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‎benchmarks/2025-07-27/747c01564b9fd3515d28209766d1aae1034159e9/benchmarks/2025-07-27/index.html‎

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<h1>Buddy-Benchmark results</h1><ul>
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‎benchmarks/2025-07-27/747c01564b9fd3515d28209766d1aae1034159e9/deeplearning/dl-layer-ffn-benchmark.html‎

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<h2>deeplearning/dl-layer-ffn-benchmark.json</h2><p><em>2025-07-27 17:54:34 UTC</em></p>
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<h3>dl-layer-ffn-benchmark.json</h3>
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<table><tr><th>Name</th><th>Time&nbsp;(ms)</th><th>CPU&nbsp;(ms)</th><th>Iterations</th></tr>
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<tr><td style='text-align:left'>DL_LAYER_FFN/Scalar</td><td>0.0654</td><td>0.0654</td><td>10,762</td></tr>
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<tr><td style='text-align:left'>DL_LAYER_FFN/Auto_Vectorization</td><td>0.0271</td><td>0.0271</td><td>25,673</td></tr></table>
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<details><summary>Console output</summary>
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<pre>2025-07-27T14:26:49+00:00
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Running ./dl-layer-ffn-benchmark
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Run on (24 X 5100 MHz CPU s)
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CPU Caches:
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L1 Data 48 KiB (x12)
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L1 Instruction 32 KiB (x12)
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L2 Unified 1280 KiB (x12)
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L3 Unified 30720 KiB (x1)
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Load Average: 1.04, 1.19, 1.31
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***WARNING*** CPU scaling is enabled, the benchmark real time measurements may be noisy and will incur extra overhead.
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--------------------------------------------------------------------------
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Benchmark Time CPU Iterations
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--------------------------------------------------------------------------
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DL_LAYER_FFN/Scalar 0.065 ms 0.065 ms 10762
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DL_LAYER_FFN/Auto_Vectorization 0.027 ms 0.027 ms 25673
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-----------------------------------------------------------
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Correctness Verification: PASS
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-----------------------------------------------------------
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</pre></details>

‎benchmarks/2025-07-27/747c01564b9fd3515d28209766d1aae1034159e9/deeplearning/dl-layer-rmsnorm-benchmark.html‎

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<h2>deeplearning/dl-layer-rmsnorm-benchmark.json</h2><p><em>2025-07-27 17:54:34 UTC</em></p>
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<h3>dl-layer-rmsnorm-benchmark.json</h3>
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<table><tr><th>Name</th><th>Time&nbsp;(ms)</th><th>CPU&nbsp;(ms)</th><th>Iterations</th></tr>
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<tr><td style='text-align:left'>DL_LAYER_RMSNORM/Scalar</td><td>0.00196</td><td>0.00196</td><td>356,202</td></tr>
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<tr><td style='text-align:left'>DL_LAYER_RMSNORM/Auto_Vectorization</td><td>0.000915</td><td>0.000915</td><td>751,546</td></tr></table>
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<details><summary>Console output</summary>
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<pre>2025-07-27T14:26:53+00:00
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Running ./dl-layer-rmsnorm-benchmark
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Run on (24 X 5100 MHz CPU s)
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CPU Caches:
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L1 Data 48 KiB (x12)
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L1 Instruction 32 KiB (x12)
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L2 Unified 1280 KiB (x12)
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L3 Unified 30720 KiB (x1)
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Load Average: 1.03, 1.19, 1.30
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***WARNING*** CPU scaling is enabled, the benchmark real time measurements may be noisy and will incur extra overhead.
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------------------------------------------------------------------------------
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Benchmark Time CPU Iterations
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------------------------------------------------------------------------------
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DL_LAYER_RMSNORM/Scalar 0.002 ms 0.002 ms 356202
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DL_LAYER_RMSNORM/Auto_Vectorization 0.001 ms 0.001 ms 751546
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-----------------------------------------------------------
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Correctness Verification: PASS
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-----------------------------------------------------------
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</pre></details>

‎benchmarks/2025-07-27/747c01564b9fd3515d28209766d1aae1034159e9/deeplearning/dl-layer-selfattention-benchmark.html‎

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<h2>deeplearning/dl-layer-selfattention-benchmark.json</h2><p><em>2025-07-27 17:54:34 UTC</em></p>
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<h3>dl-layer-selfattention-benchmark.json</h3>
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<table><tr><th>Name</th><th>Time&nbsp;(ms)</th><th>CPU&nbsp;(ms)</th><th>Iterations</th></tr>
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<tr><td style='text-align:left'>DL_LAYER_ATTENTION/Scalar</td><td>4.69</td><td>4.69</td><td>149</td></tr>
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<tr><td style='text-align:left'>DL_LAYER_ATTENTION/Auto_Vectorization</td><td>1.57</td><td>1.57</td><td>446</td></tr></table>
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<details><summary>Console output</summary>
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<pre>2025-07-27T14:26:51+00:00
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Running ./dl-layer-selfattention-benchmark
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Run on (24 X 5100 MHz CPU s)
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CPU Caches:
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L1 Data 48 KiB (x12)
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L1 Instruction 32 KiB (x12)
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L2 Unified 1280 KiB (x12)
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L3 Unified 30720 KiB (x1)
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Load Average: 1.04, 1.19, 1.31
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***WARNING*** CPU scaling is enabled, the benchmark real time measurements may be noisy and will incur extra overhead.
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--------------------------------------------------------------------------------
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Benchmark Time CPU Iterations
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--------------------------------------------------------------------------------
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DL_LAYER_ATTENTION/Scalar 4.69 ms 4.69 ms 149
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DL_LAYER_ATTENTION/Auto_Vectorization 1.57 ms 1.57 ms 446
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-----------------------------------------------------------
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Correctness Verification: PASS
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-----------------------------------------------------------
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</pre></details>

‎benchmarks/2025-07-27/747c01564b9fd3515d28209766d1aae1034159e9/deeplearning/dl-model-lenet-benchmark.html‎

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<h2>deeplearning/dl-model-lenet-benchmark.json</h2><p><em>2025-07-27 17:54:34 UTC</em></p>
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<h3>dl-model-lenet-benchmark.json</h3>
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<table><tr><th>Name</th><th>Time&nbsp;(ms)</th><th>CPU&nbsp;(ms)</th><th>Iterations</th></tr>
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<tr><td style='text-align:left'>DL_MODEL_LENET/Auto_Vectorization</td><td>0.165</td><td>0.165</td><td>4,304</td></tr>
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<tr><td style='text-align:left'>DL_MODEL_LENET/Buddy_Vectorization</td><td>0.137</td><td>0.137</td><td>5,022</td></tr></table>
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<details><summary>Console output</summary>
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<pre>2025-07-27T14:22:52+00:00
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Running ./dl-model-lenet-benchmark
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Run on (24 X 5100 MHz CPU s)
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CPU Caches:
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L1 Data 48 KiB (x12)
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L1 Instruction 32 KiB (x12)
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L2 Unified 1280 KiB (x12)
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L3 Unified 30720 KiB (x1)
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Load Average: 1.40, 1.39, 1.40
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***WARNING*** CPU scaling is enabled, the benchmark real time measurements may be noisy and will incur extra overhead.
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-----------------------------------------------------------------------------
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Benchmark Time CPU Iterations
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-----------------------------------------------------------------------------
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DL_MODEL_LENET/Auto_Vectorization 0.165 ms 0.165 ms 4304
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DL_MODEL_LENET/Buddy_Vectorization 0.137 ms 0.137 ms 5022
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-----------------------------------------------------------
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Correctness Verification:
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Transform case: FAIL
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-----------------------------------------------------------
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</pre></details>

‎benchmarks/2025-07-27/747c01564b9fd3515d28209766d1aae1034159e9/deeplearning/dl-model-mobilenetv3-benchmark.html‎

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<h2>deeplearning/dl-model-mobilenetv3-benchmark.json</h2><p><em>2025-07-27 17:54:34 UTC</em></p>
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<h3>dl-model-mobilenetv3-benchmark.json</h3>
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<table><tr><th>Name</th><th>Time&nbsp;(ms)</th><th>CPU&nbsp;(ms)</th><th>Iterations</th></tr>
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<tr><td style='text-align:left'>BM_MobileNet_V3/BM_MobileNet_V3_scalar</td><td>37.1</td><td>37.1</td><td>19</td></tr>
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<tr><td style='text-align:left'>BM_MobileNet_V3/BM_MobileNet_V3_conv_opt</td><td>33</td><td>33</td><td>21</td></tr></table>
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<details><summary>Console output</summary>
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<pre>2025-07-27T14:22:49+00:00
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Running ./dl-model-mobilenetv3-benchmark
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Run on (24 X 5100 MHz CPU s)
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CPU Caches:
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L1 Data 48 KiB (x12)
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L1 Instruction 32 KiB (x12)
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L2 Unified 1280 KiB (x12)
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L3 Unified 30720 KiB (x1)
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Load Average: 1.40, 1.39, 1.40
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***WARNING*** CPU scaling is enabled, the benchmark real time measurements may be noisy and will incur extra overhead.
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-----------------------------------------------------------------------------------
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Benchmark Time CPU Iterations
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-----------------------------------------------------------------------------------
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BM_MobileNet_V3/BM_MobileNet_V3_scalar 37.1 ms 37.1 ms 19
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BM_MobileNet_V3/BM_MobileNet_V3_conv_opt 33.0 ms 33.0 ms 21
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-----------------------------------------------------------
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Correctness Verification:
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Transform case: PASS
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-----------------------------------------------------------
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</pre></details>

‎benchmarks/2025-07-27/747c01564b9fd3515d28209766d1aae1034159e9/deeplearning/dl-model-resnet18-benchmark.html‎

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<h2>deeplearning/dl-model-resnet18-benchmark.json</h2><p><em>2025-07-27 17:54:34 UTC</em></p>
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<h3>dl-model-resnet18-benchmark.json</h3>
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<table><tr><th>Name</th><th>Time&nbsp;(ms)</th><th>CPU&nbsp;(ms)</th><th>Iterations</th></tr>
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<tr><td style='text-align:left'>DL_MODEL_Resnet18/Auto_Vectorization</td><td>731</td><td>723</td><td>1</td></tr>
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<tr><td style='text-align:left'>DL_MODEL_Resnet18/Buddy_Vectorization</td><td>729</td><td>722</td><td>1</td></tr></table>
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<details><summary>Console output</summary>
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<pre>2025-07-27T14:26:46+00:00
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Running ./dl-model-resnet18-benchmark
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Run on (24 X 5100 MHz CPU s)
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CPU Caches:
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L1 Data 48 KiB (x12)
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L1 Instruction 32 KiB (x12)
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L2 Unified 1280 KiB (x12)
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L3 Unified 30720 KiB (x1)
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Load Average: 1.04, 1.19, 1.31
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***WARNING*** CPU scaling is enabled, the benchmark real time measurements may be noisy and will incur extra overhead.
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--------------------------------------------------------------------------------
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Benchmark Time CPU Iterations
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--------------------------------------------------------------------------------
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DL_MODEL_Resnet18/Auto_Vectorization 731 ms 723 ms 1
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DL_MODEL_Resnet18/Buddy_Vectorization 729 ms 722 ms 1
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-----------------------------------------------------------
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Correctness Verification: PASS
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-----------------------------------------------------------
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</pre></details>

‎benchmarks/2025-07-27/747c01564b9fd3515d28209766d1aae1034159e9/deeplearning/dl-model-tinyllama-benchmark.html‎

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<h2>deeplearning/dl-model-tinyllama-benchmark.json</h2><p><em>2025-07-27 17:54:34 UTC</em></p>
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<h3>dl-model-tinyllama-benchmark.json</h3>
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<table><tr><th>Name</th><th>Time&nbsp;(ms)</th><th>CPU&nbsp;(ms)</th><th>Iterations</th></tr>
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<tr><td style='text-align:left'>DL_MODEL_TINYLLAMA/scalar</td><td>1.39e+05</td><td>1.39e+05</td><td>1</td></tr>
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<tr><td style='text-align:left'>DL_MODEL_TINYLLAMA/matmul_opt</td><td>1e+04</td><td>1e+04</td><td>1</td></tr>
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<tr><td style='text-align:left'>DL_MODEL_TINYLLAMA/matmul_opt_omp</td><td>7.84e+03</td><td>7.2e+03</td><td>1</td></tr></table>
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<details><summary>Console output</summary>
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<pre>2025-07-27T14:17:33+00:00
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Running ./dl-model-tinyllama-benchmark
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Run on (24 X 5100 MHz CPU s)
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CPU Caches:
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L1 Data 48 KiB (x12)
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L1 Instruction 32 KiB (x12)
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L2 Unified 1280 KiB (x12)
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L3 Unified 30720 KiB (x1)
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Load Average: 1.70, 1.92, 1.54
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***WARNING*** CPU scaling is enabled, the benchmark real time measurements may be noisy and will incur extra overhead.
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----------------------------------------------------------------------------
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Benchmark Time CPU Iterations
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----------------------------------------------------------------------------
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DL_MODEL_TINYLLAMA/scalar 139185 ms 139179 ms 1
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DL_MODEL_TINYLLAMA/matmul_opt 10038 ms 10038 ms 1
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DL_MODEL_TINYLLAMA/matmul_opt_omp 7836 ms 7201 ms 1
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---------- Verification ----------
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matmul_opt PASS
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matmul_opt_omp PASS
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</pre></details>

‎benchmarks/2025-07-27/747c01564b9fd3515d28209766d1aae1034159e9/deeplearning/dl-model-whisper-benchmark.html‎

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<h2>deeplearning/dl-model-whisper-benchmark.json</h2><p><em>2025-07-27 17:54:34 UTC</em></p>
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<h3>dl-model-whisper-benchmark.json</h3>
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<table><tr><th>Name</th><th>Time&nbsp;(ms)</th><th>CPU&nbsp;(ms)</th><th>Iterations</th></tr>
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<tr><td style='text-align:left'>DL_MODEL_Whisper/Auto_Vectorization</td><td>8e+04</td><td>8e+04</td><td>1</td></tr>
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<tr><td style='text-align:left'>DL_MODEL_Whisper/Buddy_Vectorization</td><td>3.67e+04</td><td>3.67e+04</td><td>1</td></tr></table>
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<details><summary>Console output</summary>
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<pre>2025-07-27T14:22:54+00:00
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Running ./dl-model-whisper-benchmark
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Run on (24 X 5100 MHz CPU s)
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CPU Caches:
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L1 Data 48 KiB (x12)
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L1 Instruction 32 KiB (x12)
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L2 Unified 1280 KiB (x12)
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L3 Unified 30720 KiB (x1)
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Load Average: 1.45, 1.40, 1.40
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***WARNING*** CPU scaling is enabled, the benchmark real time measurements may be noisy and will incur extra overhead.
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-------------------------------------------------------------------------------
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Benchmark Time CPU Iterations
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-------------------------------------------------------------------------------
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DL_MODEL_Whisper/Auto_Vectorization 79983 ms 79980 ms 1
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DL_MODEL_Whisper/Buddy_Vectorization 36713 ms 36700 ms 1
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-----------------------------------------------------------
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Correctness Verification for Output1: PASS
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Correctness Verification for Output2: FAIL
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-----------------------------------------------------------
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</pre></details>

‎benchmarks/2025-07-27/747c01564b9fd3515d28209766d1aae1034159e9/deeplearning/dl-op-linalg-arithaddf-benchmark.html‎

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<h2>deeplearning/dl-op-linalg-arithaddf-benchmark.json</h2><p><em>2025-07-27 17:54:34 UTC</em></p>
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<h3>dl-op-linalg-arithaddf-benchmark.json</h3>
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<table><tr><th>Name</th><th>Time&nbsp;(ms)</th><th>CPU&nbsp;(ms)</th><th>Iterations</th></tr>
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<tr><td style='text-align:left'>BM_ADDF_SCALAR</td><td>0.0295</td><td>0.0295</td><td>23,451</td></tr>
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<tr><td style='text-align:left'>BM_ADDF_AutoVectorization</td><td>0.004</td><td>0.004</td><td>174,931</td></tr></table>
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<details><summary>Console output</summary>
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<pre>2025-07-27T14:27:23+00:00
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Running ./dl-op-linalg-arithaddf-benchmark
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Run on (24 X 5100 MHz CPU s)
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CPU Caches:
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L1 Data 48 KiB (x12)
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L1 Instruction 32 KiB (x12)
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L2 Unified 1280 KiB (x12)
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L3 Unified 30720 KiB (x1)
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Load Average: 1.07, 1.18, 1.30
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***WARNING*** CPU scaling is enabled, the benchmark real time measurements may be noisy and will incur extra overhead.
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--------------------------------------------------------------------
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Benchmark Time CPU Iterations
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--------------------------------------------------------------------
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BM_ADDF_SCALAR 0.030 ms 0.030 ms 23451
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BM_ADDF_AutoVectorization 0.004 ms 0.004 ms 174931
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-----------------------------------------------------------
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Correctness Verification:
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Transform case: PASS
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-----------------------------------------------------------
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</pre></details>

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