430 x6 = log(x6) + b; 1431 x7 = log(x7) + b; 1432 } 1433 out[idx] = x0 + x1 + x2 + x3 + x4 + x5 + x6 + x7; 1434} 1435`,EC=` 1436enable f16; 1437 1438struct Params { 1439 threads: u32, 1440 iterations: u32, 1441}; 1442 1443@group(0) @binding(0) var<uniform> params: Params; 1444@group(0) @binding(1) var<storage, read_write> out: array<f32>; 1445 1446@compute @workgroup_size(64) 1447fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 1448 let idx = gid.x; 1449 if (idx >= params.threads) { 1450 return; 1451 } 1452 let a: f16 = f16(1.2) + f16(idx & 15u) * f16(0.05); 1453 let b: f16 = f16(0.5) + f16(idx & 7u) * f16(0.001); 1454 var x0: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.01); 1455 var x1: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.02); 1456 var x2: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.03); 1457 var x3: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.04); 1458 var x4: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.05); 1459 var x5: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.06); 1460 var x6: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.07); 1461 var x7: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.08); 1462 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 1463 x0 = a / x0 + b; 1464 x1 = a / x1 + b; 1465 x2 = a / x2 + b; 1466 x3 = a / x3 + b; 1467 x4 = a / x4 + b; 1468 x5 = a / x5 + b; 1469 x6 = a / x6 + b; 1470 x7 = a / x7 + b; 1471 x0 = a / x0 + b; 1472 x1 = a / x1 + b; 1473 x2 = a / x2 + b; 1474 x3 = a / x3 + b; 1475 x4 = a / x4 + b; 1476 x5 = a / x5 + b; 1477 x6 = a / x6 + b; 1478 x7 = a / x7 + b; 1479 x0 = a / x0 + b; 1480 x1 = a / x1 + b; 1481 x2 = a / x2 + b; 1482 x3 = a / x3 + b; 1483 x4 = a / x4 + b; 1484 x5 = a / x5 + b; 1485 x6 = a / x6 + b; 1486 x7 = a / x7 + b; 1487 x0 = a / x0 + b; 1488 x1 = a / x1 + b; 1489 x2 = a / x2 + b; 1490 x3 = a / x3 + b; 1491 x4 = a / x4 + b; 1492 x5 = a / x5 + b; 1493 x6 = a / x6 + b; 1494 x7 = a / x7 + b; 1495 } 1496 out[idx] = f32(x0 + x1 + x2 + x3 + x4 + x5 + x6 + x7); 1497} 1498`,DC=` 1499enable f16; 1500 1501struct Params { 1502 threads: u32, 1503 iterations: u32, 1504}; 1505 1506@group(0) @binding(0) var<uniform> params: Params; 1507@group(0) @binding(1) var<storage, read_write> out: array<f32>; 1508 1509@compute @workgroup_size(64) 1510fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 1511 let idx = gid.x; 1512 if (idx >= params.threads) { 1513 return; 1514 } 1515 let b: f16 = f16(0.5) + f16(idx & 7u) * f16(0.001); 1516 var x0: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.01); 1517 var x1: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.02); 1518 var x2: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.03); 1519 var x3: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.04); 1520 var x4: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.05); 1521 var x5: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.06); 1522 var x6: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.07); 1523 var x7: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.08); 1524 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 1525 x0 = sqrt(x0) + b; 1526 x1 = sqrt(x1) + b; 1527 x2 = sqrt(x2) + b; 1528 x3 = sqrt(x3) + b; 1529 x4 = sqrt(x4) + b; 1530 x5 = sqrt(x5) + b; 1531 x6 = sqrt(x6) + b; 1532 x7 = sqrt(x7) + b; 1533 x0 = sqrt(x0) + b; 1534 x1 = sqrt(x1) + b; 1535 x2 = sqrt(x2) + b; 1536 x3 = sqrt(x3) + b; 1537 x4 = sqrt(x4) + b; 1538 x5 = sqrt(x5) + b; 1539 x6 = sqrt(x6) + b; 1540 x7 = sqrt(x7) + b; 1541 x0 = sqrt(x0) + b; 1542 x1 = sqrt(x1) + b; 1543 x2 = sqrt(x2) + b; 1544 x3 = sqrt(x3) + b; 1545 x4 = sqrt(x4) + b; 1546 x5 = sqrt(x5) + b; 1547 x6 = sqrt(x6) + b; 1548 x7 = sqrt(x7) + b; 1549 x0 = sqrt(x0) + b; 1550 x1 = sqrt(x1) + b; 1551 x2 = sqrt(x2) + b; 1552 x3 = sqrt(x3) + b; 1553 x4 = sqrt(x4) + b; 1554 x5 = sqrt(x5) + b; 1555 x6
1555 = sqrt(x6) + b; 1556 x7 = sqrt(x7) + b; 1557 } 1558 out[idx] = f32(x0 + x1 + x2 + x3 + x4 + x5 + x6 + x7); 1559} 1560`,OC=` 1561enable f16; 1562 1563struct Params { 1564 threads: u32, 1565 iterations: u32, 1566}; 1567 1568@group(0) @binding(0) var<uniform> params: Params; 1569@group(0) @binding(1) var<storage, read_write> out: array<f32>; 1570 1571@compute @workgroup_size(64) 1572fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 1573 let idx = gid.x; 1574 if (idx >= params.threads) { 1575 return; 1576 } 1577 let b: f16 = f16(0.5) + f16(idx & 7u) * f16(0.001); 1578 var x0: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.01); 1579 var x1: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.02); 1580 var x2: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.03); 1581 var x3: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.04); 1582 var x4: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.05); 1583 var x5: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.06); 1584 var x6: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.07); 1585 var x7: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.08); 1586 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 1587 x0 = inverseSqrt(x0) + b; 1588 x1 = inverseSqrt(x1) + b; 1589 x2 = inverseSqrt(x2) + b; 1590 x3 = inverseSqrt(x3) + b; 1591 x4 = inverseSqrt(x4) + b; 1592 x5 = inverseSqrt(x5) + b; 1593 x6 = inverseSqrt(x6) + b; 1594 x7 = inverseSqrt(x7) + b; 1595 x0 = inverseSqrt(x0) + b; 1596 x1 = inverseSqrt(x1) + b; 1597 x2 = inverseSqrt(x2) + b; 1598 x3 = inverseSqrt(x3) + b; 1599 x4 = inverseSqrt(x4) + b; 1600 x5 = inverseSqrt(x5) + b; 1601 x6 = inverseSqrt(x6) + b; 1602 x7 = inverseSqrt(x7) + b; 1603 x0 = inverseSqrt(x0) + b; 1604 x1 = inverseSqrt(x1) + b; 1605 x2 = inverseSqrt(x2) + b; 1606 x3 = inverseSqrt(x3) + b; 1607 x4 = inverseSqrt(x4) + b; 1608 x5 = inverseSqrt(x5) + b; 1609 x6 = inverseSqrt(x6) + b; 1610 x7 = inverseSqrt(x7) + b; 1611 x0 = inverseSqrt(x0) + b; 1612 x1 = inverseSqrt(x1) + b; 1613 x2 = inverseSqrt(x2) + b; 1614 x3 = inverseSqrt(x3) + b; 1615 x4 = inverseSqrt(x4) + b; 1616 x5 = inverseSqrt(x5) + b; 1617 x6 = inverseSqrt(x6) + b; 1618 x7 = inverseSqrt(x7) + b; 1619 } 1620 out[idx] = f32(x0 + x1 + x2 + x3 + x4 + x5 + x6 + x7); 1621} 1622`,kC=` 1623enable f16; 1624 1625struct Params { 1626 threads: u32, 1627 iterations: u32, 1628}; 1629 1630@group(0) @binding(0) var<uniform> params: Params; 1631@group(0) @binding(1) var<storage, read_write> out: array<f32>; 1632 1633@compute @workgroup_size(64) 1634fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 1635 let idx = gid.x; 1636 if (idx >= params.threads) { 1637 return; 1638 } 1639 let e: f16 = f16(0.4) + f16(idx & 15u) * f16(0.02); 1640 let b: f16 = f16(0.5) + f16(idx & 7u) * f16(0.001); 1641 var x0: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.01); 1642 var x1: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.02); 1643 var x2: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.03); 1644 var x3: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.04); 1645 var x4: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.05); 1646 var x5: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.06); 1647 var x6: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.07); 1648 var x7: f16 = f16(idx & 255u) * f16(0.0001) + f16(0.08); 1649 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 1650 x0 = pow(x0, e) + b; 1651 x1 = pow(x1, e) + b; 1652 x2 = pow(x2, e) + b; 1653 x3 = pow(x3, e) + b; 1654 x4 = pow(x4, e) + b; 1655 x5 = pow(x5, e) + b; 1656 x6 = pow(x6, e) + b; 1657 x7 = pow(x7, e) + b; 1658 x0 = pow(x0, e) + b; 1659 x1 = pow(x1, e) + b; 1660 x2 = pow(x2, e) + b; 1661 x3 = pow(x3, e) + b; 1662 x4 = pow(x4, e) + b; 1663 x5 = pow(x5, e) + b; 1664 x6 = pow(x6, e) + b; 1665 x7 = pow(x7, e) + b; 1666 x0 = pow(x0, e) + b; 1667 x1 = pow(x1, e) + b; 1668 x2 = pow(x2, e) + b; 1669 x3 = pow(x3, e) + b; 1670 x4 = pow(x4, e) + b; 1671 x5 = pow(x5, e) + b; 1672 x6 = pow(x6, e) + b; 1673 x7 = pow(x7, e) + b; 1674 x0 = pow(x0, e) + b; 1675 x1 = pow(x1, e) + b; 1676 x2 = pow(x2, e) + b; 1677 x3 = pow(x3, e) + b; 1678 x4 = pow(x4, e) + b; 1679 x5 = pow(x5, e) + b; 1680 x6 = pow(x6, e) + b; 1681 x7 = pow(x7, e) + b; 1682 } 1683 out[idx] = f32(x0 + x1 + x2 + x3 + x4 + x5 + x6 + x7); 1684} 1685`,AC=` 1686enable f16; 1687 1688struct Params { 1689 threads: u32, 1690 iterations: u32, 1691}; 1692 1693@group(0) @binding(0) var<uniform> params: Params; 1694@group(0) @binding(1) var<storage, read_write> out: array<f32>; 1695 1696@compute @workgroup_size(64) 1697fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 1698 let idx = gid.x; 1699 if (idx >= params.threads) { 1700 return; 1701 } 1702 var x0: f16 = f16(idx & 255u) * f16(0.01) + f16(0.1); 1703 var x1: f16 = f16(idx & 255u) * f16(0.01) + f16(0.2); 1704 var x2: f16 = f16(idx & 255u) * f16(0.01) + f16(0.3); 1705 var x3: f16 = f16(idx & 255u) * f16(0.01) + f16(0.4); 1706 var x4: f16 = f16(idx & 255u) * f16(0.01) + f16(0.5); 1707 var x5: f16 = f16(idx & 255u) * f16(0.01) + f16(0.6); 1708 var x6: f16 = f16(idx & 255u) * f16(0.01) + f16(0.7); 1709 var x7: f16 = f16(idx & 255u) * f16(0.01) + f16(0.8); 1710 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 1711 x0 = cos(sin(x0)); 1712 x1 = cos(sin(x1)); 1713 x2 = cos(sin(x2)); 1714 x3 = cos(sin(x3)); 1715 x4 = cos(sin(x4)); 1716 x5 = cos(sin(x5)); 1717 x6 = cos(sin(x6)); 1718 x7 = cos(sin(x7)); 1719 x0 = cos(sin(x0)); 1720 x1 = cos(sin(x1)); 1721 x2 = cos(sin(x2)); 1722 x3 = cos(sin(x3)); 1723 x4 = cos(sin(x4)); 1724 x5 = cos(sin(x5)); 1725 x6 = cos(sin(x6)); 1726 x7 = cos(sin(x7)); 1727 x0 = cos(sin(x0)); 1728 x1 = cos(sin(x1)); 1729 x2 = cos(sin(x2)); 1730 x3 = cos(sin(x3)); 1731 x4 = cos(sin(x4)); 1732 x5 = cos(sin(x5)); 1733 x6 = cos(sin(x6)); 1734 x7 = cos(sin(x7)); 1735 x0 = cos(sin(x0)); 1736 x1 = cos(sin(x1)); 1737 x2 = cos(sin(x2)); 1738 x3 = cos(sin(x3)); 1739 x4 = cos(sin(x4)); 1740 x5 = cos(sin(x5)); 1741 x6 = cos(sin(x6)); 1742 x7 = cos(sin(x7)); 1743 } 1744 out[idx] = f32(x0 + x1 + x2 + x3 + x4 + x5 + x6 + x7); 1745} 1746`,jC=` 1747enable f16; 1748 1749struct Params { 1750 threads: u32, 1751 iterations: u32, 1752}; 1753 1754@group(0) @binding(0) var<uniform> params: Params; 1755@group(0) @binding(1) var<storage, read_write> out: array<f32>; 1756 1757@compute @workgroup_size(64) 1758fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 1759 let idx = gid.x; 1760 if (idx >= params.threads) { 1761 return; 1762 } 1763 let b: f16 = f16(10.0) + f16(idx & 7u); 1764 var x0: f16 = f16(10.0) + f16(idx & 255u) * f16(0.01); 1765 var x1: f16 = f16(11.0) + f16(idx & 255u) * f16(0.01); 1766 var x2: f16 = f16(12.0) + f16(idx & 255u) * f16(0.01); 1767 var x3: f16 = f16(13.0) + f16(idx & 255u) * f16(0.01); 1768 var x4: f16 = f16(14.0) + f16(idx & 255u) * f16(0.01); 1769 var x5: f16 = f16(15.0) + f16(idx & 255u) * f16(0.01); 1770 var x6: f16 = f16(16.0) + f16(idx & 255u) * f16(0.01); 1771 var x7: f16 = f16(17.0) + f16(idx & 255u) * f16(0.01); 1772 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 1773 x0 = log(x0) + b; 1774 x1 = log(x1) + b; 1775 x2 = log(x2) + b; 1776 x3 = log(x3) + b; 1777 x4 = log(x4) + b; 1778 x5 = log(x5) + b; 1779 x6 = log(x6) + b; 1780 x7 = log(x7) + b; 1781 x0 = log(x0) + b; 1782 x1 = log(x1) + b; 1783 x2 = log(x2) + b; 1784 x3 = log(x3) + b; 1785 x4 = log(x4) + b; 1786 x5 = log(x5) + b; 1787 x6 = log(x6) + b; 1788 x7 = log(x7) + b; 1789 x0 = log(x0) + b; 1790 x1 = log(x1) + b; 1791 x2 = log(x2) + b; 1792 x3 = log(x3) + b; 1793 x4 = log(x4) + b; 1794 x5 = log(x5) + b; 1795 x6 = log(x6) + b; 1796 x7 = log(x7) + b; 1797 x0 = log(x0) + b; 1798 x1 = log(x1) + b; 1799 x2 = log(x2) + b; 1800 x3 = log(x3) + b; 1801 x4 = log(x4) + b; 1802 x5 = log(x5) + b; 1803 x6 = log(x6) + b; 1804 x7 = log(x7) + b; 1805 } 1806 out[idx] = f32(x0 + x1 + x2 + x3 + x4 + x5 + x6 + x7); 1807} 1808`;function MC(e,t={}){return JS(e,{id:`f32-div`,wgsl:yC,flopsPerIteration:64,defaultIterations:256},t)}function NC(e,t={}){return JS(e,{id:`i32-div`,wgsl:bC,flopsPerIteration:64,defaultIterations:256},t)}function PC(e,t={}){return JS(e,{id:`f32-sqrt`,wgsl:xC,flopsPerIteration:64,defaultIterations:256},t)}function FC(e,t={}){return JS(e,{id:`f32-rsqrt`,wgsl:SC,flopsPerIteration:64,defaultIterations:256},t)}function IC(e,t={}){return JS(e,{id:`f32-pow`,wgsl:CC,flopsPerIteration:64,defaultIterations:128},t)}function LC(e,t={}){return JS(e,{id:`f32-sincos`,wgsl:wC,flopsPerIteration:64,defaultIterations:128},t)}function RC(e,t={}){return JS(e,{id:`f32-log`,wgsl:TC,flopsPerIteration:64,defaultIterations:256},t)}function zC(e,t={}){return JS(e,{id:`f16-div`,wgsl:EC,flopsPerIteration:64,defaultIterations:256,requiresF16:!0},t)}function BC(e,t={}){return JS(e,{id:`f16-sqrt`,wgsl:DC,flopsPerIteration:64,defaultIterations:256,requiresF16:!0},t)}function VC(e,t={}){return JS(e,{id:`f16-rsqrt`,wgsl:OC,flopsPerIteration:64,defaultIterations:256,requiresF16:!0},t)}function HC(e,t={}){return JS(e,{id:`f16-pow`,wgsl:kC,flopsPerIteration:64,defaultIterations:128,requiresF16:!0},t)}function UC(e,t={}){return JS(e,{id:`f16-sincos`,wgsl:AC,flopsPerIteration:64,defaultIterations:128,requiresF16:!0},t)}function WC(e,t={}){return JS(e,{id:`f16-log`,wgsl:jC,flopsPerIteration:64,defaultIterations:256,requiresF16:!0},t)}var GC=` 1809struct Params { 1810 threads: u32, 1811 iterations: u32, 1812}; 1813 1814@group(0) @binding(0) var<uniform> params: Params; 1815@group(0) @binding(1) var<storage, read_write> out: array<f32>; 1816 1817// Unpack 4 bytes, add 1 to each (wrapping), repack. 1818fn step(v: u32) -> u32 { 1819 let b0 = (v & 0xFFu) + 1u; 1820 let b1 = ((v >> 8u) & 0xFFu) + 1u; 1821 let b2 = ((v >> 16u) & 0xFFu) + 1u; 1822 let b3 = (v >> 24u) + 1u; 1823 return (b0 & 0xFFu) | ((b1 & 0xFFu) << 8u) | ((b2 & 0xFFu) << 16u) | (b3 << 24u); 1824} 1825 1826@compute @workgroup_size(64) 1827fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 1828 let idx = gid.x; 1829 if (idx >= params.threads) { 1830 return; 1831 } 1832 var v0: u32 = (idx + 0u) * 2654435761u; 1833 var v1: u32 = (idx + 1u) * 2654435761u; 1834 var v2: u32 = (idx + 2u) * 2654435761u; 1835 var v3: u32 = (idx + 3u) * 2654435761u; 1836 var v4: u32 = (idx + 4u) * 2654435761u; 1837 var v5: u32 = (idx + 5u) * 2654435761u; 1838 var v6: u32 = (idx + 6u) * 2654435761u; 1839 var v7: u32 = (idx + 7u) * 2654435761u; 1840 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 1841 v0 = step(v0); 1842 v1 = step(v1); 1843 v2 = step(v2); 1844 v3 = step(v3); 1845 v4 = step(v4); 1846 v5 = step(v5); 1847 v6 = step(v6); 1848 v7 = step(v7); 1849 v0 = step(v0); 1850 v1 = step(v1); 1851 v2 = step(v2); 1852 v3 = step(v3); 1853 v4 = step(v4); 1854 v5 = step(v5); 1855 v6 = step(v6); 1856 v7 = step(v7); 1857 v0 = step(v0); 1858 v1 = step(v1); 1859 v2 = step(v2); 1860 v3 = step(v3); 1861 v4 = step(v4); 1862 v5 = step(v5); 1863 v6 = step(v6); 1864 v7 = step(v7); 1865 v0 = step(v0); 1866 v1 = step(v1); 1867 v2 = step(v2); 1868 v3 = step(v3); 1869 v4 = step(v4); 1870 v5 = step(v5); 1871 v6 = step(v6); 1872 v7 = step(v7); 1873 } 1874 out[idx] = f32(v0 ^ v1 ^ v2 ^ v3 ^ v4 ^ v5 ^ v6 ^ v7); 1875} 1876`,KC=` 1877struct Params { 1878 threads: u32, 1879 iterations: u32, 1880}; 1881 1882@group(0) @binding(0) var<uniform> params: Params; 1883@group(0) @binding(1) var<storage, read_write> out: array<f32>; 1884 1885@compute @workgroup_size(64) 1886fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 1887 let idx = gid.x; 1888 if (idx >= params.threads) { 1889 return; 1890 } 1891 let a: f32 = 0.9 + f32(idx & 15u) * 0.005; 1892 let b: f32 = 3.0 + f32(idx & 7u) * 0.1; 1893 var x0: i32 = i32(idx & 255u) + 100; 1894 var x1: i32 = i32(idx & 255u) + 200; 1895 var x2: i32 = i32(idx & 255u) + 300; 1896 var x3: i32 = i32(idx & 255u) + 400; 1897 var x4: i32 = i32(idx & 255u) + 500; 1898 var x5: i32 = i32(idx & 255u) + 600; 1899 var x6: i32 = i32(idx & 255u) + 700; 1900 var x7: i32 = i32(idx & 255u) + 800; 1901 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 1902 x0 = i32(f32(x0) * a + b); 1903 x1 = i32(f32(x1) * a + b); 1904 x2 = i32(f32(x2) * a + b); 1905 x3 = i32(f32(x3) * a + b); 1906 x4 = i32(f32(x4) * a + b); 1907 x5 = i32(f32(x5) * a + b); 1908 x6 = i32(f32(x6) * a + b); 1909 x7 = i32(f32(x7) * a + b); 1910 x0 = i32(f32(x0) * a + b); 1911 x1 = i32(f32(x1) * a + b); 1912 x2 = i32(f32(x2) * a + b); 1913 x3 = i32(f32(x3) * a + b); 1914 x4 = i32(f32(x4) * a + b); 1915 x5 = i32(f32(x5) * a + b); 1916 x6 = i32(f32(x6) * a + b); 1917 x7 = i32(f32(x7) * a + b); 1918 x0 = i32(f32(x0) * a + b); 1919 x1 = i32(f32(x1) * a + b); 1920 x2 = i32(f32(x2) * a + b); 1921 x3 = i32(f32(x3) * a + b); 1922 x4 = i32(f32(x4) * a + b); 1923 x5 = i32(f32(x5) * a + b); 1924 x6 = i32(f32(x6) * a + b); 1925 x7 = i32(f32(x7) * a + b); 1926 x0 = i32(f32(x0) * a + b); 1927 x1 = i32(f32(x1) * a + b); 1928 x2 = i32(f32(x2) * a + b); 1929 x3 = i32(f32(x3) * a + b); 1930 x4 = i32(f32(x4) * a + b); 1931 x5 = i32(f32(x5) * a + b); 1932 x6 = i32(f32(x6) * a + b); 1933 x7 = i32(f32(x7) * a + b); 1934 } 1935 out[idx] = f32(x0 + x1 + x2 + x3 + x4 + x5 + x6 + x7); 1936} 1937`,qC=` 1938struct Params { 1939 threads: u32, 1940 iterations: u32, 1941}; 1942 1943@group(0) @binding(0) var<uniform> params: Params; 1944@group(0) @binding(1) var<storage, read_write> out: array<f32>; 1945 1946@compute @workgroup_size(64) 1947fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 1948 let idx = gid.x; 1949 if (idx >= params.threads) { 1950 return; 1951 } 1952 let a: vec2<f32> = vec2<f32>(0.97 + f32(idx & 15u) * 0.001); 1953 let b: vec2<f32> = vec2<f32>(0.5 + f32(idx & 7u) * 0.001); 1954 var x0: vec2<f32> = vec2<f32>(f32(idx & 255u) * 0.0001 + 0.01); 1955 var x1: vec2<f32> = vec2<f32>(f32(idx & 255u) * 0.0001 + 0.02); 1956 var x2: vec2<f32> = vec2<f32>(f32(idx & 255u) * 0.0001 + 0.03); 1957 var x3: vec2<f32> = vec2<f32>(f32(idx & 255u) * 0.0001 + 0.04); 1958 var x4: vec2<f32> = vec2<f32>(f32(idx & 255u) * 0.0001 + 0.05); 1959 var x5: vec2<f32> = vec2<f32>(f32(idx & 255u) * 0.0001 + 0.06); 1960 var x6: vec2<f32> = vec2<f32>(f32(idx & 255u) * 0.0001 + 0.07); 1961 var x7: vec2<f32> = vec2<f32>(f32(idx & 255u) * 0.0001 + 0.08); 1962 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 1963 x0 = unpack2x16float(pack2x16float(x0)) * a + b; 1964 x1 = unpack2x16float(pack2x16float(x1)) * a + b; 1965 x2 = unpack2x16float(pack2x16float(x2)) * a + b; 1966 x3 = unpack2x16float(pack2x16float(x3)) * a + b; 1967 x4 = unpack2x16float(pack2x16float(x4)) * a + b; 1968 x5 = unpack2x16float(pack2x16float(x5)) * a + b; 1969 x6 = unpack2x16float(pack2x16float(x6)) * a + b; 1970 x7 = unpack2x16float(pack2x16float(x7)) * a + b; 1971 x0 = unpack2x16float(pack2x16float(x0)) * a + b; 1972 x1 = unpack2x16float(pack2x16float(x1)) * a + b; 1973 x2 = unpack2x16float(pack2x16float(x2)) * a + b; 1974 x3 = unpack2x16float(pack2x16float(x3)) * a + b; 1975 x4 = unpack2x16float(pack2x16float(x4)) * a + b; 1976 x5 = unpack2x16float(pack2x16float(x5)) * a + b; 1977 x6 = unpack2x16float(pack2x16float(x6)) * a + b; 1978 x7 = unpack2x16float(pack2x16float(x7)) * a + b; 1979 x0 = unpack2x16float(pack2x16float(x0)) * a + b; 1980 x1 = unpack2x16float(pack2x16float(x1)) * a + b; 1981 x2 = unpack2x16float(pack2x16float(x2)) * a + b; 1982 x3 = unpack2x16float(pack2x16float(x3)) * a + b; 1983 x4 = unpack2x16float(pack2x16float(x4)) * a + b; 1984 x5 = unpack2x16float(pack2x16float(x5)) * a + b; 1985 x6 = unpack2x16float(pack2x16float(x6)) * a + b; 1986 x7 = unpack2x16float(pack2x16float(x7)) * a + b; 1987 x0 = unpack2x16float(pack2x16float(x0)) * a + b; 1988 x1 = unpack2x16float(pack2x16float(x1)) * a + b; 1989 x2 = unpack2x16float(pack2x16float(x2)) * a + b; 1990 x3 = unpack2x16float(pack2x16float(x3)) * a + b; 1991 x4 = unpack2x16float(pack2x16float(x4)) * a + b; 1992 x5 = unpack2x16float(pack2x16float(x5)) * a + b; 1993 x6 = unpack2x16float(pack2x16float(x6)) * a + b; 1994 x7 = unpack2x16float(pack2x16float(x7)) * a + b; 1995 } 1996 let s0 = x0 + x1 + x2 + x3 + x4 + x5 + x6 + x7; 1997 out[idx] = s0.x + s0.y; 1998} 1999`,JC=` 2000struct Params { 2001 threads: u32, 2002 iterations: u32, 2003}; 2004 2005@group(0) @binding(0) var<uniform> params: Params; 2006@group(0) @binding(1) var<storage, read_write> out: array<f32>; 2007 2008@compute @workgroup_size(64) 2009fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 2010 let idx = gid.x; 2011 if (idx >= params.threads) { 2012 return; 2013 } 2014 let k: u32 = (idx * 2654435761u) | 1u; 2015 var x0: u32 = k; 2016 var x1: u32 = k + 1u; 2017 var x2: u32 = k + 2u; 2018 var x3: u32 = k + 3u; 2019 var x4: u32 = k + 4u; 2020 var x5: u32 = k + 5u; 2021 var x6: u32 = k + 6u; 2022 var x7: u32 = k + 7u; 2023 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 2024 let s0 = i & 31u; 2025 let s1 = (i + 8u) & 31u; 2026 let s2 = (i + 16u) & 31u; 2027 let s3 = (i + 24u) & 31u; 2028 x0 = (x0 << s0) ^ k; 2029 x1 = (x1 >> s0) ^ k; 2030 x2 = (x2 << s0) ^ k; 2031 x3 = (x3 >> s0) ^ k; 2032 x4 = (x4 << s0) ^ k; 2033 x5 = (x5 >> s0) ^ k; 2034 x6 = (x6 << s0) ^ k; 2035 x7 = (x7 >> s0) ^ k; 2036 x0 = (x0 << s1) ^ k; 2037 x1 = (x1 >> s1) ^ k; 2038 x2 = (x2 << s1) ^ k; 2039 x3 = (x3 >> s1) ^ k; 2040 x4 = (x4 << s1) ^ k; 2041 x5 = (x5 >> s1) ^ k; 2042 x6 = (x6 << s1) ^ k; 2043 x7 = (x7 >> s1) ^ k; 2044 x0 = (x0 << s2) ^ k; 2045 x1 = (x1 >> s2) ^ k; 2046 x2 = (x2 << s2) ^ k; 2047 x3 = (x3 >> s2) ^ k; 2048 x4 = (x4 << s2) ^ k; 2049 x5 = (x5 >> s2) ^ k; 2050 x6 = (x6 << s2) ^ k; 2051 x7 = (x7 >> s2) ^ k; 2052 x0 = (x0 << s3) ^ k; 2053 x1 = (x1 >> s3) ^ k; 2054
2054 x2 = (x2 << s3) ^ k; 2055 x3 = (x3 >> s3) ^ k; 2056 x4 = (x4 << s3) ^ k; 2057 x5 = (x5 >> s3) ^ k; 2058 x6 = (x6 << s3) ^ k; 2059 x7 = (x7 >> s3) ^ k; 2060 } 2061 out[idx] = f32(x0 ^ x1 ^ x2 ^ x3 ^ x4 ^ x5 ^ x6 ^ x7); 2062} 2063`;function YC(e){let t=[0,1,2,3,4,5,6,7],n=t.map(t=>` var x${t}: ${e.type} = ${e.init(t)};`).join(` 2064`),r=t.map(t=>` x${t} = ${e.step(`x${t}`)};`).join(` 2065`),i=e.type===`f32`?t.map(e=>`x${e}`).join(` + `):`f32(${t.map(e=>`x${e}`).join(` ^ `)})`;return` 2066struct Params { 2067 threads: u32, 2068 iterations: u32, 2069}; 2070 2071@group(0) @binding(0) var<uniform> params: Params; 2072@group(0) @binding(1) var<storage, read_write> out: array<f32>; 2073 2074@compute @workgroup_size(64) 2075fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 2076 let idx = gid.x; 2077 if (idx >= params.threads) { 2078 return; 2079 } 2080${e.consts} 2081${n} 2082 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 2083${r} 2084${r} 2085${r} 2086${r} 2087 } 2088 out[idx] = ${i}; 2089} 2090`}var XC=` let a: f32 = 1.0 - f32(idx & 15u) * 0.001; 2091 let b: f32 = 0.5 + f32(idx & 7u) * 0.001;`,ZC=e=>`f32(idx & 255u) * 0.0001 + 0.0${e+1}`,QC=` let k: u32 = (idx * 2654435761u) | 1u;`,$C=e=>`k + ${e}u`,ew=YC({type:`f32`,consts:XC,init:ZC,step:e=>`fma(${e}, a, b)`}),tw=YC({type:`f32`,consts:XC,init:ZC,step:e=>`select(${e} + b, ${e} - a, ${e} > 1.0)`}),nw=YC({type:`f32`,consts:XC,init:ZC,step:e=>`clamp(${e} * a + b, 0.0, 1.0)`}),rw=YC({type:`f32`,consts:XC,init:ZC,step:e=>`max(min(${e} * a + b, 1.0), 0.0)`}),iw=YC({type:`u32`,consts:QC,init:$C,step:e=>`countOneBits(${e}) ^ k`}),aw=YC({type:`u32`,consts:QC,init:$C,step:e=>`firstLeadingBit(${e}) ^ k`}),ow=YC({type:`u32`,consts:QC,init:$C,step:e=>`reverseBits(${e}) ^ k`}),sw=(e,t)=>[`x0`,`x1`,`x2`,`x3`,`x4`,`x5`,`x6`,`x7`].map(n=>` ${n} = ${n} * ${e} + ${t};`).join(` 2092`);function cw(e){return` 2093struct Params { 2094 threads: u32, 2095 iterations: u32, 2096}; 2097 2098@group(0) @binding(0) var<uniform> params: Params; 2099@group(0) @binding(1) var<storage, read_write> out: array<f32>; 2100 2101@compute @workgroup_size(64) 2102fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 2103 let idx = gid.x; 2104 if (idx >= params.threads) { 2105 return; 2106 } 2107 let a: f32 = 1.0 - f32(idx & 15u) * 0.001; 2108 let b: f32 = 0.5 + f32(idx & 7u) * 0.001; 2109 let c: f32 = 1.0 - f32(idx & 31u) * 0.0005; 2110 let d: f32 = 0.25 + f32(idx & 3u) * 0.001; 2111 var x0: f32 = f32(idx & 255u) * 0.0001 + 0.01; 2112 var x1: f32 = f32(idx & 255u) * 0.0001 + 0.02; 2113 var x2: f32 = f32(idx & 255u) * 0.0001 + 0.03; 2114 var x3: f32 = f32(idx & 255u) * 0.0001 + 0.04; 2115 var x4: f32 = f32(idx & 255u) * 0.0001 + 0.05; 2116 var x5: f32 = f32(idx & 255u) * 0.0001 + 0.06; 2117 var x6: f32 = f32(idx & 255u) * 0.0001 + 0.07; 2118 var x7: f32 = f32(idx & 255u) * 0.0001 + 0.08; 2119 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 2120${[0,1,2,3].map(t=>e===null?sw(`a`,`b`):` if (${e.replaceAll(`STEP`,`(i + ${t}u)`)}) { 2121${sw(`a`,`b`)} 2122 } else { 2123${sw(`c`,`d`)} 2124 }`).join(` 2125`)} 2126 } 2127 out[idx] = x0 + x1 + x2 + x3 + x4 + x5 + x6 + x7; 2128} 2129`}var lw=cw(null),uw=cw(`(STEP & 1u) == 0u`),dw=cw(`((idx / 64u + STEP) & 1u) == 0u`),fw=cw(`((idx + STEP) & 1u) == 0u`),pw=` 2130requires packed_4x8_integer_dot_product; 2131 2132struct Params { 2133 threads: u32, 2134 iterations: u32, 2135}; 2136 2137@group(0) @binding(0) var<uniform> params: Params; 2138@group(0) @binding(1) var<storage, read_write> out: array<f32>; 2139 2140@compute @workgroup_size(64) 2141fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 2142 let idx = gid.x; 2143 if (idx >= params.threads) { 2144 return; 2145 } 2146 let b: u32 = 0x05060708u ^ (idx * 0x85ebca6bu); 2147 var a0: u32 = 0x01020300u ^ (idx * 0x9e3779b1u); 2148 var acc0: u32 = (idx & 255u) + 0u; 2149 var a1: u32 = 0x01020301u ^ (idx * 0x9e3779b1u); 2150 var acc1: u32 = (idx & 255u) + 1u; 2151 var a2: u32 = 0x01020302u ^ (idx * 0x9e3779b1u); 2152 var acc2: u32 = (idx & 255u) + 2u; 2153 var a3: u32 = 0x01020303u ^ (idx * 0x9e3779b1u); 2154 var acc3: u32 = (idx & 255u) + 3u; 2155 var a4: u32 = 0x01020304u ^ (idx * 0x9e3779b1u); 2156 var acc4: u32 = (idx & 255u) + 4u; 2157 var a5: u32 = 0x01020305u ^ (idx * 0x9e3779b1u); 2158 var acc5: u32 = (idx & 255u) + 5u; 2159 var a6: u32 = 0x01020306u ^ (idx * 0x9e3779b1u); 2160 var acc6: u32 = (idx & 255u) + 6u; 2161 var a7: u32 = 0x01020307u ^ (idx * 0x9e3779b1u); 2162 var acc7: u32 = (idx & 255u) + 7u; 2163 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 2164 acc0 = acc0 + dot4U8Packed(a0, b); 2165 a0 = a0 ^ acc0; 2166 acc1 = acc1 + dot4U8Packed(a1, b); 2167 a1 = a1 ^ acc1; 2168 acc2 = acc2 + dot4U8Packed(a2, b); 2169 a2 = a2 ^ acc2; 2170 acc3 = acc3 + dot4U8Packed(a3, b); 2171 a3 = a3 ^ acc3; 2172 acc4 = acc4 + dot4U8Packed(a4, b); 2173 a4 = a4 ^ acc4; 2174 acc5 = acc5 + dot4U8Packed(a5, b); 2175 a5 = a5 ^ acc5; 2176 acc6 = acc6 + dot4U8Packed(a6, b); 2177 a6 = a6 ^ acc6; 2178 acc7 = acc7 + dot4U8Packed(a7, b); 2179 a7 = a7 ^ acc7; 2180 } 2181 out[idx] = f32(acc0 + acc1 + acc2 + acc3 + acc4 + acc5 + acc6 + acc7); 2182} 2183`;function mw(e,t={}){return JS(e,{id:`u32-packunpack`,wgsl:GC,flopsPerIteration:64,defaultIterations:256},t)}function hw(e,t={}){return JS(e,{id:`i32-f32-convert`,wgsl:KC,flopsPerIteration:64,defaultIterations:256},t)}function gw(e,t={}){return JS(e,{id:`f32-f16-convert`,wgsl:qC,flopsPerIteration:128,defaultIterations:256},t)}function _w(e,t={}){return JS(e,{id:`u32-shift`,wgsl:JC,flopsPerIteration:32,defaultIterations:256},t)}var vw=` 2184struct Params { 2185 threads: u32, 2186 iterations: u32, 2187 texelCount: u32, 2188}; 2189 2190const STEP: f32 = 0.25; 2191 2192@group(0) @binding(0) var<uniform> params: Params; 2193@group(0) @binding(1) var tex: texture_2d<f32>; 2194@group(0) @binding(2) var samp: sampler; 2195@group(0) @binding(3) var<storage, read_write> out: array<f32>; 2196 2197@compute @workgroup_size(256) 2198fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 2199 let t = gid.x; 2200 if (t >= params.threads) { return; } 2201 let phase = f32(t) / f32(params.threads);
2202 let stepNorm = STEP / f32(params.texelCount); 2203 var sum: vec4<f32> = vec4<f32>(0.0, 0.0, 0.0, 0.0); 2204 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 2205 let u = fract(phase + f32(i) * stepNorm); 2206 sum = sum + textureSampleLevel(tex, samp, vec2<f32>(u, 0.5), 0.0); 2207 } 2208 out[t] = sum.x + sum.y + sum.z + sum.w; 2209} 2210`,yw=` 2211struct Params { 2212 threads: u32, 2213 iterations: u32, 2214 texelCount: u32, 2215}; 2216 2217const STEP: f32 = 0.25; 2218 2219@group(0) @binding(0) var<uniform> params: Params; 2220@group(0) @binding(1) var tex: texture_2d<f32>; 2221@group(0) @binding(2) var<storage, read_write> out: array<f32>; 2222 2223@compute @workgroup_size(256) 2224fn main(@builtin(global_invocation_id) gid: vec3<u32>) { 2225 let t = gid.x; 2226 if (t >= params.threads) { return; } 2227 let phase = f32(t) / f32(params.threads); 2228 let stepNorm = STEP / f32(params.texelCount); 2229 var sum: vec4<f32> = vec4<f32>(0.0, 0.0, 0.0, 0.0); 2230 for (var i: u32 = 0u; i < params.iterations; i = i + 1u) { 2231 let u = fract(phase + f32(i) * stepNorm); 2232 // Normalized filtering places texel centers at (i + 0.5) / width. 2233 let pos = u * f32(params.texelCount) - 0.5; 2234 let base = i32(floor(pos)); 2235 let width = i32(params.texelCount); 2236 let i0 = u32((base + width) % width); 2237 let i1 = (i0 + 1u) % params.texelCount; 2238 let frac = pos - floor(pos); 2239 let a = textureLoad(tex, vec2<u32>(i0, 0u), 0); 2240 let b = textureLoad(tex, vec2<u32>(i1, 0u), 0); 2241 sum = sum + mix(a, b, frac); 2242 } 2243 out[t] = sum.x + sum.y + sum.z + sum.w; 2244} 2245`;function bw(e,t,n,r){let i=e.createTexture({label:r,size:[n,1,1],format:`rgba32float`,usage:GPUTextureUsage.TEXTURE_BINDING|GPUTextureUsage.COPY_DST});return e.queue.writeTexture({texture:i},t,{bytesPerRow:n*16},{width:n,height:1}),i}var xw=4096,Sw=1024*1024,Cw=256,ww=16;function Tw(e,t=4242){let n=Tx(t),r=new Float32Array(e*4);for(let e=0;e<r.length;e++)r[e]=n()*2-1;return r}async function Ew(e,t,n={}){let r=n.threads??Sw,i=n.iterations??Cw,a=e=>({id:t.id,category:`bandwidth`,rows:r,cols:e,amountPerOp:r*e*2*16}),o=a(i);if(t.requiresFloat32Filterable&&!e.info.supportsFloat32Filterable)return{kind:`skipped`,result:iS(o,`Device/browser does not support the "float32-filterable" WebGPU feature.`)};let{device:s}=e,c=await tS(s,t.id,t.wgsl),l=lS(s,new Uint32Array([r,i,xw]),`params`),u=bw(s,Tw(xw),xw,`texel-data`),d=uS(s,r*4,`out`),f=[{binding:0,resource:{buffer:l}},{binding:1,resource:u.createView()}];if(t.useSampler){let e=s.createSampler({minFilter:`linear`,magFilter:`linear`,addressModeU:`repeat`});f.push({binding:2,resource:e},{binding:3,resource:{buffer:d}})}else f.push({binding:2,resource:{buffer:d}});let p=s.createBindGroup({layout:c.getBindGroupLayout(0),entries:f}),m=n.iterations===void 0?{min:Math.min(i,ww),max:i,apply:e=>s.queue.writeBuffer(l,0,new Uint32Array([r,e,xw]))}:void 0;return rS({...o,ctx:e,workgroupsPerIteration:[Math.ceil(r/256),1,1],pipeline:c,bindGroup:p,work:m,metaAtWork:a,targetMs:n.targetMs,targetDispatchMs:n.targetDispatchMs,warmups:n.warmups,maxIterations:n.maxIterations})}function Dw(e,t){return Ew(e,{id:`texture-interp-builtin`,wgsl:vw,useSampler:!0,requiresFloat32Filterable:!0},t)}function Ow(e,t){return Ew(e,{id:`texture-interp-manual`,wgsl:yw,useSampler:!1},t)}function kw(e){return({ctx:t,data:n,harness:r})=>e(t,n,r)}function Aw(e){return({ctx:t,harness:n,computeThreads:r,computeIterations:i})=>e(t,{...n,threads:r,iterations:i})}function jw(e,t,n,r,i,a,o=!1){return{id:e,label:t,description:n,source:r,category:`compute`,metric:i,prepare:({ctx:t,harness:n,computeThreads:i,computeIterations:s})=>JS(t,{id:e,wgsl:r,flopsPerIteration:a,defaultIterations:256,requiresI8Dot:o},{...n,threads:i,iterations:s})}}var Mw=1024,Nw=1024*Mw;function Pw(e,t,n){return[{id:`read-gather-${e}`,label:`read gather ${e}`,description:`Same grid-stride loop and byte count as the linear read, but each thread loads a pseudo-random vec4<f32> from ${n}. Window size describes the access footprint, not cache residency. Loads are independent, so this is throughput, not latency.`,source:jS,category:`bandwidth`,metric:eS,prepare:({ctx:n,data:r,harness:i})=>zS(n,r,i,`read-gather-${e}`,t)},{id:`write-scatter-${e}`,label:`write scatter ${e}`,description:`Writes each vec4 once through a permutation of ${n}, clamped to a power-of-two window fitting the buffer. Every destination has one writer. Reports logical bytes stored per dispatch; smaller windows perform less work.`,source:MS,category:`bandwidth`,metric:eS,prepare:({ctx:n,data:r,harness:i})=>BS(n,r,i,`write-scatter-${e}`,t)}]}var Fw=[{id:`read-linear`,label:`read linear`,description:`Coalesced grid-stride loop: adjacent threads load adjacent vec4<f32>s from a large buffer, folded with addition only, one scalar written per thread. Read-bandwidth-bound.`,source:kS,category:`bandwidth`,metric:eS,prepare:kw(IS)},{id:`write-linear`,label:`write linear`,description:`Coalesced grid-stride loop: adjacent threads store adjacent computed vec4<f32>s into a large buffer with no buffer reads. Write-bandwidth-bound.`,source:AS,category:`bandwidth`,metric:eS,prepare:kw(LS)},...Pw(`16kb`,16*Mw,`a 16 KB window`),...Pw(`4mb`,4*Nw,`a 4 MB window`),...Pw(`64mb`,64*Nw,`a 64 MB window (the whole default buffer)`),{id:`texture-interp-builtin`,label:`texture interp (built-in)`,description:`Each thread does a straight-line "zoom in" scan across a small rgba32float texture, advancing a quarter of a texel per sample (most samples land between the same or adjacent texel pair). The GPU's texture-filtering hardware does the bilinear interpolation via textureSampleLevel. Needs the "float32-filterable" device feature.`,source:vw,category:`bandwidth`,metric:eS,prepare:({ctx:e,harness:t,computeThreads:n,computeIterations:r})=>Dw(e,{...t,threads:n,iterations:r})},{id:`texture-interp-manual`,label:`texture interp (manual)`,description:`Same zoomed-in linear scan and texture as texture-interp-builtin, but each thread fetches the two neighbouring texels with unfiltered textureLoad and lerps them itself with mix â what the built-in bilinear path is competing against. No sampler, works on any device.`,source:yw,category:`bandwidth`,metric:eS,prepare:({ctx:e,harness:t,computeThreads:n,computeIterations:r})=>Ow(e,{...t,threads:n,iterations:r})},{id:`f32-fma-scalar`,label:`fp32 scalar FMA`,description:`Eight independent scalar f32 fused multiply-add chains per thread, unrolled 4x, so the ALU always has work in flight and the number reflects throughput rather than FMA latency. ~no memory traffic.`,source:VS,category:`compute`,metric:Qx,prepare:Aw(YS)},{id:`f32-fma-vec4`,label:`fp32 vec4 FMA`,description:`Eight independent FMA chains held in vec4<f32> registers, unrolled 4x: the fp32 scalar test with every chain 4 lanes wide. Compare with scalar throughput; differences can reflect compiler lowering, live state, and scheduling, not just vector operation cost.`,source:HS,category:`compute`,metric:Qx,prepare:Aw(XS)},{id:`f32-fma-mat4`,label:`fp32 mat4 FMA`,description:`x = m * x + c chained in a register with a mat4x4<f32> (a contracting matrix and rotating nonzero forcing keep it stable): 16 FMAs per step with plenty of independent work, exercising the full mat4 x vec4 multiply.`,source:US,category:`compute`,metric:Qx,prepare:Aw(ZS)},{id:`f32-fma-matvec`,label:`fp32 matvec FMA`,description:`A 4-row x 8-column f32 weight tile held in registers, applied to an 8-wide input every iteration via dot
2245() (outputs feed back as the next inputs). The dot-product-accumulate shape of a GEMV inner loop with zero buffer traffic: pure ALU.`,source:WS,category:`compute`,metric:Qx,prepare:Aw(QS)},{id:`f16-fma-scalar`,label:`fp16 scalar FMA`,description:`Same eight independent, 4x-unrolled FMA chains as the fp32 scalar test, but every operand and accumulator is f16, so the chains run entirely in half precision.`,source:$S,category:`compute`,metric:Qx,prepare:Aw(rC)},{id:`f16-fma-vec4`,label:`fp16 vec4 FMA`,description:`Same eight 4x-unrolled vec4 FMA chains as the fp32 vec4 test, but in vec4<f16>. Only GPUs with packed-half ALUs run this faster than fp32.`,source:eC,category:`compute`,metric:Qx,prepare:Aw(iC)},{id:`f16-fma-mat4`,label:`fp16 mat4 FMA`,description:`Same bounded x = m * x + c recurrence as the fp32 mat4 test, but m, c, and x are all f16, so the mat4x4 x vec4 multiply runs entirely in half precision.`,source:tC,category:`compute`,metric:Qx,prepare:Aw(aC)},{id:`f16-fma-matvec`,label:`fp16 matvec FMA`,description:`Same register-resident 4x8 matvec tile as the fp32 matvec test, but weights, inputs, and dot() accumulation are all f16. Pure ALU: the fp16 win here comes only from the ALU, not from halved memory traffic.`,source:nC,category:`compute`,metric:Qx,prepare:Aw(oC)},{id:`i32-mad-scalar`,label:`i32 scalar multiply-add`,description:`Same eight independent, 4x-unrolled multiply-add chains as the fp32 scalar test, but on i32 with int8-range operands. Measures 32-bit integer multiply-add throughput; overflow wraps.`,source:sC,category:`compute`,metric:$x,prepare:Aw(pC)},{id:`i32-mad-vec4`,label:`i32 vec4 multiply-add`,description:`Same eight 4x-unrolled vec4 multiply-add chains as the fp32 vec4 test, but in vec4<i32>.`,source:cC,category:`compute`,metric:$x,prepare:Aw(mC)},{id:`i32-mad-mat4`,label:`i32 mat4 multiply-add`,description:`x = m * x + c chained in a register, where m is a 4x4 integer matrix emulated as four vec4<i32> rows combined with dot() (WGSL has no mat4x4<i32>): the same 4 dot products a real int4x4 multiply compiles to.`,source:lC,category:`compute`,metric:$x,prepare:Aw(hC)},{id:`i32-mad-matvec`,label:`i32 matvec multiply-add`,description:`Same register-resident 4x8 matvec tile as the fp32 matvec test, with int8-range weights and inputs held unpacked as vec4<i32> and accumulated with integer dot(). The no-extension int8 path: what dot4I8Packed is competing against.`,source:uC,category:`compute`,metric:$x,prepare:Aw(gC)},{id:`i8-dp4a-matvec`,label:`int8 dp4a matvec`,description:`Same 4x8 matvec tile, but weights and inputs stay packed four int8 lanes per u32 and each 4-wide dot product is one dot4I8Packed call from the packed_4x8_integer_dot_product extension. On GPUs without a native dp4a instruction this runs the extension's polyfill.`,source:dC,category:`compute`,metric:$x,prepare:Aw(_C)},{id:`i8-dp4a`,label:`int8 dp4a`,description:`Eight independent accumulators per thread, each summing dot4I8Packed(a, b) â the packed_4x8_integer_dot_product extension's 4-wide int8 dot-product instruction â in a tight loop to measure its peak throughput in isolation.`,source:fC,category:`compute`,metric:$x,prepare:Aw(vC)},{id:`f32-div`,label:`fp32 div`,description:`Eight independent scalar f32 chains of x = a / x + b per thread, unrolled 4x â the fp32 scalar FMA test with divide in place of multiply, so the gap between the two isolates the cost of division. The loop-carried value is the divisor, so the compiler cannot hoist a reciprocal and turn it back into an FMA.`,source:yC,category:`compute`,metric:Qx,prepare:Aw(MC)},{id:`i32-div`,label:`i32 div`,description:`Eight independent scalar i32 chains of x = a / x + b per thread, unrolled 4x â the i32 multiply-add scalar test with divide in place of multiply, divisor loop-carried. Integer division is typically the slowest basic ALU op on a GPU.`,source:bC,category:`compute`,metric:$x,prepare:Aw(NC)},{id:`f32-sqrt`,label:`fp32 sqrt`,description:`Eight independent scalar f32 sqrt-add chains per thread, unrolled 4x. sqrt is a common special-function-unit instruction; this measures its throughput in isolation.`,source:xC,category:`compute`,metric:Qx,prepare:Aw(PC)},{id:`f32-rsqrt`,label:`fp32 rsqrt`,description:`Eight independent scalar f32 inverseSqrt-add chains per thread, unrolled 4x. The op behind every normalize(); most GPUs have a dedicated fast-rsqrt path, so compare against f32-sqrt to see the gap.`,source:SC,category:`compute`,metric:Qx,prepare:Aw(FC)},{id:`f32-pow`,label:`fp32 pow`,description:`Eight independent scalar f32 pow-add chains per thread, unrolled 4x. pow(x, e) for a non-integer e is usually exp2(e * log2(x)) under the hood â several instructions â so expect this well below sqrt/div throughput.`,source:CC,category:`compute`,metric:Qx,prepare:Aw(IC)},{id:`f32-sincos`,label:`fp32 sin/cos`,description:`Eight independent scalar f32 cos(sin(x)) chains per thread, unrolled 4x. Naturally bounded to [-1, 1], so no stabilization term is needed. Measures comb
2245ined sin+cos throughput.`,source:wC,category:`compute`,metric:Qx,prepare:Aw(LC)},{id:`f32-log`,label:`fp32 ln`,description:`Eight independent scalar f32 ln-add chains per thread, unrolled 4x. log(x) is usually log2(x) * ln(2) under the hood, so expect throughput close to a raw log2 special-function call.`,source:TC,category:`compute`,metric:Qx,prepare:Aw(RC)},{id:`f16-div`,label:`fp16 div`,description:`Eight independent scalar f16 chains of x = a / x + b per thread, unrolled 4x â the fp16 scalar FMA test with divide in place of multiply, so the gap against f16-fma-scalar isolates the cost of division in half precision. The loop-carried value is the divisor, so the compiler cannot hoist a reciprocal and turn it back into an FMA.`,source:EC,category:`compute`,metric:Qx,prepare:Aw(zC)},{id:`f16-sqrt`,label:`fp16 sqrt`,description:`Eight independent scalar f16 sqrt-add chains per thread, unrolled 4x. Same shape as f32-sqrt but entirely in half precision.`,source:DC,category:`compute`,metric:Qx,prepare:Aw(BC)},{id:`f16-rsqrt`,label:`fp16 rsqrt`,description:`Eight independent scalar f16 inverseSqrt-add chains per thread, unrolled 4x. Same shape as f32-rsqrt but entirely in half precision; compare against f16-sqrt to see the gap.`,source:OC,category:`compute`,metric:Qx,prepare:Aw(VC)},{id:`f16-pow`,label:`fp16 pow`,description:`Eight independent scalar f16 pow-add chains per thread, unrolled 4x. Same shape as f32-pow but entirely in half precision.`,source:kC,category:`compute`,metric:Qx,prepare:Aw(HC)},{id:`f16-sincos`,label:`fp16 sin/cos`,description:`Eight independent scalar f16 cos(sin(x)) chains per thread, unrolled 4x. Same shape as f32-sincos but entirely in half precision.`,source:AC,category:`compute`,metric:Qx,prepare:Aw(UC)},{id:`f16-log`,label:`fp16 ln`,description:`Eight independent scalar f16 ln-add chains per thread, unrolled 4x. Same shape as f32-log but entirely in half precision.`,source:jC,category:`compute`,metric:Qx,prepare:Aw(WC)},{id:`u32-packunpack`,label:`u32 byte pack/unpack`,description:`Eight independent u32 lanes, unrolled 4x, each step unpacking 4 bytes via shift+mask, incrementing them, and repacking â no pack4x8 (or unpack4x8) builtin, just the bit-twiddling those compile to. Counted as 2 ops per lane step (one unpack + one pack of a whole u32), since the compiler folds the individual shifts and masks.`,source:GC,category:`compute`,metric:$x,prepare:Aw(mw)},{id:`u32-shift`,label:`u32 variable shift`,description:`Eight independent u32 lanes, unrolled 4x, even lanes shifting left and odd lanes right by an amount taken from the loop counter, so every lane cycles through all 32 shift amounts and the number is the average across them. Counted as 1 op per lane step (the shift only; the XOR that refills shifted-out bits is not counted).`,source:JC,category:`compute`,metric:$x,prepare:Aw(_w)},{id:`i32-f32-convert`,label:`i32<->f32 convert`,description:`Eight independent chains per thread, unrolled 4x: xi -> f32(xi)*a+b -> back to i32 each step. Counted as 2 ops per lane step (one convert each way; the FMA is not counted).`,source:KC,category:`compute`,metric:$x,prepare:Aw(hw)},{id:`f32-f16-convert`,label:`f32<->f16 convert`,description:`Eight independent vec2<f32> chains per thread, unrolled 4x: pack2x16float then unpack2x16float (round-trips through fp16 bits) plus a vec2 FMA to keep the chain moving. Counted as 2 ops per lane per step (one convert each way; the FMA is not counted). Unlike f16-*, this needs no shader-f16 device feature â it measures the conversion, not f16 compute.`,source:qC,category:`compute`,metric:$x,prepare:Aw(gw)},jw(`f32-fma-builtin`,`fp32 fma() builtin`,`The fp32 scalar test with the explicit fma(x, a, b) builtin in place of x * a + b. WGSL lets the compiler contract the latter into an FMA; similar timing is consistent with similar lowering but does not prove contraction.`,ew,Qx,64),jw(`f32-select`,`fp32 select`,`Eight independent f32 lanes, unrolled 4x, each stepping x = select(x + b, x - a, x > 1.0): a bounded walk whose direction is a runtime compare. Counted as 1 op per lane step (the select; compare and add/sub not counted).`,tw,$x,32),jw(`f32-clamp`,`fp32 clamp`,`Eight independent f32 lanes, unrolled 4x, each stepping x = clamp(x * a + b, 0, 1). Counted as 1 op per lane step (the clamp; the FMA not counted). Half the ops/s of f32-minmax means clamp compiled to a separate min and max.`,nw,$x,32),jw(`f32-minmax`,`fp32 min/max`,`Eight independent f32 lanes, unrolled 4x, each stepping x = max(min(x * a + b, 1), 0). Counted as 2 ops per lane step (min + max;
2245 the FMA not counted).`,rw,$x,64),jw(`u32-countonebits`,`u32 countOneBits`,`Eight independent u32 lanes, unrolled 4x, each stepping x = countOneBits(x) ^ k. Counted as 1 op per lane step (the popcount; the XOR that keeps the lane moving not counted).`,iw,$x,32),jw(`u32-firstleadingbit`,`u32 firstLeadingBit`,`Eight independent u32 lanes, unrolled 4x, each stepping x = firstLeadingBit(x) ^ k. Counted as 1 op per lane step (the leading-bit scan; the XOR not counted).`,aw,$x,32),jw(`u32-reversebits`,`u32 reverseBits`,`Eight independent u32 lanes, unrolled 4x, each stepping x = reverseBits(x) ^ k. Counted as 1 op per lane step (the bit reverse; the XOR not counted).`,ow,$x,32),jw(`u8-dp4a`,`uint8 dp4a`,`Unsigned twin of i8-dp4a: the same eight loop-carried accumulator chains summing dot4U8Packed(a, b). Shows whether the hardware has a native unsigned dp4a as well as a signed one.`,pw,$x,64,!0),jw(`branch-none`,`branch none`,`Baseline for the branch tests: the same eight-chain fp32 FMA body as the other three with no if at all (identical to f32-fma-scalar).`,lw,Qx,64),jw(`branch-uniform`,`branch uniform`,`The branch-none body with every unrolled step wrapped in an if/else whose two sides do equal work with different constants. The condition alternates each loop trip but is identical for every lane, so every invocation chooses the same source branch. The gap against branch-none includes condition handling and any compiler transformations; it does not isolate a native jump cost.`,uw,Qx,64),jw(`branch-coherent`,`branch coherent`,`Same as branch-uniform, but the condition also flips per 64-thread workgroup: lanes within a wave agree while neighbouring workgroups disagree. Compares workgroup-coherent conditions with globally uniform conditions; timing alone does not identify the native control flow.`,dw,Qx,64),jw(`branch-divergent`,`branch divergent`,`Same as branch-uniform, but the condition flips per lane: adjacent threads take opposite sides. 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