mnn ncnn zen 1 epyc

AMD EPYC 7551 32-Core testing with a GIGABYTE MZ31-AR0-00 v01010101 (F10 BIOS) and ASPEED on Debian 11 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 2208156-NE-MNNNCNNZE48
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HPC - High Performance Computing 2 Tests
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A
August 15 2022
  19 Hours, 22 Minutes
B
August 15 2022
  21 Hours, 6 Minutes
C
August 15 2022
  21 Hours, 3 Minutes
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  20 Hours, 30 Minutes

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mnn ncnn zen 1 epyc AMD EPYC 7551 32-Core testing with a GIGABYTE MZ31-AR0-00 v01010101 (F10 BIOS) and ASPEED on Debian 11 via the Phoronix Test Suite. ,,"A","B","C" Processor,,AMD EPYC 7551 32-Core @ 2.00GHz (32 Cores / 64 Threads),AMD EPYC 7551 32-Core @ 2.00GHz (32 Cores / 64 Threads),AMD EPYC 7551 32-Core @ 2.00GHz (32 Cores / 64 Threads) Motherboard,,GIGABYTE MZ31-AR0-00 v01010101 (F10 BIOS),GIGABYTE MZ31-AR0-00 v01010101 (F10 BIOS),GIGABYTE MZ31-AR0-00 v01010101 (F10 BIOS) Chipset,,AMD 17h,AMD 17h,AMD 17h Memory,,8 x 4 GB DDR4-2133MT/s 9ASF51272PZ-2G6E1,8 x 4 GB DDR4-2133MT/s 9ASF51272PZ-2G6E1,8 x 4 GB DDR4-2133MT/s 9ASF51272PZ-2G6E1 Disk,,Samsung SSD 960 EVO 500GB,Samsung SSD 960 EVO 500GB,Samsung SSD 960 EVO 500GB Graphics,,ASPEED,ASPEED,ASPEED Network,,Realtek RTL8111/8168/8411 + 2 x Broadcom NetXtreme II BCM57810 10,Realtek RTL8111/8168/8411 + 2 x Broadcom NetXtreme II BCM57810 10,Realtek RTL8111/8168/8411 + 2 x Broadcom NetXtreme II BCM57810 10 OS,,Debian 11,Debian 11,Debian 11 Kernel,,5.10.0-9-amd64 (x86_64),5.10.0-9-amd64 (x86_64),5.10.0-9-amd64 (x86_64) Compiler,,GCC 10.2.1 20210110,GCC 10.2.1 20210110,GCC 10.2.1 20210110 File-System,,ext4,ext4,ext4 Screen Resolution,,1024x768,1024x768,1024x768 ,,"A","B","C" "Mobile Neural Network - Model: mobilenetV3 (ms)",LIB,5.281,5.464,6.070 "Mobile Neural Network - Model: squeezenetv1.1 (ms)",LIB,9.157,9.009,9.516 "Mobile Neural Network - Model: resnet-v2-50 (ms)",LIB,52.380,54.152,57.826 "Mobile Neural Network - Model: SqueezeNetV1.0 (ms)",LIB,14.090,13.983,14.492 "Mobile Neural Network - Model: MobileNetV2_224 (ms)",LIB,10.048,8.595,9.898 "Mobile Neural Network - Model: mobilenet-v1-1.0 (ms)",LIB,8.341,8.119,8.783 "Mobile Neural Network - Model: inception-v3 (ms)",LIB,59.589,57.847,59.955 "NCNN - Target: CPU - Model: mobilenet (ms)",LIB,45.00,41.52,45.88 "NCNN - Target: CPU-v2-v2 - Model: mobilenet-v2 (ms)",LIB,24.04,24.63,27.05 "NCNN - Target: CPU-v3-v3 - Model: mobilenet-v3 (ms)",LIB,21.60,23.51,22.35 "NCNN - Target: CPU - Model: shufflenet-v2 (ms)",LIB,29.16,26.61,27.07 "NCNN - Target: CPU - Model: mnasnet (ms)",LIB,22.37,22.07,26.29 "NCNN - Target: CPU - Model: efficientnet-b0 (ms)",LIB,33.19,34.65,31.80 "NCNN - Target: CPU - Model: blazeface (ms)",LIB,12.28,14.47,11.38 "NCNN - Target: CPU - Model: googlenet (ms)",LIB,59.41,53.82,53.24 "NCNN - Target: CPU - Model: vgg16 (ms)",LIB,94.47,98.99,92.70 "NCNN - Target: CPU - Model: resnet18 (ms)",LIB,45.42,45.65,40.39 "NCNN - Target: CPU - Model: alexnet (ms)",LIB,41.36,40.94,42.47 "NCNN - Target: CPU - Model: resnet50 (ms)",LIB,71.34,77.61,65.41 "NCNN - Target: CPU - Model: yolov4-tiny (ms)",LIB,63.28,55.48,60.06 "NCNN - Target: CPU - Model: squeezenet_ssd (ms)",LIB,60.88,56.80,58.65 "NCNN - Target: CPU - Model: regnety_400m (ms)",LIB,103.41,96.94,100.75 "NCNN - Target: CPU - Model: vision_transformer (ms)",LIB,353.68,352.36,350.58 "NCNN - Target: CPU - Model: FastestDet (ms)",LIB,32.28,32.75,30.45