smoke

ARMv8 Neoverse-V2 testing with a Quanta Cloud QuantaGrid S74G-2U 1S7GZ9Z0000 S7G MB (CG1) (3A06 BIOS) and ASPEED 96GB on Ubuntu 22.04 via the Phoronix Test Suite.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2402267-NE-SMOKE254569
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Identifier
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Date
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  Test
  Duration
ARMv8 Neoverse-V2
February 26
  3 Hours, 15 Minutes
b
February 26
  39 Minutes
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smoke Suite 1.0.0 System Test suite extracted from smoke. pts/compress-lz4-1.1.0 -b1 -e1 Compression Level: 1 - Compression Speed pts/quicksilver-1.0.0 ../Examples/CORAL2_Benchmark/Problem1/Coral2_P1.inp Input: CORAL2 P1 pts/compress-lz4-1.1.0 -b1 -e1 Compression Level: 1 - Decompression Speed pts/compress-lz4-1.1.0 -b3 -e3 Compression Level: 3 - Compression Speed pts/compress-lz4-1.1.0 -b3 -e3 Compression Level: 3 - Decompression Speed pts/compress-lz4-1.1.0 -b9 -e9 Compression Level: 9 - Compression Speed pts/compress-lz4-1.1.0 -b9 -e9 Compression Level: 9 - Decompression Speed pts/pytorch-1.0.1 cpu 1 resnet50 Device: CPU - Batch Size: 1 - Model: ResNet-50 pts/pytorch-1.0.1 cpu 1 resnet152 Device: CPU - Batch Size: 1 - Model: ResNet-152 pts/pytorch-1.0.1 cpu 16 resnet50 Device: CPU - Batch Size: 16 - Model: ResNet-50 pts/pytorch-1.0.1 cpu 16 resnet152 Device: CPU - Batch Size: 16 - Model: ResNet-152 pts/quicksilver-1.0.0 ../Examples/CORAL2_Benchmark/Problem2/Coral2_P2.inp Input: CORAL2 P2 pts/pytorch-1.0.1 cpu 32 resnet50 Device: CPU - Batch Size: 32 - Model: ResNet-50 pts/pytorch-1.0.1 cpu 32 resnet152 Device: CPU - Batch Size: 32 - Model: ResNet-152 pts/pytorch-1.0.1 cpu 512 resnet50 Device: CPU - Batch Size: 512 - Model: ResNet-50 pts/pytorch-1.0.1 cpu 512 resnet152 Device: CPU - Batch Size: 512 - Model: ResNet-152 pts/pytorch-1.0.1 cpu 1 efficientnet_v2_l Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l pts/pytorch-1.0.1 cpu 16 efficientnet_v2_l Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l pts/pytorch-1.0.1 cpu 32 efficientnet_v2_l Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l pts/pytorch-1.0.1 cpu 512 efficientnet_v2_l Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l pts/vvenc-1.11.0 -i Bosphorus_3840x2160.y4m --preset fast --tiles 2x2 --additional WaveFrontSynchro=1 Video Input: Bosphorus 4K - Video Preset: Fast pts/vvenc-1.11.0 -i Bosphorus_3840x2160.y4m --preset faster --ifp 1 --tiles 2x1 --additional WaveFrontSynchro=1 Video Input: Bosphorus 4K - Video Preset: Faster pts/vvenc-1.11.0 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m --preset fast --tiles 2x2 --additional WaveFrontSynchro=1 Video Input: Bosphorus 1080p - Video Preset: Fast pts/vvenc-1.11.0 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m --preset faster --ifp 1 --tiles 2x1 --additional WaveFrontSynchro=1 Video Input: Bosphorus 1080p - Video Preset: Faster pts/quicksilver-1.0.0 ../Examples/CTS2_Benchmark/CTS2.inp Input: CTS2