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@@ -1098,6 +1098,10 @@ implementations in PyTorch.</p>
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<td>Fused Linear JSD</td>
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<td><code>liger_kernel.transformers.LigerFusedLinearJSD</code></td>
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</tr>
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<tr>
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<td>Fused Linear KL Divergence</td>
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<td><code>liger_kernel.transformers.LigerFusedLinearKLDivLoss</code></td>
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</tr>
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</tbody>
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</table>
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<h2 id="experimental-kernels">Experimental Kernels<a class="headerlink" href="#experimental-kernels" title="Permanent link">¶</a></h2>
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@@ -1,55 +0,0 @@
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kernel_name,kernel_provider,kernel_operation_mode,metric_name,metric_unit,x_name,x_label,x_value,y_value_50,y_value_20,y_value_80,extra_benchmark_config_str,gpu_name,timestamp,liger_version
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kto_loss,liger,forward,speed,ms,B,Batch Size (B),2,3.2825279235839844,3.2804479598999023,3.2853888988494875,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:19:21,0.5.10
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kto_loss,liger,forward,speed,ms,B,Batch Size (B),4,6.605775833129883,6.478592014312744,6.648127937316895,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:19:21,0.5.10
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kto_loss,liger,forward,speed,ms,B,Batch Size (B),8,12.956992149353027,12.9052095413208,12.996537399291991,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:19:21,0.5.10
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kto_loss,liger,forward,speed,ms,B,Batch Size (B),16,25.663455963134766,25.593625259399417,25.742118072509765,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:19:21,0.5.10
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kto_loss,liger,forward,speed,ms,B,Batch Size (B),32,51.20742416381836,51.20742416381836,51.20742416381836,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:19:21,0.5.10
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kto_loss,huggingface,forward,speed,ms,B,Batch Size (B),2,3.5336320400238037,3.5222464084625247,3.544422483444214,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:19:38,0.5.10
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kto_loss,huggingface,forward,speed,ms,B,Batch Size (B),4,6.366528034210205,6.352678298950195,6.390655994415283,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:19:38,0.5.10
|
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kto_loss,huggingface,forward,speed,ms,B,Batch Size (B),8,12.048687934875488,12.035417366027833,12.061068725585937,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:19:38,0.5.10
|
||||
kto_loss,huggingface,forward,speed,ms,B,Batch Size (B),16,23.290640830993652,23.276774978637697,23.311956024169923,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:19:38,0.5.10
|
||||
kto_loss,huggingface,forward,speed,ms,B,Batch Size (B),32,46.10256004333496,46.08627853393555,46.118841552734374,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:19:38,0.5.10
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kto_loss,liger,full,speed,ms,B,Batch Size (B),2,5.123855829238892,4.941535949707031,5.643481731414796,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:19:53,0.5.10
|
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kto_loss,liger,full,speed,ms,B,Batch Size (B),4,8.228639602661133,8.044639587402344,8.611104011535645,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:19:53,0.5.10
|
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kto_loss,liger,full,speed,ms,B,Batch Size (B),8,14.871295928955078,14.519136428833008,15.598176002502441,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:19:53,0.5.10
|
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kto_loss,liger,full,speed,ms,B,Batch Size (B),16,27.374431610107422,27.2985538482666,27.46200294494629,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:19:53,0.5.10
|
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kto_loss,liger,full,speed,ms,B,Batch Size (B),32,53.22422409057617,53.22422409057617,53.22422409057617,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:19:53,0.5.10
|
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kto_loss,huggingface,full,speed,ms,B,Batch Size (B),2,5.69536018371582,5.379321479797364,6.10686092376709,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:20:10,0.5.10
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kto_loss,huggingface,full,speed,ms,B,Batch Size (B),4,9.326096057891846,9.312140464782715,9.343622016906739,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:20:10,0.5.10
|
||||
kto_loss,huggingface,full,speed,ms,B,Batch Size (B),8,17.51139259338379,17.49594192504883,17.544064331054688,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:20:10,0.5.10
|
||||
kto_loss,huggingface,full,speed,ms,B,Batch Size (B),16,33.48164749145508,33.46792831420898,33.49536666870117,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:20:10,0.5.10
|
||||
kto_loss,huggingface,full,speed,ms,B,Batch Size (B),32,65.69068908691406,65.69068908691406,65.69068908691406,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:20:10,0.5.10
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kto_loss,liger,full,memory,MB,B,Batch Size (B),2,2077.2275390625,2077.2275390625,2077.2275390625,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:20:36,0.5.10
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||||
kto_loss,liger,full,memory,MB,B,Batch Size (B),4,2083.2353515625,2083.2353515625,2083.2353515625,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:20:36,0.5.10
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||||
kto_loss,liger,full,memory,MB,B,Batch Size (B),8,2095.2509765625,2095.2509765625,2095.2509765625,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:20:36,0.5.10
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kto_loss,liger,full,memory,MB,B,Batch Size (B),16,2119.2822265625,2119.2822265625,2119.2822265625,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:20:36,0.5.10
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kto_loss,liger,full,memory,MB,B,Batch Size (B),32,2166.5947265625,2166.5947265625,2166.5947265625,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:20:36,0.5.10
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kto_loss,huggingface,full,memory,MB,B,Batch Size (B),2,3077.24462890625,3077.24462890625,3077.24462890625,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:20:51,0.5.10
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kto_loss,huggingface,full,memory,MB,B,Batch Size (B),4,4834.26123046875,4834.26123046875,4834.26123046875,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:20:51,0.5.10
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kto_loss,huggingface,full,memory,MB,B,Batch Size (B),8,8347.794921875,8347.794921875,8347.794921875,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:20:51,0.5.10
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kto_loss,huggingface,full,memory,MB,B,Batch Size (B),16,15378.361328125,15378.361328125,15378.361328125,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:20:51,0.5.10
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kto_loss,huggingface,full,memory,MB,B,Batch Size (B),32,29437.994140625,29437.994140625,29437.994140625,"{""T"": 512, ""H"": 1024, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16"", ""bias"": true, ""beta"": 0.1, ""ignore_index"": 42}",NVIDIA H200,2025-06-12 18:20:51,0.5.10
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fused_linear_cpo_loss,liger,forward,speed,ms,B,B,2,2898.949951171875,2898.949951171875,2898.949951171875,"{""T"": 1024, ""H"": 4096, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16""}",NVIDIA H200,2025-06-12 18:23:06,0.5.10
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fused_linear_cpo_loss,liger,forward,speed,ms,B,B,4,2889.01318359375,2889.01318359375,2889.01318359375,"{""T"": 1024, ""H"": 4096, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16""}",NVIDIA H200,2025-06-12 18:23:06,0.5.10
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fused_linear_cpo_loss,liger,forward,speed,ms,B,B,8,2910.042724609375,2910.042724609375,2910.042724609375,"{""T"": 1024, ""H"": 4096, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16""}",NVIDIA H200,2025-06-12 18:23:06,0.5.10
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fused_linear_cpo_loss,liger,forward,speed,ms,B,B,16,2893.47265625,2893.47265625,2893.47265625,"{""T"": 1024, ""H"": 4096, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16""}",NVIDIA H200,2025-06-12 18:23:06,0.5.10
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fused_linear_cpo_loss,huggingface,forward,speed,ms,B,B,2,2897.0673828125,2897.0673828125,2897.0673828125,"{""T"": 1024, ""H"": 4096, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16""}",NVIDIA H200,2025-06-12 18:24:39,0.5.10
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fused_linear_cpo_loss,huggingface,forward,speed,ms,B,B,4,2916.94091796875,2916.94091796875,2916.94091796875,"{""T"": 1024, ""H"": 4096, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16""}",NVIDIA H200,2025-06-12 18:24:39,0.5.10
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fused_linear_cpo_loss,huggingface,forward,speed,ms,B,B,8,2896.0009765625,2896.0009765625,2896.0009765625,"{""T"": 1024, ""H"": 4096, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16""}",NVIDIA H200,2025-06-12 18:24:39,0.5.10
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fused_linear_cpo_loss,huggingface,forward,speed,ms,B,B,16,2913.238525390625,2913.238525390625,2913.238525390625,"{""T"": 1024, ""H"": 4096, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16""}",NVIDIA H200,2025-06-12 18:24:39,0.5.10
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fused_linear_cpo_loss,liger,full,speed,ms,B,B,2,2897.10791015625,2897.10791015625,2897.10791015625,"{""T"": 1024, ""H"": 4096, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16""}",NVIDIA H200,2025-06-12 18:26:13,0.5.10
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fused_linear_cpo_loss,liger,full,speed,ms,B,B,4,2922.138671875,2922.138671875,2922.138671875,"{""T"": 1024, ""H"": 4096, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16""}",NVIDIA H200,2025-06-12 18:26:13,0.5.10
|
||||
fused_linear_cpo_loss,liger,full,speed,ms,B,B,8,2951.142822265625,2951.142822265625,2951.142822265625,"{""T"": 1024, ""H"": 4096, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16""}",NVIDIA H200,2025-06-12 18:26:13,0.5.10
|
||||
fused_linear_cpo_loss,liger,full,speed,ms,B,B,16,2996.000244140625,2996.000244140625,2996.000244140625,"{""T"": 1024, ""H"": 4096, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16""}",NVIDIA H200,2025-06-12 18:26:13,0.5.10
|
||||
fused_linear_cpo_loss,huggingface,full,speed,ms,B,B,2,2903.344970703125,2903.344970703125,2903.344970703125,"{""T"": 1024, ""H"": 4096, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16""}",NVIDIA H200,2025-06-12 18:27:47,0.5.10
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||||
fused_linear_cpo_loss,huggingface,full,speed,ms,B,B,4,2921.09912109375,2921.09912109375,2921.09912109375,"{""T"": 1024, ""H"": 4096, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16""}",NVIDIA H200,2025-06-12 18:27:47,0.5.10
|
||||
fused_linear_cpo_loss,huggingface,full,speed,ms,B,B,8,2906.561767578125,2906.561767578125,2906.561767578125,"{""T"": 1024, ""H"": 4096, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16""}",NVIDIA H200,2025-06-12 18:27:47,0.5.10
|
||||
fused_linear_cpo_loss,huggingface,full,speed,ms,B,B,16,2952.124267578125,2952.124267578125,2952.124267578125,"{""T"": 1024, ""H"": 4096, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16""}",NVIDIA H200,2025-06-12 18:27:47,0.5.10
|
||||
fused_linear_cpo_loss,liger,full,memory,MB,B,B,2,4138.03466796875,4138.03466796875,4138.03466796875,"{""T"": 1024, ""H"": 4096, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16""}",NVIDIA H200,2025-06-12 18:29:45,0.5.10
|
||||
fused_linear_cpo_loss,liger,full,memory,MB,B,B,4,4186.0517578125,4186.0517578125,4186.0517578125,"{""T"": 1024, ""H"": 4096, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16""}",NVIDIA H200,2025-06-12 18:29:45,0.5.10
|
||||
fused_linear_cpo_loss,liger,full,memory,MB,B,B,8,4282.0859375,4282.0859375,4282.0859375,"{""T"": 1024, ""H"": 4096, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16""}",NVIDIA H200,2025-06-12 18:29:45,0.5.10
|
||||
fused_linear_cpo_loss,liger,full,memory,MB,B,B,16,4474.154296875,4474.154296875,4474.154296875,"{""T"": 1024, ""H"": 4096, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16""}",NVIDIA H200,2025-06-12 18:29:45,0.5.10
|
||||
fused_linear_cpo_loss,huggingface,full,memory,MB,B,B,2,4606.017578125,4606.017578125,4606.017578125,"{""T"": 1024, ""H"": 4096, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16""}",NVIDIA H200,2025-06-12 18:31:41,0.5.10
|
||||
fused_linear_cpo_loss,huggingface,full,memory,MB,B,B,4,8144.033203125,8144.033203125,8144.033203125,"{""T"": 1024, ""H"": 4096, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16""}",NVIDIA H200,2025-06-12 18:31:41,0.5.10
|
||||
fused_linear_cpo_loss,huggingface,full,memory,MB,B,B,8,15222.064453125,15222.064453125,15222.064453125,"{""T"": 1024, ""H"": 4096, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16""}",NVIDIA H200,2025-06-12 18:31:41,0.5.10
|
||||
fused_linear_cpo_loss,huggingface,full,memory,MB,B,B,16,29378.126953125,29378.126953125,29378.126953125,"{""T"": 1024, ""H"": 4096, ""V"": 128256, ""mode"": ""forward"", ""dtype"": ""torch.bfloat16""}",NVIDIA H200,2025-06-12 18:31:41,0.5.10
|
||||
|
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
@@ -1,34 +0,0 @@
|
||||
b6ed735
|
||||
c1bdc24
|
||||
0701bab
|
||||
d47751c
|
||||
08906d3
|
||||
02bac05
|
||||
5e8f12b
|
||||
7705dcc
|
||||
2845fe8
|
||||
1c07943
|
||||
77a4c1a
|
||||
c856fba
|
||||
33924d2
|
||||
d5648bf-v0.6.3
|
||||
a80f30b
|
||||
817436f
|
||||
4c32ab6
|
||||
0a62700-v0.6.4
|
||||
0a62700
|
||||
3d075fd
|
||||
49e6353
|
||||
6059dfb
|
||||
5101e3c
|
||||
3b79375
|
||||
4444fdf
|
||||
7656bcb
|
||||
81f932a-v0.6.5
|
||||
1fdb668
|
||||
7644a0f-v0.7.0
|
||||
7644a0f
|
||||
9c1ddb7
|
||||
5057ca8
|
||||
e6f84b8
|
||||
ab7fe2a
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
@@ -1,55 +0,0 @@
|
||||
<!DOCTYPE html>
|
||||
<html lang="en">
|
||||
<head>
|
||||
<meta charset="UTF-8" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0"/>
|
||||
<title>Benchmark Visualization</title>
|
||||
<link rel="stylesheet" href="style.css"/>
|
||||
<script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
|
||||
<script src="https://cdn.jsdelivr.net/npm/[email protected]/papaparse.min.js"></script>
|
||||
</head>
|
||||
<body>
|
||||
<div class="container">
|
||||
<div class="panel1">
|
||||
<h1>Panel 1</h1>
|
||||
<div class="controls">
|
||||
<label>Commit Hash:</label>
|
||||
<select id="commit"></select>
|
||||
|
||||
<label for="kernel">Kernel Name:</label>
|
||||
<select id="kernel"></select>
|
||||
|
||||
<label for="mode">Pass Type:</label>
|
||||
<select id="mode"></select>
|
||||
</div>
|
||||
<div class="metric-section">
|
||||
<h2>Speed Metrics</h2>
|
||||
<canvas id="benchmarkChartSpeed"></canvas>
|
||||
<h2>Memory Metrics</h2>
|
||||
<canvas id="benchmarkChartMemory"></canvas>
|
||||
</div>
|
||||
</div>
|
||||
<div class="panel2">
|
||||
<h1>Panel 2</h1>
|
||||
<div class="controls">
|
||||
<label>Commit Hash:</label>
|
||||
<select id="commit2"></select>
|
||||
|
||||
<label for="kernel">Kernel Name:</label>
|
||||
<select id="kernel2"></select>
|
||||
|
||||
<label for="mode">Pass Type:</label>
|
||||
<select id="mode2"></select>
|
||||
</div>
|
||||
<div class="metric-section">
|
||||
<h2>Speed Metrics</h2>
|
||||
<canvas id="benchmarkChart2Speed"></canvas>
|
||||
<h2>Memory Metrics</h2>
|
||||
<canvas id="benchmarkChart2Memory"></canvas>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<script src="script.js"></script>
|
||||
</body>
|
||||
</html>
|
||||
@@ -1,295 +0,0 @@
|
||||
let chartSpeed;
|
||||
let chartMemory;
|
||||
let chart2Speed;
|
||||
let chart2Memory;
|
||||
|
||||
const primaryBase = 'https://raw.githubusercontent.com/linkedin/Liger-Kernel/refs/heads/gh-pages/benchmarks';
|
||||
const fallbackBase = 'https://cdn.jsdelivr.net/gh/linkedin/Liger-Kernel@gh-pages/benchmarks';
|
||||
|
||||
async function fetchWithFallback(path) {
|
||||
const urls = [
|
||||
`${primaryBase}/${path}`,
|
||||
`${fallbackBase}/${path}`,
|
||||
];
|
||||
let lastErr;
|
||||
for (const url of urls) {
|
||||
try {
|
||||
const res = await fetch(url);
|
||||
if (res.ok) return res;
|
||||
lastErr = new Error(`HTTP ${res.status} for ${url}`);
|
||||
} catch (e) {
|
||||
lastErr = e;
|
||||
}
|
||||
}
|
||||
throw lastErr || new Error('Failed to fetch with fallback');
|
||||
}
|
||||
|
||||
document.addEventListener("DOMContentLoaded", async () => {
|
||||
const commits = await fetchCommitHashes();
|
||||
// const commits = ["a96bdc1", "bc105fd", "cbe66ed"]
|
||||
populateCommitDropdown(commits, "commit");
|
||||
populateCommitDropdown(commits, "commit2");
|
||||
|
||||
document.getElementById("commit").addEventListener("change", (e) => {
|
||||
loadCSV(e.target.value, 1);
|
||||
});
|
||||
|
||||
document.getElementById("commit2").addEventListener("change", (e) => {
|
||||
loadCSV(e.target.value, 2);
|
||||
});
|
||||
|
||||
if (commits.length > 0) {
|
||||
loadCSV(commits[0], 1);
|
||||
loadCSV(commits[0], 2);
|
||||
}
|
||||
});
|
||||
|
||||
async function fetchCommitHashes() {
|
||||
try {
|
||||
const response = await fetchWithFallback('commits.txt');
|
||||
const text = await response.text();
|
||||
// Split by newlines and filter out empty lines
|
||||
return text.split('\n')
|
||||
.map(line => line.trim())
|
||||
.filter(line => line.length > 0);
|
||||
} catch (err) {
|
||||
console.error("Failed to fetch commit hashes:", err);
|
||||
return [];
|
||||
}
|
||||
}
|
||||
|
||||
function populateCommitDropdown(commits, selectId) {
|
||||
const select = document.getElementById(selectId);
|
||||
select.innerHTML = "";
|
||||
commits.forEach(commit => {
|
||||
const opt = document.createElement("option");
|
||||
opt.value = opt.textContent = commit;
|
||||
select.appendChild(opt);
|
||||
});
|
||||
}
|
||||
|
||||
function loadCSV(commit, panel) {
|
||||
Papa.parse(`${primaryBase}/${commit}/benchmark.csv`, {
|
||||
download: true,
|
||||
header: true,
|
||||
dynamicTyping: true,
|
||||
complete: async (result) => {
|
||||
// If primary failed to load any data rows, try fallback
|
||||
let data = result.data.filter(d => d.kernel_provider);
|
||||
if (!data || data.length === 0) {
|
||||
try {
|
||||
const res = await fetchWithFallback(`${commit}/benchmark.csv`);
|
||||
const text = await res.text();
|
||||
const parsed = Papa.parse(text, { header: true, dynamicTyping: true });
|
||||
data = parsed.data.filter(d => d.kernel_provider);
|
||||
} catch (e) {
|
||||
alert("Failed to load CSV for commit: " + commit);
|
||||
console.error(e);
|
||||
return;
|
||||
}
|
||||
}
|
||||
if (panel === 1) {
|
||||
setupControls(data, 1);
|
||||
renderCharts(data, 1);
|
||||
} else {
|
||||
setupControls(data, 2);
|
||||
renderCharts(data, 2);
|
||||
}
|
||||
},
|
||||
error: async (err) => {
|
||||
// Try fallback immediately
|
||||
try {
|
||||
const res = await fetchWithFallback(`${commit}/benchmark.csv`);
|
||||
const text = await res.text();
|
||||
const parsed = Papa.parse(text, { header: true, dynamicTyping: true });
|
||||
const data = parsed.data.filter(d => d.kernel_provider);
|
||||
if (panel === 1) {
|
||||
setupControls(data, 1);
|
||||
renderCharts(data, 1);
|
||||
} else {
|
||||
setupControls(data, 2);
|
||||
renderCharts(data, 2);
|
||||
}
|
||||
} catch (e) {
|
||||
alert("Failed to load CSV for commit: " + commit);
|
||||
console.error(err);
|
||||
}
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
function setupControls(data, panel) {
|
||||
const kernelSet = new Set(data.map(d => d.kernel_name));
|
||||
const modeSet = new Set(data.map(d => d.kernel_operation_mode));
|
||||
|
||||
const kernelSelect = document.getElementById(panel === 1 ? "kernel" : "kernel2");
|
||||
const modeSelect = document.getElementById(panel === 1 ? "mode" : "mode2");
|
||||
|
||||
kernelSelect.innerHTML = "";
|
||||
modeSelect.innerHTML = "";
|
||||
|
||||
kernelSet.forEach(k => {
|
||||
const opt = document.createElement("option");
|
||||
opt.value = opt.textContent = k;
|
||||
kernelSelect.appendChild(opt);
|
||||
});
|
||||
|
||||
modeSet.forEach(m => {
|
||||
const opt = document.createElement("option");
|
||||
opt.value = opt.textContent = m;
|
||||
modeSelect.appendChild(opt);
|
||||
});
|
||||
|
||||
kernelSelect.addEventListener("change", () => renderCharts(data, panel));
|
||||
modeSelect.addEventListener("change", () => renderCharts(data, panel));
|
||||
}
|
||||
|
||||
function renderCharts(data, panel) {
|
||||
const kernel = document.getElementById(panel === 1 ? "kernel" : "kernel2").value;
|
||||
const mode = document.getElementById(panel === 1 ? "mode" : "mode2").value;
|
||||
|
||||
// Render speed chart
|
||||
renderChart(data, panel, "speed", kernel, mode);
|
||||
// Render memory chart
|
||||
renderChart(data, panel, "memory", kernel, mode);
|
||||
}
|
||||
|
||||
function renderChart(data, panel, metric, kernel, mode) {
|
||||
|
||||
const filtered = data.filter(
|
||||
d =>
|
||||
d.kernel_name === kernel &&
|
||||
d.metric_name.toLowerCase() === metric.toLowerCase() &&
|
||||
d.kernel_operation_mode === mode
|
||||
);
|
||||
|
||||
|
||||
const batchSizes = [...new Set(filtered.map(d => d.x_value))].sort((a, b) => a - b);
|
||||
const providers = [...new Set(filtered.map(d => d.kernel_provider))];
|
||||
|
||||
|
||||
|
||||
const datasets = providers.map(provider => {
|
||||
const values = batchSizes.map(bs => {
|
||||
const row = filtered.find(d => d.kernel_provider === provider && d.x_value === bs);
|
||||
return row ? row.y_value_50 : null;
|
||||
});
|
||||
|
||||
let borderColor;
|
||||
if (provider === "liger") {
|
||||
borderColor = "#FF6B35";
|
||||
} else if (provider === "huggingface") {
|
||||
borderColor = "#4A90E2";
|
||||
} else {
|
||||
borderColor = "#2ECC71"; // For any third provider (like torch_compile)
|
||||
}
|
||||
|
||||
return {
|
||||
label: provider,
|
||||
data: values,
|
||||
borderColor: borderColor,
|
||||
backgroundColor: "transparent",
|
||||
tension: 0.2,
|
||||
pointRadius: 4,
|
||||
pointHoverRadius: 6,
|
||||
borderWidth: 2,
|
||||
};
|
||||
});
|
||||
|
||||
const chartId = panel === 1
|
||||
? (metric === "speed" ? "benchmarkChartSpeed" : "benchmarkChartMemory")
|
||||
: (metric === "speed" ? "benchmarkChart2Speed" : "benchmarkChart2Memory");
|
||||
|
||||
const ctx = document.getElementById(chartId).getContext("2d");
|
||||
|
||||
// Destroy existing chart if it exists
|
||||
if (panel === 1) {
|
||||
if (metric === "speed" && chartSpeed) chartSpeed.destroy();
|
||||
if (metric === "memory" && chartMemory) chartMemory.destroy();
|
||||
} else {
|
||||
if (metric === "speed" && chart2Speed) chart2Speed.destroy();
|
||||
if (metric === "memory" && chart2Memory) chart2Memory.destroy();
|
||||
}
|
||||
|
||||
// Calculate smart Y-axis range for better visibility of differences
|
||||
const allValues = datasets.flatMap(d => d.data.filter(v => v !== null));
|
||||
let yAxisConfig = {
|
||||
title: {
|
||||
display: true,
|
||||
text: `${metric} (${getMetricUnit(metric)})`
|
||||
},
|
||||
type: 'linear'
|
||||
};
|
||||
|
||||
if (allValues.length > 0) {
|
||||
const minVal = Math.min(...allValues);
|
||||
const maxVal = Math.max(...allValues);
|
||||
const range = maxVal - minVal;
|
||||
|
||||
// If the range is small compared to the minimum value, focus on the data range
|
||||
if (range < minVal * 0.1) {
|
||||
yAxisConfig.min = minVal - (range * 0.2);
|
||||
yAxisConfig.max = maxVal + (range * 0.2);
|
||||
} else {
|
||||
yAxisConfig.beginAtZero = true;
|
||||
}
|
||||
} else {
|
||||
yAxisConfig.beginAtZero = true;
|
||||
}
|
||||
|
||||
const newChart = new Chart(ctx, {
|
||||
type: "line",
|
||||
data: {
|
||||
labels: batchSizes,
|
||||
datasets: datasets,
|
||||
},
|
||||
options: {
|
||||
responsive: true,
|
||||
plugins: {
|
||||
title: {
|
||||
display: true,
|
||||
text: `${kernel} - ${metric} (${mode})`,
|
||||
font: {
|
||||
size: 14,
|
||||
weight: 'bold'
|
||||
}
|
||||
},
|
||||
legend: {
|
||||
position: "top",
|
||||
},
|
||||
tooltip: {
|
||||
callbacks: {
|
||||
label: function(context) {
|
||||
const label = context.dataset.label || '';
|
||||
const value = context.parsed.y;
|
||||
return `${label}: ${value.toFixed(2)} ${getMetricUnit(metric)}`;
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
scales: {
|
||||
x: {
|
||||
title: { display: true, text: "Batch Size (B)" },
|
||||
},
|
||||
y: yAxisConfig
|
||||
},
|
||||
interaction: {
|
||||
intersect: false,
|
||||
mode: 'index'
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
// Store the chart reference
|
||||
if (panel === 1) {
|
||||
if (metric === "speed") chartSpeed = newChart;
|
||||
else chartMemory = newChart;
|
||||
} else {
|
||||
if (metric === "speed") chart2Speed = newChart;
|
||||
else chart2Memory = newChart;
|
||||
}
|
||||
}
|
||||
|
||||
function getMetricUnit(metric) {
|
||||
return metric === 'speed' ? 'ms' : 'MB';
|
||||
}
|
||||
@@ -1,96 +0,0 @@
|
||||
body {
|
||||
font-family: Arial, sans-serif;
|
||||
background-color: #f4f4f9;
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
}
|
||||
|
||||
.container {
|
||||
max-width: 80vw;
|
||||
margin: 2rem auto;
|
||||
padding: 1rem;
|
||||
padding-left: 10px;
|
||||
padding-right: 10px;
|
||||
background: white;
|
||||
border-radius: 10px;
|
||||
box-shadow: 0 0 10px rgba(0, 0, 0, 0.1);
|
||||
display: flex;
|
||||
justify-content: space-between;
|
||||
width: 100%;
|
||||
}
|
||||
|
||||
h1 {
|
||||
text-align: center;
|
||||
margin-bottom: 2rem;
|
||||
}
|
||||
|
||||
h2 {
|
||||
text-align: center;
|
||||
margin: 1rem 0;
|
||||
color: #333;
|
||||
}
|
||||
|
||||
.controls {
|
||||
display: flex;
|
||||
flex-wrap: wrap;
|
||||
justify-content: center;
|
||||
gap: 1rem;
|
||||
margin-bottom: 2rem;
|
||||
background: #f8f9fa;
|
||||
padding: 15px;
|
||||
border-radius: 8px;
|
||||
border: 1px solid #e9ecef;
|
||||
}
|
||||
|
||||
.controls label {
|
||||
display: block;
|
||||
margin-bottom: 5px;
|
||||
color: #495057;
|
||||
font-size: 14px;
|
||||
font-weight: bold;
|
||||
}
|
||||
|
||||
.metric-section {
|
||||
margin-top: 2rem;
|
||||
}
|
||||
|
||||
.metric-section canvas {
|
||||
max-width: 100%;
|
||||
height: 300px;
|
||||
margin-bottom: 2rem;
|
||||
}
|
||||
|
||||
canvas {
|
||||
max-width: 100%;
|
||||
height: 500px;
|
||||
}
|
||||
|
||||
.panel1 {
|
||||
width: 100%;
|
||||
}
|
||||
|
||||
.panel2 {
|
||||
width: 100%;
|
||||
}
|
||||
|
||||
/* Select styling improvements */
|
||||
select {
|
||||
padding: 8px 12px;
|
||||
border: 2px solid #e9ecef;
|
||||
border-radius: 6px;
|
||||
background: white;
|
||||
font-size: 14px;
|
||||
color: #333;
|
||||
transition: border-color 0.3s ease;
|
||||
min-width: 150px;
|
||||
}
|
||||
|
||||
select:focus {
|
||||
outline: none;
|
||||
border-color: #667eea;
|
||||
box-shadow: 0 0 0 3px rgba(102, 126, 234, 0.1);
|
||||
}
|
||||
|
||||
select:hover {
|
||||
border-color: #667eea;
|
||||
}
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,31 +0,0 @@
|
||||
{
|
||||
"description": "Golden reference commits for kernel performance benchmarking",
|
||||
"default_commit": "c1bdc24",
|
||||
"golden_commits": {
|
||||
"cross_entropy": "0701bab",
|
||||
"distill_jsd_loss": "c1bdc24",
|
||||
"dpo_loss": "c1bdc24",
|
||||
"dyt_beta=False": "0701bab",
|
||||
"dyt_beta=True": "0701bab",
|
||||
"fused_linear_cpo_loss": "c1bdc24",
|
||||
"fused_linear_cross_entropy": "0701bab",
|
||||
"fused_linear_jsd": "c1bdc24",
|
||||
"fused_linear_simpo_loss": "c1bdc24",
|
||||
"fused_neighborhood_attention": "0701bab",
|
||||
"geglu": "0701bab",
|
||||
"group_norm": "0701bab",
|
||||
"jsd": "c1bdc24",
|
||||
"kl_div": "0701bab",
|
||||
"kto_loss": "c1bdc24",
|
||||
"layer_norm": "0701bab",
|
||||
"multi_token_attention": "0701bab",
|
||||
"rms_norm": "0701bab",
|
||||
"rope": "0701bab",
|
||||
"softmax": "0701bab",
|
||||
"sparse_multi_token_attention": "0701bab",
|
||||
"sparsemax": "0701bab",
|
||||
"swiglu": "0701bab",
|
||||
"tvd": "0701bab",
|
||||
"distill_cosine_loss": "08906d3"
|
||||
}
|
||||
}
|
||||
@@ -1,90 +0,0 @@
|
||||
<!DOCTYPE html>
|
||||
<html lang="en">
|
||||
<head>
|
||||
|
||||
<meta charset="UTF-8">
|
||||
<title>Liger Benchmark Dashboard</title>
|
||||
<link rel="stylesheet" href="style.css">
|
||||
</head>
|
||||
<body data-theme="light">
|
||||
<div class="container">
|
||||
<button class="theme-toggle" onclick="toggleTheme()" title="Toggle Theme">☀️</button>
|
||||
<button class="theme-toggle" onclick="goToDetailedView()">Detailed View</button>
|
||||
<h1>Liger Kernel Benchmark Comparison</h1>
|
||||
|
||||
<div class="selectors">
|
||||
<label>
|
||||
Show last N commits:
|
||||
<select id="commitCount" onchange="loadData()">
|
||||
<option value="5">5</option>
|
||||
<option value="20">20</option>
|
||||
<option value="50">50</option>
|
||||
<option value="all">All</option>
|
||||
</select>
|
||||
</label>
|
||||
<label>
|
||||
Metric type:
|
||||
<select id="metricType" onchange="renderTables()">
|
||||
<option value="full">full</option>
|
||||
<option value="forward">forward</option>
|
||||
<option value="backward">backward</option>
|
||||
</select>
|
||||
</label>
|
||||
<label>
|
||||
Category:
|
||||
<select id="categoryFilter" onchange="renderTables()">
|
||||
<option value="all">All Categories</option>
|
||||
<option value="pretraining">Pretraining</option>
|
||||
<option value="distillation">Distillation</option>
|
||||
<option value="post_training">Post Training</option>
|
||||
</select>
|
||||
</label>
|
||||
|
||||
<label>
|
||||
Show:
|
||||
<select id="viewType" onchange="loadData()">
|
||||
<option value="commits">Commits</option>
|
||||
<option value="versions">Versions</option>
|
||||
</select>
|
||||
</label>
|
||||
|
||||
<input type="text" id="kernelSearch" placeholder="Search kernel name..." oninput="renderTables()">
|
||||
</div>
|
||||
|
||||
<div class="legend">
|
||||
<h3>Kernel Categories</h3>
|
||||
<div class="legend-items">
|
||||
<div class="legend-item">
|
||||
<span class="legend-color pretraining"></span>
|
||||
<span class="legend-label">Pretraining</span>
|
||||
</div>
|
||||
<div class="legend-item">
|
||||
<span class="legend-color distillation"></span>
|
||||
<span class="legend-label">Distillation</span>
|
||||
</div>
|
||||
<div class="legend-item">
|
||||
<span class="legend-color post_training"></span>
|
||||
<span class="legend-label">Post Training</span>
|
||||
</div>
|
||||
<div class="legend-item">
|
||||
<span class="legend-color other"></span>
|
||||
<span class="legend-label">Other</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<h2>Memory</h2>
|
||||
<div class="scroll-container">
|
||||
<table id="memoryTable"></table>
|
||||
</div>
|
||||
|
||||
<h2>Speed</h2>
|
||||
<div class="scroll-container">
|
||||
<table id="speedTable"></table>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<script src="script.js"></script>
|
||||
</body>
|
||||
</html>
|
||||
|
||||
@@ -1,425 +0,0 @@
|
||||
// TODO: Make this configurable into a separate file
|
||||
const defaultReferenceCommit = 'c1bdc24';
|
||||
const benchmarkPrimaryBase = 'https://raw.githubusercontent.com/linkedin/Liger-Kernel/refs/heads/gh-pages/benchmarks';
|
||||
const benchmarkFallbackBase = 'https://cdn.jsdelivr.net/gh/linkedin/Liger-Kernel@gh-pages/benchmarks';
|
||||
|
||||
// Kernel categories configuration
|
||||
const kernelCategories = {
|
||||
"pretraining": [
|
||||
"cross_entropy",
|
||||
"fused_linear_cross_entropy",
|
||||
"softmax",
|
||||
"sparsemax",
|
||||
"rope",
|
||||
"geglu",
|
||||
"swiglu",
|
||||
"layer_norm",
|
||||
"rms_norm",
|
||||
"group_norm",
|
||||
"multi_token_attention",
|
||||
"sparse_multi_token_attention",
|
||||
"fused_neighborhood_attention"
|
||||
],
|
||||
"distillation": [
|
||||
"distill_jsd_loss",
|
||||
"distill_cosine_loss",
|
||||
"jsd",
|
||||
"kl_div",
|
||||
"tvd",
|
||||
"fused_linear_jsd",
|
||||
"dyt_beta=True",
|
||||
"dyt_beta=False"
|
||||
],
|
||||
"post_training": [
|
||||
"dpo_loss",
|
||||
"kto_loss",
|
||||
"fused_linear_cpo_loss",
|
||||
"fused_linear_simpo_loss"
|
||||
]
|
||||
};
|
||||
|
||||
let allDataByCommit = {};
|
||||
let kernelMeta = {};
|
||||
let configData = {}; // Store configuration data for tooltips - format: {commit: {kernelKey: config}}
|
||||
let goldenCommits = {};
|
||||
|
||||
async function fetchWithFallback(path, responseType = 'text') {
|
||||
const urls = [
|
||||
`${benchmarkPrimaryBase}/${path}`,
|
||||
`${benchmarkFallbackBase}/${path}`,
|
||||
];
|
||||
let lastErr;
|
||||
for (const url of urls) {
|
||||
try {
|
||||
const res = await fetch(url);
|
||||
if (res.ok) {
|
||||
if (responseType === 'json') return await res.json();
|
||||
return await res.text();
|
||||
}
|
||||
lastErr = new Error(`HTTP ${res.status} for ${url}`);
|
||||
} catch (e) {
|
||||
lastErr = e;
|
||||
}
|
||||
}
|
||||
throw lastErr || new Error('Failed to fetch with fallback');
|
||||
}
|
||||
|
||||
async function loadGoldenCommits() {
|
||||
try {
|
||||
const data = await fetchWithFallback('golden_commits.json', 'json');
|
||||
return data.golden_commits || {};
|
||||
} catch (e) {
|
||||
console.warn('Could not load golden commits from JSON');
|
||||
}
|
||||
return {};
|
||||
}
|
||||
|
||||
function getGoldenCommit(kernelName) {
|
||||
// Extract base kernel name by removing operation mode and metric suffixes
|
||||
let baseKernelName = kernelName;
|
||||
|
||||
const suffixes = ['_forward_speed', '_backward_speed', '_full_speed', '_full_memory', '_forward_memory', '_backward_memory'];
|
||||
for (const suffix of suffixes) {
|
||||
if (baseKernelName.endsWith(suffix)) {
|
||||
baseKernelName = baseKernelName.slice(0, -suffix.length);
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
// Check for exact base kernel match
|
||||
if (goldenCommits[baseKernelName]) {
|
||||
return goldenCommits[baseKernelName];
|
||||
}
|
||||
|
||||
// Check for partial matches - find the longest matching key
|
||||
let bestMatch = '';
|
||||
let bestCommit = defaultReferenceCommit;
|
||||
|
||||
for (const [key, commit] of Object.entries(goldenCommits)) {
|
||||
if (kernelName.includes(key) && key.length > bestMatch.length) {
|
||||
bestMatch = key;
|
||||
bestCommit = commit;
|
||||
}
|
||||
}
|
||||
|
||||
return bestCommit;
|
||||
}
|
||||
|
||||
function getKernelCategory(kernelName) {
|
||||
// Extract base kernel name by removing operation mode and metric suffixes
|
||||
let baseKernelName = kernelName;
|
||||
|
||||
const suffixes = ['_forward_speed', '_backward_speed', '_full_speed', '_full_memory', '_forward_memory', '_backward_memory'];
|
||||
for (const suffix of suffixes) {
|
||||
if (baseKernelName.endsWith(suffix)) {
|
||||
baseKernelName = baseKernelName.slice(0, -suffix.length);
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
// Find which category this kernel belongs to
|
||||
for (const [category, kernels] of Object.entries(kernelCategories)) {
|
||||
for (const kernelPattern of kernels) {
|
||||
if (baseKernelName === kernelPattern || baseKernelName.includes(kernelPattern)) {
|
||||
return category;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return 'other'; // Default category for unmatched kernels
|
||||
}
|
||||
|
||||
function toggleTheme() {
|
||||
const body = document.body;
|
||||
const themeButton = document.querySelector('.theme-toggle');
|
||||
const isDark = body.getAttribute('data-theme') === 'dark';
|
||||
body.setAttribute('data-theme', isDark ? 'light' : 'dark');
|
||||
themeButton.textContent = isDark ? '☀️' : '🌙';
|
||||
}
|
||||
|
||||
function goToDetailedView() {
|
||||
const baseUrl = window.location.href.endsWith('/') ? window.location.href : window.location.href + '/';
|
||||
window.location.href = baseUrl + 'detailed';
|
||||
}
|
||||
|
||||
async function fetchCommits() {
|
||||
const text = await fetchWithFallback('commits.txt', 'text');
|
||||
const all = text.trim().split('\n');
|
||||
const commits = all.filter(line => !line.includes('-'));
|
||||
const versions = all.filter(line => line.includes('-'));
|
||||
return { commits, versions };
|
||||
}
|
||||
|
||||
async function fetchCSV(commit) {
|
||||
const text = await fetchWithFallback(`${commit}/benchmark.csv`, 'text');
|
||||
const rows = text.trim().split('\n');
|
||||
const headers = rows[0].split(',');
|
||||
const data = {};
|
||||
|
||||
for (let i = 1; i < rows.length; i++) {
|
||||
const rowText = rows[i];
|
||||
const cols = [];
|
||||
let currentCol = '';
|
||||
let inQuotes = false;
|
||||
let quoteChar = '';
|
||||
|
||||
// Parse CSV row properly handling quoted fields
|
||||
for (let j = 0; j < rowText.length; j++) {
|
||||
const char = rowText[j];
|
||||
|
||||
if ((char === '"' || char === "'") && !inQuotes) {
|
||||
inQuotes = true;
|
||||
quoteChar = char;
|
||||
} else if (char === quoteChar && inQuotes) {
|
||||
inQuotes = false;
|
||||
quoteChar = '';
|
||||
} else if (char === ',' && !inQuotes) {
|
||||
cols.push(currentCol.trim());
|
||||
currentCol = '';
|
||||
} else {
|
||||
currentCol += char;
|
||||
}
|
||||
}
|
||||
cols.push(currentCol.trim());
|
||||
|
||||
const row = Object.fromEntries(headers.map((h, idx) => [h.trim(), cols[idx]?.trim()]));
|
||||
if (row.kernel_provider !== 'liger') continue;
|
||||
|
||||
const kernelKey = `${row.kernel_name}_${row.kernel_operation_mode}_${row.metric_name}`;
|
||||
|
||||
if (!data[kernelKey]) {
|
||||
data[kernelKey] = parseFloat(row.y_value_50);
|
||||
if (!kernelMeta[kernelKey]) {
|
||||
kernelMeta[kernelKey] = {
|
||||
x_label: row.x_label,
|
||||
x_value: row.x_value
|
||||
};
|
||||
}
|
||||
// Store configuration data for tooltips
|
||||
if (!configData[commit]) {
|
||||
configData[commit] = {};
|
||||
}
|
||||
if (!configData[commit][kernelKey]) {
|
||||
configData[commit][kernelKey] = {
|
||||
extra_benchmark_config_str: row.extra_benchmark_config_str || 'N/A',
|
||||
gpu_name: row.gpu_name || 'N/A',
|
||||
liger_version: row.liger_version || 'N/A'
|
||||
};
|
||||
}
|
||||
}
|
||||
}
|
||||
return data;
|
||||
}
|
||||
|
||||
async function loadData() {
|
||||
document.getElementById('speedTable').innerHTML = 'Loading...';
|
||||
document.getElementById('memoryTable').innerHTML = 'Loading...';
|
||||
|
||||
goldenCommits = await loadGoldenCommits();
|
||||
|
||||
const count = document.getElementById('commitCount').value;
|
||||
const viewType = document.getElementById('viewType').value;
|
||||
const { commits, versions } = await fetchCommits();
|
||||
|
||||
let selectedList = viewType === 'versions' ? versions : commits;
|
||||
const selectedCommits = count === 'all' ? selectedList : selectedList.slice(-parseInt(count));
|
||||
|
||||
// Collect all unique commits that need to be loaded
|
||||
const commitsToLoad = new Set(selectedCommits);
|
||||
|
||||
// Add reference commits only if they're not already in the selected commits
|
||||
Object.values(goldenCommits).forEach(commit => {
|
||||
if (!selectedCommits.includes(commit)) {
|
||||
commitsToLoad.add(commit);
|
||||
}
|
||||
});
|
||||
|
||||
// Also add the default reference commit if not already included
|
||||
if (!selectedCommits.includes(defaultReferenceCommit)) {
|
||||
commitsToLoad.add(defaultReferenceCommit);
|
||||
}
|
||||
|
||||
allDataByCommit = {};
|
||||
kernelMeta = {};
|
||||
configData = {};
|
||||
|
||||
await Promise.all([...commitsToLoad].map(async (commit) => {
|
||||
const data = await fetchCSV(commit);
|
||||
if (data) allDataByCommit[commit] = data;
|
||||
}));
|
||||
|
||||
await renderTables();
|
||||
}
|
||||
|
||||
function compareMetric(current, reference) {
|
||||
const THRESHOLD = 0.10;
|
||||
if (current == null || reference == null) return '';
|
||||
const delta = (current - reference) / reference;
|
||||
if (delta > THRESHOLD) return 'red';
|
||||
if (delta < 0) return 'green';
|
||||
return '';
|
||||
}
|
||||
|
||||
function formatConfigForTooltip(config) {
|
||||
try {
|
||||
const parsed = JSON.parse(config.extra_benchmark_config_str);
|
||||
const configStr = Object.entries(parsed)
|
||||
.map(([key, value]) => `${key}: ${value}`)
|
||||
.join('\n');
|
||||
return `Extra Config:\n${configStr}\n\nGPU: ${config.gpu_name}\nLiger Version: ${config.liger_version}`;
|
||||
} catch (e) {
|
||||
return `Extra Config: ${config.extra_benchmark_config_str}\n\nGPU: ${config.gpu_name}\nLiger Version: ${config.liger_version}`;
|
||||
}
|
||||
}
|
||||
|
||||
async function renderTables() {
|
||||
const metricType = document.getElementById('metricType').value;
|
||||
const searchQuery = document.getElementById('kernelSearch').value.toLowerCase();
|
||||
const categoryFilter = document.getElementById('categoryFilter').value;
|
||||
const speedTable = document.getElementById('speedTable');
|
||||
const memoryTable = document.getElementById('memoryTable');
|
||||
const viewType = document.getElementById('viewType').value;
|
||||
|
||||
speedTable.innerHTML = '';
|
||||
memoryTable.innerHTML = '';
|
||||
|
||||
const count = document.getElementById('commitCount').value;
|
||||
const { commits: allCommitsList, versions: allVersionsList } = await fetchCommits();
|
||||
const selectedList = viewType === 'versions' ? allVersionsList : allCommitsList;
|
||||
const selectedCommits = count === 'all' ? selectedList : selectedList.slice(-parseInt(count));
|
||||
|
||||
const allLoadedCommits = Object.keys(allDataByCommit);
|
||||
const commits = selectedCommits.filter(commit => allLoadedCommits.includes(commit)).reverse();
|
||||
|
||||
function createTable(table, filterMetric) {
|
||||
let header = `<tr><th>Kernel</th><th>X</th>`;
|
||||
if (viewType === 'commits') {
|
||||
header += `<th>Golden Reference</th>`;
|
||||
}
|
||||
for (const commit of commits) {
|
||||
header += `<th>${commit}</th>`;
|
||||
}
|
||||
header += '</tr>';
|
||||
table.innerHTML += header;
|
||||
|
||||
const allKeys = new Set();
|
||||
for (const commit of commits) {
|
||||
for (const k in allDataByCommit[commit]) {
|
||||
if (k.includes(`_${metricType}_${filterMetric}`)) allKeys.add(k);
|
||||
}
|
||||
}
|
||||
|
||||
[...allKeys].forEach((kernelKey) => {
|
||||
if (searchQuery && !kernelKey.toLowerCase().includes(searchQuery)) return;
|
||||
|
||||
if (categoryFilter !== 'all') {
|
||||
const kernelCategory = getKernelCategory(kernelKey);
|
||||
if (kernelCategory !== categoryFilter) return;
|
||||
}
|
||||
|
||||
const kernelCategory = getKernelCategory(kernelKey);
|
||||
let row = `<tr class="category-${kernelCategory}">`;
|
||||
row += `<td>${kernelKey}</td><td>${(kernelMeta[kernelKey]?.x_label || '?')}=${(kernelMeta[kernelKey]?.x_value || '?')}</td>`;
|
||||
if (viewType === 'commits') {
|
||||
const goldenCommit = getGoldenCommit(kernelKey);
|
||||
let refVal = allDataByCommit[goldenCommit]?.[kernelKey];
|
||||
if (refVal == null) {
|
||||
const versionedKey = Object.keys(allDataByCommit).find(k => k.startsWith(goldenCommit + '-'));
|
||||
if (versionedKey && allDataByCommit[versionedKey]?.[kernelKey] != null) {
|
||||
refVal = allDataByCommit[versionedKey][kernelKey];
|
||||
}
|
||||
}
|
||||
const refConfig = configData[goldenCommit]?.[kernelKey] || { extra_benchmark_config_str: 'N/A', gpu_name: 'N/A', liger_version: 'N/A' };
|
||||
const refTooltipText = formatConfigForTooltip(refConfig) + `\n\nCategory: ${kernelCategory}\nGolden Commit: ${goldenCommit}`;
|
||||
row += `<td title="${goldenCommit}" data-tooltip="${refTooltipText}" style="cursor: pointer;">${refVal != null ? refVal.toFixed(2) : 'N/A'}</td>`;
|
||||
}
|
||||
for (const commit of commits) {
|
||||
const val = allDataByCommit[commit]?.[kernelKey];
|
||||
let cellClass = '';
|
||||
if (viewType === 'commits') {
|
||||
const goldenCommit = getGoldenCommit(kernelKey);
|
||||
const refVal = allDataByCommit[goldenCommit]?.[kernelKey];
|
||||
const cls = compareMetric(val, refVal);
|
||||
const isGolden = commit === goldenCommit;
|
||||
cellClass = isGolden ? 'golden' : cls;
|
||||
}
|
||||
|
||||
const config = configData[commit]?.[kernelKey] || { extra_benchmark_config_str: 'N/A', gpu_name: 'N/A', liger_version: 'N/A' };
|
||||
const tooltipText = formatConfigForTooltip(config) + `\n\nCategory: ${kernelCategory}\nCommit: ${commit}`;
|
||||
row += `<td class="${cellClass}" data-tooltip="${tooltipText}" style="cursor: pointer;">${val != null ? val.toFixed(2) : 'N/A'}</td>`;
|
||||
}
|
||||
row += '</tr>';
|
||||
table.innerHTML += row;
|
||||
});
|
||||
}
|
||||
|
||||
createTable(memoryTable, 'memory');
|
||||
createTable(speedTable, 'speed');
|
||||
|
||||
addTooltipListeners();
|
||||
}
|
||||
|
||||
let tooltipEl;
|
||||
|
||||
function addTooltipListeners() {
|
||||
if (!tooltipEl) {
|
||||
tooltipEl = document.createElement('div');
|
||||
tooltipEl.id = 'custom-tooltip';
|
||||
tooltipEl.className = 'custom-tooltip';
|
||||
document.body.appendChild(tooltipEl);
|
||||
}
|
||||
|
||||
const tooltipCells = document.querySelectorAll('td[data-tooltip]');
|
||||
|
||||
tooltipCells.forEach(cell => {
|
||||
cell.addEventListener('mouseenter', showTooltip);
|
||||
cell.addEventListener('mousemove', moveTooltip);
|
||||
cell.addEventListener('mouseleave', hideTooltip);
|
||||
});
|
||||
}
|
||||
|
||||
function showTooltip(event) {
|
||||
tooltipEl.textContent = event.currentTarget.getAttribute('data-tooltip');
|
||||
tooltipEl.style.display = 'block';
|
||||
moveTooltip(event);
|
||||
}
|
||||
|
||||
function moveTooltip(event) {
|
||||
if (!tooltipEl || tooltipEl.style.display === 'none') return;
|
||||
|
||||
const viewportWidth = window.innerWidth;
|
||||
const viewportHeight = window.innerHeight;
|
||||
|
||||
let left = event.clientX + 15;
|
||||
let top = event.clientY + 15;
|
||||
|
||||
const tooltipWidth = tooltipEl.offsetWidth;
|
||||
const tooltipHeight = tooltipEl.offsetHeight;
|
||||
|
||||
if (left + tooltipWidth > viewportWidth) {
|
||||
left = event.clientX - tooltipWidth - 15;
|
||||
}
|
||||
|
||||
if (top + tooltipHeight > viewportHeight) {
|
||||
top = event.clientY - tooltipHeight - 15;
|
||||
}
|
||||
|
||||
if (left < 0) {
|
||||
left = 5;
|
||||
}
|
||||
|
||||
if (top < 0) {
|
||||
top = 5;
|
||||
}
|
||||
|
||||
tooltipEl.style.left = `${left}px`;
|
||||
tooltipEl.style.top = `${top}px`;
|
||||
}
|
||||
|
||||
function hideTooltip() {
|
||||
if (tooltipEl) {
|
||||
tooltipEl.style.display = 'none';
|
||||
}
|
||||
}
|
||||
|
||||
window.onload = loadData;
|
||||
@@ -1,252 +0,0 @@
|
||||
:root {
|
||||
--primary-color: #4CAF50;
|
||||
--danger-color: #f44336;
|
||||
--success-color: #4caf50;
|
||||
--font-color: #333;
|
||||
--bg-color: #ffffff;
|
||||
--secondary-color: #f2f2f2;
|
||||
}
|
||||
|
||||
[data-theme="dark"] {
|
||||
--primary-color: #4CAF50;
|
||||
--danger-color: #e57373;
|
||||
--success-color: #81c784;
|
||||
--font-color: #f1f1f1;
|
||||
--bg-color: #1e1e1e;
|
||||
--secondary-color: #2c2c2c;
|
||||
}
|
||||
|
||||
[data-theme="dark"] td.golden {
|
||||
background-color: #3a3a1a;
|
||||
color: #ffc107;
|
||||
border-color: #b8860b;
|
||||
}
|
||||
|
||||
body {
|
||||
font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
|
||||
margin: 0;
|
||||
padding: 20px;
|
||||
background-color: var(--bg-color);
|
||||
color: var(--font-color);
|
||||
text-align: center;
|
||||
transition: background-color 0.3s, color 0.3s;
|
||||
}
|
||||
|
||||
.container {
|
||||
display: inline-block;
|
||||
text-align: left;
|
||||
max-width: 95%;
|
||||
background-color: var(--bg-color);
|
||||
padding: 20px;
|
||||
border-radius: 12px;
|
||||
box-shadow: 0 0 15px rgba(0, 0, 0, 0.1);
|
||||
transition: background-color 0.3s;
|
||||
}
|
||||
|
||||
h1, h2 {
|
||||
color: var(--primary-color);
|
||||
}
|
||||
|
||||
table {
|
||||
border-collapse: collapse;
|
||||
width: 100%;
|
||||
margin-top: 10px;
|
||||
background-color: var(--bg-color);
|
||||
border-radius: 8px;
|
||||
overflow: hidden;
|
||||
}
|
||||
|
||||
th, td {
|
||||
border: 1px solid #ccc;
|
||||
padding: 12px 8px;
|
||||
text-align: center;
|
||||
}
|
||||
|
||||
th {
|
||||
background-color: var(--secondary-color);
|
||||
position: sticky;
|
||||
top: 0;
|
||||
z-index: 2;
|
||||
}
|
||||
|
||||
td.green {
|
||||
background-color: #d4edda;
|
||||
color: #155724;
|
||||
}
|
||||
|
||||
td.red {
|
||||
background-color: #f8d7da;
|
||||
color: #721c24;
|
||||
}
|
||||
|
||||
td.golden {
|
||||
background-color: #fff3cd;
|
||||
color: #856404;
|
||||
font-weight: bold;
|
||||
border: 2px solid #ffc107;
|
||||
}
|
||||
|
||||
/* Tooltip styles */
|
||||
tr[data-tooltip]:hover {
|
||||
background-color: rgba(76, 175, 80, 0.1) !important;
|
||||
}
|
||||
|
||||
.custom-tooltip {
|
||||
position: fixed;
|
||||
display: none;
|
||||
background-color: #333;
|
||||
color: white;
|
||||
padding: 8px 12px;
|
||||
border-radius: 6px;
|
||||
font-size: 12px;
|
||||
white-space: pre-line;
|
||||
z-index: 10001;
|
||||
max-width: 300px;
|
||||
box-shadow: 0 4px 8px rgba(0, 0, 0, 0.3);
|
||||
pointer-events: none;
|
||||
}
|
||||
|
||||
.selectors {
|
||||
margin-bottom: 20px;
|
||||
text-align: center;
|
||||
}
|
||||
|
||||
.selectors label {
|
||||
margin: 0 10px;
|
||||
}
|
||||
|
||||
#kernelSearch {
|
||||
padding: 8px;
|
||||
margin: 10px 0;
|
||||
width: 300px;
|
||||
font-size: 16px;
|
||||
border-radius: 5px;
|
||||
border: 1px solid #ccc;
|
||||
}
|
||||
|
||||
button {
|
||||
padding: 8px 16px;
|
||||
background-color: var(--primary-color);
|
||||
color: #fff;
|
||||
border: none;
|
||||
border-radius: 5px;
|
||||
cursor: pointer;
|
||||
font-weight: bold;
|
||||
}
|
||||
|
||||
button:hover {
|
||||
background-color: #388e3c;
|
||||
}
|
||||
|
||||
.scroll-container {
|
||||
overflow-x: auto;
|
||||
margin-bottom: 40px;
|
||||
}
|
||||
|
||||
.theme-toggle {
|
||||
float: right;
|
||||
margin-bottom: 20px;
|
||||
cursor: pointer;
|
||||
font-weight: bold;
|
||||
background: none;
|
||||
border: none;
|
||||
color: var(--font-color);
|
||||
font-size: 20px;
|
||||
padding: 8px;
|
||||
border-radius: 50%;
|
||||
transition: background-color 0.3s;
|
||||
}
|
||||
|
||||
.theme-toggle:hover {
|
||||
background-color: var(--secondary-color);
|
||||
}
|
||||
|
||||
/* Category-based row styling */
|
||||
.category-pretraining {
|
||||
border-left: 4px solid #2196F3;
|
||||
}
|
||||
|
||||
.category-distillation {
|
||||
border-left: 4px solid #FF9800;
|
||||
}
|
||||
|
||||
.category-post_training {
|
||||
border-left: 4px solid #9C27B0;
|
||||
}
|
||||
|
||||
.category-other {
|
||||
border-left: 4px solid #607D8B;
|
||||
}
|
||||
|
||||
/* Category filter styling */
|
||||
#categoryFilter {
|
||||
padding: 8px;
|
||||
border-radius: 5px;
|
||||
border: 1px solid #ccc;
|
||||
background-color: var(--bg-color);
|
||||
color: var(--font-color);
|
||||
}
|
||||
|
||||
#viewType {
|
||||
padding: 8px;
|
||||
border-radius: 5px;
|
||||
border: 1px solid #ccc;
|
||||
background-color: var(--bg-color);
|
||||
color: var(--font-color);
|
||||
margin-left: 10px;
|
||||
}
|
||||
|
||||
|
||||
/* Legend styling */
|
||||
.legend {
|
||||
margin: 20px 0;
|
||||
text-align: center;
|
||||
}
|
||||
|
||||
.legend h3 {
|
||||
margin-bottom: 10px;
|
||||
color: var(--font-color);
|
||||
font-size: 16px;
|
||||
}
|
||||
|
||||
.legend-items {
|
||||
display: flex;
|
||||
justify-content: center;
|
||||
flex-wrap: wrap;
|
||||
gap: 20px;
|
||||
}
|
||||
|
||||
.legend-item {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
gap: 8px;
|
||||
}
|
||||
|
||||
.legend-color {
|
||||
width: 20px;
|
||||
height: 20px;
|
||||
border-radius: 3px;
|
||||
border: 1px solid #ddd;
|
||||
}
|
||||
|
||||
.legend-color.pretraining {
|
||||
background-color: #2196F3;
|
||||
}
|
||||
|
||||
.legend-color.distillation {
|
||||
background-color: #FF9800;
|
||||
}
|
||||
|
||||
.legend-color.post_training {
|
||||
background-color: #9C27B0;
|
||||
}
|
||||
|
||||
.legend-color.other {
|
||||
background-color: #607D8B;
|
||||
}
|
||||
|
||||
.legend-label {
|
||||
font-size: 14px;
|
||||
font-weight: 500;
|
||||
color: var(--font-color);
|
||||
}
|
||||
File diff suppressed because one or more lines are too long
+8
-8
@@ -2,34 +2,34 @@
|
||||
<urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">
|
||||
<url>
|
||||
<loc>https://linkedin.github.io/Liger-Kernel/</loc>
|
||||
<lastmod>2026-08-27</lastmod>
|
||||
<lastmod>2026-09-14</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://linkedin.github.io/Liger-Kernel/Examples/</loc>
|
||||
<lastmod>2026-08-27</lastmod>
|
||||
<lastmod>2026-09-14</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://linkedin.github.io/Liger-Kernel/Getting-Started/</loc>
|
||||
<lastmod>2026-08-27</lastmod>
|
||||
<lastmod>2026-09-14</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://linkedin.github.io/Liger-Kernel/High-Level-APIs/</loc>
|
||||
<lastmod>2026-08-27</lastmod>
|
||||
<lastmod>2026-09-14</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://linkedin.github.io/Liger-Kernel/Low-Level-APIs/</loc>
|
||||
<lastmod>2026-08-27</lastmod>
|
||||
<lastmod>2026-09-14</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://linkedin.github.io/Liger-Kernel/acknowledgement/</loc>
|
||||
<lastmod>2026-08-27</lastmod>
|
||||
<lastmod>2026-09-14</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://linkedin.github.io/Liger-Kernel/contributing/</loc>
|
||||
<lastmod>2026-08-27</lastmod>
|
||||
<lastmod>2026-09-14</lastmod>
|
||||
</url>
|
||||
<url>
|
||||
<loc>https://linkedin.github.io/Liger-Kernel/license/</loc>
|
||||
<lastmod>2026-08-27</lastmod>
|
||||
<lastmod>2026-09-14</lastmod>
|
||||
</url>
|
||||
</urlset>
|
||||
Binary file not shown.
Reference in New Issue
Block a user