epyc last

AMD EPYC 7343 16-Core testing with a Supermicro H12SSL-i v1.02 (2.4 BIOS) and astdrmfb on AlmaLinux 9.1 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 2304307-NE-EPYCLAST283
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Database Test Suite 2 Tests
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  Test
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a
April 30 2023
  7 Hours, 46 Minutes
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April 30 2023
  2 Hours, 34 Minutes
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April 30 2023
  2 Hours, 34 Minutes
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April 30 2023
  2 Hours, 34 Minutes
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epyc last Suite 1.0.0 System Test suite extracted from epyc last. pts/svt-av1-2.8.0 --preset 4 -n 160 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Encoder Mode: Preset 4 - Input: Bosphorus 4K pts/svt-av1-2.8.0 --preset 8 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Encoder Mode: Preset 8 - Input: Bosphorus 4K pts/svt-av1-2.8.0 --preset 12 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Encoder Mode: Preset 12 - Input: Bosphorus 4K pts/svt-av1-2.8.0 --preset 13 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Encoder Mode: Preset 13 - Input: Bosphorus 4K pts/svt-av1-2.8.0 --preset 4 -n 160 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Encoder Mode: Preset 4 - Input: Bosphorus 1080p pts/svt-av1-2.8.0 --preset 8 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Encoder Mode: Preset 8 - Input: Bosphorus 1080p pts/svt-av1-2.8.0 --preset 12 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Encoder Mode: Preset 12 - Input: Bosphorus 1080p pts/svt-av1-2.8.0 --preset 13 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Encoder Mode: Preset 13 - Input: Bosphorus 1080p pts/intel-tensorflow-1.0.0 resnet50_fp32_pretrained_model.pb 1 Model: resnet50_fp32_pretrained_model - Batch Size: 1 pts/intel-tensorflow-1.0.0 resnet50_int8_pretrained_model.pb 1 Model: resnet50_int8_pretrained_model - Batch Size: 1 pts/intel-tensorflow-1.0.0 resnet50_fp32_pretrained_model.pb 16 Model: resnet50_fp32_pretrained_model - Batch Size: 16 pts/intel-tensorflow-1.0.0 resnet50_fp32_pretrained_model.pb 32 Model: resnet50_fp32_pretrained_model - Batch Size: 32 pts/intel-tensorflow-1.0.0 resnet50_fp32_pretrained_model.pb 64 Model: resnet50_fp32_pretrained_model - Batch Size: 64 pts/intel-tensorflow-1.0.0 resnet50_fp32_pretrained_model.pb 96 Model: resnet50_fp32_pretrained_model - Batch Size: 96 pts/intel-tensorflow-1.0.0 resnet50_int8_pretrained_model.pb 16 Model: resnet50_int8_pretrained_model - Batch Size: 16 pts/intel-tensorflow-1.0.0 resnet50_int8_pretrained_model.pb 32 Model: resnet50_int8_pretrained_model - Batch Size: 32 pts/intel-tensorflow-1.0.0 resnet50_int8_pretrained_model.pb 64 Model: resnet50_int8_pretrained_model - Batch Size: 64 pts/intel-tensorflow-1.0.0 resnet50_int8_pretrained_model.pb 96 Model: resnet50_int8_pretrained_model - Batch Size: 96 pts/intel-tensorflow-1.0.0 resnet50_fp32_pretrained_model.pb 256 Model: resnet50_fp32_pretrained_model - Batch Size: 256 pts/intel-tensorflow-1.0.0 resnet50_fp32_pretrained_model.pb 512 Model: resnet50_fp32_pretrained_model - Batch Size: 512 pts/intel-tensorflow-1.0.0 resnet50_fp32_pretrained_model.pb 960 Model: resnet50_fp32_pretrained_model - Batch Size: 960 pts/intel-tensorflow-1.0.0 resnet50_int8_pretrained_model.pb 256 Model: resnet50_int8_pretrained_model - Batch Size: 256 pts/intel-tensorflow-1.0.0 resnet50_int8_pretrained_model.pb 512 Model: resnet50_int8_pretrained_model - Batch Size: 512 pts/intel-tensorflow-1.0.0 resnet50_int8_pretrained_model.pb 960 Model: resnet50_int8_pretrained_model - Batch Size: 960 pts/intel-tensorflow-1.0.0 inceptionv4_fp32_pretrained_model.pb 1 Model: inceptionv4_fp32_pretrained_model - Batch Size: 1 pts/intel-tensorflow-1.0.0 inceptionv4_int8_pretrained_model.pb 1 Model: inceptionv4_int8_pretrained_model - Batch Size: 1 pts/intel-tensorflow-1.0.0 mobilenetv1_fp32_pretrained_model.pb 1 Model: mobilenetv1_fp32_pretrained_model - Batch Size: 1 pts/intel-tensorflow-1.0.0 mobilenetv1_int8_pretrained_model.pb 1 Model: mobilenetv1_int8_pretrained_model - Batch Size: 1 pts/intel-tensorflow-1.0.0 inceptionv4_fp32_pretrained_model.pb 16 Model: inceptionv4_fp32_pretrained_model - Batch Size: 16 pts/intel-tensorflow-1.0.0 inceptionv4_fp32_pretrained_model.pb 32 Model: inceptionv4_fp32_pretrained_model - Batch Size: 32 pts/intel-tensorflow-1.0.0 inceptionv4_fp32_pretrained_model.pb 64 Model: inceptionv4_fp32_pretrained_model - Batch Size: 64 pts/intel-tensorflow-1.0.0 inceptionv4_fp32_pretrained_model.pb 96 Model: inceptionv4_fp32_pretrained_model - Batch Size: 96 pts/intel-tensorflow-1.0.0 inceptionv4_int8_pretrained_model.pb 16 Model: inceptionv4_int8_pretrained_model - Batch Size: 16 pts/intel-tensorflow-1.0.0 inceptionv4_int8_pretrained_model.pb 32 Model: inceptionv4_int8_pretrained_model - Batch Size: 32 pts/intel-tensorflow-1.0.0 inceptionv4_int8_pretrained_model.pb 64 Model: inceptionv4_int8_pretrained_model - Batch Size: 64 pts/intel-tensorflow-1.0.0 inceptionv4_int8_pretrained_model.pb 96 Model: inceptionv4_int8_pretrained_model - Batch Size: 96 pts/intel-tensorflow-1.0.0 mobilenetv1_fp32_pretrained_model.pb 16 Model: mobilenetv1_fp32_pretrained_model - Batch Size: 16 pts/intel-tensorflow-1.0.0 mobilenetv1_fp32_pretrained_model.pb 32 Model: mobilenetv1_fp32_pretrained_model - Batch Size: 32 pts/intel-tensorflow-1.0.0 mobilenetv1_fp32_pretrained_model.pb 64 Model: mobilenetv1_fp32_pretrained_model - Batch Size: 64 pts/intel-tensorflow-1.0.0 mobilenetv1_fp32_pretrained_model.pb 96 Model: mobilenetv1_fp32_pretrained_model - Batch Size: 96 pts/intel-tensorflow-1.0.0 mobilenetv1_int8_pretrained_model.pb 16 Model: mobilenetv1_int8_pretrained_model - Batch Size: 16 pts/intel-tensorflow-1.0.0 mobilenetv1_int8_pretrained_model.pb 32 Model: mobilenetv1_int8_pretrained_model - Batch Size: 32 pts/intel-tensorflow-1.0.0 mobilenetv1_int8_pretrained_model.pb 64 Model: mobilenetv1_int8_pretrained_model - Batch Size: 64 pts/intel-tensorflow-1.0.0 mobilenetv1_int8_pretrained_model.pb 96 Model: mobilenetv1_int8_pretrained_model - Batch Size: 96 pts/intel-tensorflow-1.0.0 inceptionv4_fp32_pretrained_model.pb 256 Model: inceptionv4_fp32_pretrained_model - Batch Size: 256 pts/intel-tensorflow-1.0.0 inceptionv4_fp32_pretrained_model.pb 512 Model: inceptionv4_fp32_pretrained_model - Batch Size: 512 pts/intel-tensorflow-1.0.0 inceptionv4_fp32_pretrained_model.pb 960 Model: inceptionv4_fp32_pretrained_model - Batch Size: 960 pts/intel-tensorflow-1.0.0 inceptionv4_int8_pretrained_model.pb 256 Model: inceptionv4_int8_pretrained_model - Batch Size: 256 pts/intel-tensorflow-1.0.0 inceptionv4_int8_pretrained_model.pb 512 Model: inceptionv4_int8_pretrained_model - Batch Size: 512 pts/intel-tensorflow-1.0.0 inceptionv4_int8_pretrained_model.pb 960 Model: inceptionv4_int8_pretrained_model - Batch Size: 960 pts/intel-tensorflow-1.0.0 mobilenetv1_fp32_pretrained_model.pb 256 Model: mobilenetv1_fp32_pretrained_model - Batch Size: 256 pts/intel-tensorflow-1.0.0 mobilenetv1_fp32_pretrained_model.pb 512 Model: mobilenetv1_fp32_pretrained_model - Batch Size: 512 pts/intel-tensorflow-1.0.0 mobilenetv1_fp32_pretrained_model.pb 960 Model: mobilenetv1_fp32_pretrained_model - Batch Size: 960 pts/intel-tensorflow-1.0.0 mobilenetv1_int8_pretrained_model.pb 256 Model: mobilenetv1_int8_pretrained_model - Batch Size: 256 pts/intel-tensorflow-1.0.0 mobilenetv1_int8_pretrained_model.pb 512 Model: mobilenetv1_int8_pretrained_model - Batch Size: 512 pts/intel-tensorflow-1.0.0 mobilenetv1_int8_pretrained_model.pb 960 Model: mobilenetv1_int8_pretrained_model - Batch Size: 960 pts/quantlib-1.1.0 pts/influxdb-1.0.2 -c 4 -b 10000 -t 2,5000,1 -p 10000 Concurrent Streams: 4 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 pts/influxdb-1.0.2 -c 64 -b 10000 -t 2,5000,1 -p 10000 Concurrent Streams: 64 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 pts/sqlite-2.2.0 1 Threads / Copies: 1 pts/sqlite-2.2.0 2 Threads / Copies: 2 pts/sqlite-2.2.0 4 Threads / Copies: 4 pts/sqlite-2.2.0 8 Threads / Copies: 8 pts/sqlite-2.2.0 16 Threads / Copies: 16 pts/sqlite-2.2.0 32 Threads / Copies: 32