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 epyc last - Phoronix Test Suite 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.
HTML result view exported from: https://openbenchmarking.org/result/2304307-NE-EPYCLAST283&grt&sor .
epyc last Processor Motherboard Memory Disk Graphics Monitor OS Kernel Compiler File-System Screen Resolution a b c d AMD EPYC 7343 16-Core @ 3.20GHz (16 Cores / 32 Threads) Supermicro H12SSL-i v1.02 (2.4 BIOS) 8 x 64 GB DDR4-3200MT/s Samsung M393A8G40AB2-CWE 2 x 1920GB SAMSUNG MZQL21T9HCJR-00A07 astdrmfb DELL E207WFP AlmaLinux 9.1 5.14.0-162.12.1.el9_1.x86_64 (x86_64) GCC 11.3.1 20220421 ext4 1680x1050 OpenBenchmarking.org Kernel Details - Transparent Huge Pages: always Compiler Details - --build=x86_64-redhat-linux --disable-libunwind-exceptions --enable-__cxa_atexit --enable-bootstrap --enable-cet --enable-checking=release --enable-gnu-indirect-function --enable-gnu-unique-object --enable-host-bind-now --enable-host-pie --enable-initfini-array --enable-languages=c,c++,fortran,lto --enable-link-serialization=1 --enable-multilib --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --mandir=/usr/share/man --with-arch_32=x86-64 --with-arch_64=x86-64-v2 --with-build-config=bootstrap-lto --with-gcc-major-version-only --with-linker-hash-style=gnu --with-tune=generic --without-cuda-driver --without-isl Disk Details - NONE / relatime,rw,stripe=32 / raid1 nvme1n1p3[0] nvme0n1p3[1] Block Size: 4096 Processor Details - Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa001173 Python Details - Python 3.9.14 Security Details - itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional IBRS_FW STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected
epyc last influxdb: 4 - 10000 - 2,5000,1 - 10000 influxdb: 64 - 10000 - 2,5000,1 - 10000 intel-tensorflow: resnet50_fp32_pretrained_model - 1 intel-tensorflow: resnet50_fp32_pretrained_model - 1 intel-tensorflow: resnet50_int8_pretrained_model - 1 intel-tensorflow: resnet50_int8_pretrained_model - 1 intel-tensorflow: resnet50_fp32_pretrained_model - 16 intel-tensorflow: resnet50_fp32_pretrained_model - 32 intel-tensorflow: resnet50_fp32_pretrained_model - 64 intel-tensorflow: resnet50_fp32_pretrained_model - 96 intel-tensorflow: resnet50_int8_pretrained_model - 16 intel-tensorflow: resnet50_int8_pretrained_model - 32 intel-tensorflow: resnet50_int8_pretrained_model - 64 intel-tensorflow: resnet50_int8_pretrained_model - 96 intel-tensorflow: resnet50_fp32_pretrained_model - 256 intel-tensorflow: resnet50_fp32_pretrained_model - 512 intel-tensorflow: resnet50_fp32_pretrained_model - 960 intel-tensorflow: resnet50_int8_pretrained_model - 256 intel-tensorflow: resnet50_int8_pretrained_model - 512 intel-tensorflow: resnet50_int8_pretrained_model - 960 intel-tensorflow: inceptionv4_fp32_pretrained_model - 1 intel-tensorflow: inceptionv4_fp32_pretrained_model - 1 intel-tensorflow: inceptionv4_int8_pretrained_model - 1 intel-tensorflow: inceptionv4_int8_pretrained_model - 1 intel-tensorflow: mobilenetv1_fp32_pretrained_model - 1 intel-tensorflow: mobilenetv1_int8_pretrained_model - 1 intel-tensorflow: inceptionv4_fp32_pretrained_model - 16 intel-tensorflow: inceptionv4_fp32_pretrained_model - 32 intel-tensorflow: inceptionv4_fp32_pretrained_model - 64 intel-tensorflow: inceptionv4_fp32_pretrained_model - 96 intel-tensorflow: inceptionv4_int8_pretrained_model - 16 intel-tensorflow: inceptionv4_int8_pretrained_model - 32 intel-tensorflow: inceptionv4_int8_pretrained_model - 64 intel-tensorflow: inceptionv4_int8_pretrained_model - 96 intel-tensorflow: mobilenetv1_fp32_pretrained_model - 16 intel-tensorflow: mobilenetv1_fp32_pretrained_model - 32 intel-tensorflow: mobilenetv1_fp32_pretrained_model - 64 intel-tensorflow: mobilenetv1_fp32_pretrained_model - 96 intel-tensorflow: mobilenetv1_int8_pretrained_model - 16 intel-tensorflow: mobilenetv1_int8_pretrained_model - 32 intel-tensorflow: mobilenetv1_int8_pretrained_model - 64 intel-tensorflow: mobilenetv1_int8_pretrained_model - 96 intel-tensorflow: inceptionv4_fp32_pretrained_model - 256 intel-tensorflow: inceptionv4_fp32_pretrained_model - 512 intel-tensorflow: inceptionv4_fp32_pretrained_model - 960 intel-tensorflow: inceptionv4_int8_pretrained_model - 256 intel-tensorflow: inceptionv4_int8_pretrained_model - 512 intel-tensorflow: inceptionv4_int8_pretrained_model - 960 intel-tensorflow: mobilenetv1_fp32_pretrained_model - 256 intel-tensorflow: mobilenetv1_fp32_pretrained_model - 512 intel-tensorflow: mobilenetv1_fp32_pretrained_model - 960 intel-tensorflow: mobilenetv1_int8_pretrained_model - 256 intel-tensorflow: mobilenetv1_int8_pretrained_model - 512 intel-tensorflow: mobilenetv1_int8_pretrained_model - 960 quantlib: sqlite: 2 sqlite: 4 sqlite: 8 sqlite: 16 sqlite: 32 svt-av1: Preset 4 - Bosphorus 4K svt-av1: Preset 8 - Bosphorus 4K svt-av1: Preset 12 - Bosphorus 4K svt-av1: Preset 13 - Bosphorus 4K svt-av1: Preset 4 - Bosphorus 1080p svt-av1: Preset 8 - Bosphorus 1080p svt-av1: Preset 12 - Bosphorus 1080p svt-av1: Preset 13 - Bosphorus 1080p a b c d 1547894.4 1602099.9 79.283 12.613 221.855 4.508 168.744 174.040 170.509 169.726 346.017 356.317 365.095 373.126 167.968 168.371 168.721 382.093 383.615 391.680 32.23 30.817 69.04 14.436 1045.59 1933.37 53.20 53.10 52.44 51.83 113.31 117.00 118.48 118.25 932.19 981.32 998.43 990.35 2003.49 2056.18 2112.33 2083.55 51.92 51.76 51.76 119.18 119.90 120.74 1001.61 976.58 983.76 2090.97 2170.09 2133.18 3202.1 2.150 3.178 5.065 8.476 11.321 3.766 52.582 174.519 160.501 9.027 95.925 547.498 548.007 1545780.8 1593776.4 79.776 12.535 221.769 4.509 171.632 174.303 170.516 169.649 347.926 361.362 364.043 373.723 167.998 168.641 169.729 380.652 385.546 392.07 33.16 30.475 69.16 14.415 1048.2 1932.47 53.47 52.91 52.40 51.72 111.63 117.81 118.93 119.097759734 929.58 984.41 997.73 986.72 2002.09 2110.19 2120.77 2081.87 52.07 51.87 51.78 119.18 119.61 120.94 1000.28 974.84 982.71 2106.54 2179.09 2128.1 3206.1 2.041 2.938 3.856 6.209 11.811 3.782 51.982 175.683 160.664 9.064 95.707 542.028 542.625 1552035.6 1599391.9 79.988 12.502 216.369 4.622 171.049 174.255 170.603 169.971 348.365 357.714 365.003 372.933 168.055 168.788 170.093 381.064 385.5 392.383 32.06 30.647 69.01 14.426 1046.79 1933.58 52.99 53.11 51.72 51.90 113.63 116.93 117.61 119.82 933.76 982.66 999.93 988.15 1989 2037.86 2063.78 2087.39 52.06 51.77 51.59 119.33 119.91 120.74 1001.43 976.22 982.46 2028.82 2161.98 2137.2 3200.7 2.106 2.904 3.966 7.198 11.743 3.791 52.523 172.696 160.139 9.121 96.329 535.678 545.864 1560758 1600346.9 80.218 12.466 217.593 4.596 169.333 172.269 170.261 169.31 344.868 357.035 365.305 372.928 168.16 168.365 169.338 380.015 384.26 391.383 31.86 30.723 69.07 14.377 1046.4 1934.32 53.22 53.27 51.97 52.00 113.36 117.89 119.83 118.23 931.22 981.61 999.92 988.72 1984.38 2033.57 2091.66 2071.18 52.04 51.76 51.62 119.45 120.56 120.57 1001.3 974.69 984.36 2091.6 2171.79 2132.29 3192.7 2.039 2.712 3.761 6.075 11.598 3.784 52.572 174.836 159.521 9.28 95.648 539.588 547.432 OpenBenchmarking.org
InfluxDB Concurrent Streams: 4 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 OpenBenchmarking.org val/sec, More Is Better InfluxDB 1.8.2 Concurrent Streams: 4 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 d c a b 300K 600K 900K 1200K 1500K SE +/- 5338.36, N = 3 1560758.0 1552035.6 1547894.4 1545780.8
InfluxDB Concurrent Streams: 64 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 OpenBenchmarking.org val/sec, More Is Better InfluxDB 1.8.2 Concurrent Streams: 64 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 a d c b 300K 600K 900K 1200K 1500K SE +/- 3918.66, N = 3 1602099.9 1600346.9 1599391.9 1593776.4
Intel TensorFlow Model: resnet50_fp32_pretrained_model - Batch Size: 1 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_fp32_pretrained_model - Batch Size: 1 d c b a 20 40 60 80 100 SE +/- 0.09, N = 3 80.22 79.99 79.78 79.28
Intel TensorFlow Model: resnet50_fp32_pretrained_model - Batch Size: 1 OpenBenchmarking.org ms, Fewer Is Better Intel TensorFlow 2.12 Model: resnet50_fp32_pretrained_model - Batch Size: 1 d c b a 3 6 9 12 15 SE +/- 0.01, N = 3 12.47 12.50 12.54 12.61
Intel TensorFlow Model: resnet50_int8_pretrained_model - Batch Size: 1 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_int8_pretrained_model - Batch Size: 1 a b d c 50 100 150 200 250 SE +/- 1.58, N = 3 221.86 221.77 217.59 216.37
Intel TensorFlow Model: resnet50_int8_pretrained_model - Batch Size: 1 OpenBenchmarking.org ms, Fewer Is Better Intel TensorFlow 2.12 Model: resnet50_int8_pretrained_model - Batch Size: 1 a b d c 1.04 2.08 3.12 4.16 5.2 SE +/- 0.032, N = 3 4.508 4.509 4.596 4.622
Intel TensorFlow Model: resnet50_fp32_pretrained_model - Batch Size: 16 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_fp32_pretrained_model - Batch Size: 16 b c d a 40 80 120 160 200 SE +/- 0.83, N = 3 171.63 171.05 169.33 168.74
Intel TensorFlow Model: resnet50_fp32_pretrained_model - Batch Size: 32 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_fp32_pretrained_model - Batch Size: 32 b c a d 40 80 120 160 200 SE +/- 0.31, N = 3 174.30 174.26 174.04 172.27
Intel TensorFlow Model: resnet50_fp32_pretrained_model - Batch Size: 64 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_fp32_pretrained_model - Batch Size: 64 c b a d 40 80 120 160 200 SE +/- 0.12, N = 3 170.60 170.52 170.51 170.26
Intel TensorFlow Model: resnet50_fp32_pretrained_model - Batch Size: 96 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_fp32_pretrained_model - Batch Size: 96 c a b d 40 80 120 160 200 SE +/- 0.11, N = 3 169.97 169.73 169.65 169.31
Intel TensorFlow Model: resnet50_int8_pretrained_model - Batch Size: 16 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_int8_pretrained_model - Batch Size: 16 c b a d 80 160 240 320 400 SE +/- 1.45, N = 3 348.37 347.93 346.02 344.87
Intel TensorFlow Model: resnet50_int8_pretrained_model - Batch Size: 32 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_int8_pretrained_model - Batch Size: 32 b c d a 80 160 240 320 400 SE +/- 0.47, N = 3 361.36 357.71 357.04 356.32
Intel TensorFlow Model: resnet50_int8_pretrained_model - Batch Size: 64 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_int8_pretrained_model - Batch Size: 64 d a c b 80 160 240 320 400 SE +/- 0.43, N = 3 365.31 365.10 365.00 364.04
Intel TensorFlow Model: resnet50_int8_pretrained_model - Batch Size: 96 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_int8_pretrained_model - Batch Size: 96 b a c d 80 160 240 320 400 SE +/- 0.27, N = 3 373.72 373.13 372.93 372.93
Intel TensorFlow Model: resnet50_fp32_pretrained_model - Batch Size: 256 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_fp32_pretrained_model - Batch Size: 256 d c b a 40 80 120 160 200 SE +/- 0.12, N = 3 168.16 168.06 168.00 167.97
Intel TensorFlow Model: resnet50_fp32_pretrained_model - Batch Size: 512 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_fp32_pretrained_model - Batch Size: 512 c b a d 40 80 120 160 200 SE +/- 0.21, N = 3 168.79 168.64 168.37 168.37
Intel TensorFlow Model: resnet50_fp32_pretrained_model - Batch Size: 960 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_fp32_pretrained_model - Batch Size: 960 c b d a 40 80 120 160 200 SE +/- 0.30, N = 3 170.09 169.73 169.34 168.72
Intel TensorFlow Model: resnet50_int8_pretrained_model - Batch Size: 256 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_int8_pretrained_model - Batch Size: 256 a c b d 80 160 240 320 400 SE +/- 0.54, N = 3 382.09 381.06 380.65 380.02
Intel TensorFlow Model: resnet50_int8_pretrained_model - Batch Size: 512 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_int8_pretrained_model - Batch Size: 512 b c d a 80 160 240 320 400 SE +/- 0.21, N = 3 385.55 385.50 384.26 383.62
Intel TensorFlow Model: resnet50_int8_pretrained_model - Batch Size: 960 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_int8_pretrained_model - Batch Size: 960 c b a d 90 180 270 360 450 SE +/- 0.57, N = 3 392.38 392.07 391.68 391.38
Intel TensorFlow Model: inceptionv4_fp32_pretrained_model - Batch Size: 1 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_fp32_pretrained_model - Batch Size: 1 b a c d 8 16 24 32 40 SE +/- 0.26, N = 3 33.16 32.23 32.06 31.86
Intel TensorFlow Model: inceptionv4_fp32_pretrained_model - Batch Size: 1 OpenBenchmarking.org ms, Fewer Is Better Intel TensorFlow 2.12 Model: inceptionv4_fp32_pretrained_model - Batch Size: 1 b c d a 7 14 21 28 35 SE +/- 0.10, N = 3 30.48 30.65 30.72 30.82
Intel TensorFlow Model: inceptionv4_int8_pretrained_model - Batch Size: 1 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_int8_pretrained_model - Batch Size: 1 b d a c 15 30 45 60 75 SE +/- 0.07, N = 3 69.16 69.07 69.04 69.01
Intel TensorFlow Model: inceptionv4_int8_pretrained_model - Batch Size: 1 OpenBenchmarking.org ms, Fewer Is Better Intel TensorFlow 2.12 Model: inceptionv4_int8_pretrained_model - Batch Size: 1 d b c a 4 8 12 16 20 SE +/- 0.03, N = 3 14.38 14.42 14.43 14.44
Intel TensorFlow Model: mobilenetv1_fp32_pretrained_model - Batch Size: 1 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_fp32_pretrained_model - Batch Size: 1 b c d a 200 400 600 800 1000 SE +/- 0.98, N = 3 1048.20 1046.79 1046.40 1045.59
Intel TensorFlow Model: mobilenetv1_int8_pretrained_model - Batch Size: 1 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_int8_pretrained_model - Batch Size: 1 d c a b 400 800 1200 1600 2000 SE +/- 0.61, N = 3 1934.32 1933.58 1933.37 1932.47
Intel TensorFlow Model: inceptionv4_fp32_pretrained_model - Batch Size: 16 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_fp32_pretrained_model - Batch Size: 16 b d a c 12 24 36 48 60 SE +/- 0.07, N = 3 53.47 53.22 53.20 52.99
Intel TensorFlow Model: inceptionv4_fp32_pretrained_model - Batch Size: 32 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_fp32_pretrained_model - Batch Size: 32 d c a b 12 24 36 48 60 SE +/- 0.09, N = 3 53.27 53.11 53.10 52.91
Intel TensorFlow Model: inceptionv4_fp32_pretrained_model - Batch Size: 64 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_fp32_pretrained_model - Batch Size: 64 a b d c 12 24 36 48 60 SE +/- 0.12, N = 3 52.44 52.40 51.97 51.72
Intel TensorFlow Model: inceptionv4_fp32_pretrained_model - Batch Size: 96 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_fp32_pretrained_model - Batch Size: 96 d c a b 12 24 36 48 60 SE +/- 0.07, N = 3 52.00 51.90 51.83 51.72
Intel TensorFlow Model: inceptionv4_int8_pretrained_model - Batch Size: 16 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_int8_pretrained_model - Batch Size: 16 c d a b 30 60 90 120 150 SE +/- 0.30, N = 3 113.63 113.36 113.31 111.63
Intel TensorFlow Model: inceptionv4_int8_pretrained_model - Batch Size: 32 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_int8_pretrained_model - Batch Size: 32 d b a c 30 60 90 120 150 SE +/- 0.81, N = 3 117.89 117.81 117.00 116.93
Intel TensorFlow Model: inceptionv4_int8_pretrained_model - Batch Size: 64 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_int8_pretrained_model - Batch Size: 64 d b a c 30 60 90 120 150 SE +/- 0.54, N = 3 119.83 118.93 118.48 117.61
Intel TensorFlow Model: inceptionv4_int8_pretrained_model - Batch Size: 96 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_int8_pretrained_model - Batch Size: 96 c b a d 30 60 90 120 150 SE +/- 0.42, N = 3 119.82 119.10 118.25 118.23
Intel TensorFlow Model: mobilenetv1_fp32_pretrained_model - Batch Size: 16 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_fp32_pretrained_model - Batch Size: 16 c a d b 200 400 600 800 1000 SE +/- 0.39, N = 3 933.76 932.19 931.22 929.58
Intel TensorFlow Model: mobilenetv1_fp32_pretrained_model - Batch Size: 32 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_fp32_pretrained_model - Batch Size: 32 b c d a 200 400 600 800 1000 SE +/- 1.14, N = 3 984.41 982.66 981.61 981.32
Intel TensorFlow Model: mobilenetv1_fp32_pretrained_model - Batch Size: 64 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_fp32_pretrained_model - Batch Size: 64 c d a b 200 400 600 800 1000 SE +/- 0.55, N = 3 999.93 999.92 998.43 997.73
Intel TensorFlow Model: mobilenetv1_fp32_pretrained_model - Batch Size: 96 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_fp32_pretrained_model - Batch Size: 96 a d c b 200 400 600 800 1000 SE +/- 1.26, N = 3 990.35 988.72 988.15 986.72
Intel TensorFlow Model: mobilenetv1_int8_pretrained_model - Batch Size: 16 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_int8_pretrained_model - Batch Size: 16 a b c d 400 800 1200 1600 2000 SE +/- 14.27, N = 3 2003.49 2002.09 1989.00 1984.38
Intel TensorFlow Model: mobilenetv1_int8_pretrained_model - Batch Size: 32 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_int8_pretrained_model - Batch Size: 32 b a c d 500 1000 1500 2000 2500 SE +/- 19.33, N = 7 2110.19 2056.18 2037.86 2033.57
Intel TensorFlow Model: mobilenetv1_int8_pretrained_model - Batch Size: 64 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_int8_pretrained_model - Batch Size: 64 b a d c 500 1000 1500 2000 2500 SE +/- 10.67, N = 3 2120.77 2112.33 2091.66 2063.78
Intel TensorFlow Model: mobilenetv1_int8_pretrained_model - Batch Size: 96 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_int8_pretrained_model - Batch Size: 96 c a b d 400 800 1200 1600 2000 SE +/- 2.02, N = 3 2087.39 2083.55 2081.87 2071.18
Intel TensorFlow Model: inceptionv4_fp32_pretrained_model - Batch Size: 256 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_fp32_pretrained_model - Batch Size: 256 b c d a 12 24 36 48 60 SE +/- 0.02, N = 3 52.07 52.06 52.04 51.92
Intel TensorFlow Model: inceptionv4_fp32_pretrained_model - Batch Size: 512 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_fp32_pretrained_model - Batch Size: 512 b c d a 12 24 36 48 60 SE +/- 0.05, N = 3 51.87 51.77 51.76 51.76
Intel TensorFlow Model: inceptionv4_fp32_pretrained_model - Batch Size: 960 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_fp32_pretrained_model - Batch Size: 960 b a d c 12 24 36 48 60 SE +/- 0.11, N = 3 51.78 51.76 51.62 51.59
Intel TensorFlow Model: inceptionv4_int8_pretrained_model - Batch Size: 256 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_int8_pretrained_model - Batch Size: 256 d c b a 30 60 90 120 150 SE +/- 0.27, N = 3 119.45 119.33 119.18 119.18
Intel TensorFlow Model: inceptionv4_int8_pretrained_model - Batch Size: 512 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_int8_pretrained_model - Batch Size: 512 d c a b 30 60 90 120 150 SE +/- 0.14, N = 3 120.56 119.91 119.90 119.61
Intel TensorFlow Model: inceptionv4_int8_pretrained_model - Batch Size: 960 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_int8_pretrained_model - Batch Size: 960 b c a d 30 60 90 120 150 SE +/- 0.16, N = 3 120.94 120.74 120.74 120.57
Intel TensorFlow Model: mobilenetv1_fp32_pretrained_model - Batch Size: 256 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_fp32_pretrained_model - Batch Size: 256 a c d b 200 400 600 800 1000 SE +/- 0.11, N = 3 1001.61 1001.43 1001.30 1000.28
Intel TensorFlow Model: mobilenetv1_fp32_pretrained_model - Batch Size: 512 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_fp32_pretrained_model - Batch Size: 512 a c b d 200 400 600 800 1000 SE +/- 0.75, N = 3 976.58 976.22 974.84 974.69
Intel TensorFlow Model: mobilenetv1_fp32_pretrained_model - Batch Size: 960 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_fp32_pretrained_model - Batch Size: 960 d a b c 200 400 600 800 1000 SE +/- 0.13, N = 3 984.36 983.76 982.71 982.46
Intel TensorFlow Model: mobilenetv1_int8_pretrained_model - Batch Size: 256 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_int8_pretrained_model - Batch Size: 256 b d a c 500 1000 1500 2000 2500 SE +/- 14.60, N = 3 2106.54 2091.60 2090.97 2028.82
Intel TensorFlow Model: mobilenetv1_int8_pretrained_model - Batch Size: 512 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_int8_pretrained_model - Batch Size: 512 b d a c 500 1000 1500 2000 2500 SE +/- 2.76, N = 3 2179.09 2171.79 2170.09 2161.98
Intel TensorFlow Model: mobilenetv1_int8_pretrained_model - Batch Size: 960 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_int8_pretrained_model - Batch Size: 960 c a d b 500 1000 1500 2000 2500 SE +/- 2.58, N = 3 2137.20 2133.18 2132.29 2128.10
QuantLib OpenBenchmarking.org MFLOPS, More Is Better QuantLib 1.30 b a c d 700 1400 2100 2800 3500 SE +/- 1.35, N = 3 3206.1 3202.1 3200.7 3192.7 1. (CXX) g++ options: -O3 -march=native -fPIE -pie
SQLite Threads / Copies: 2 OpenBenchmarking.org Seconds, Fewer Is Better SQLite 3.41.2 Threads / Copies: 2 d b c a 0.4838 0.9676 1.4514 1.9352 2.419 SE +/- 0.004, N = 3 2.039 2.041 2.106 2.150 1. (CC) gcc options: -O2 -lz -lm
SQLite Threads / Copies: 4 OpenBenchmarking.org Seconds, Fewer Is Better SQLite 3.41.2 Threads / Copies: 4 d c b a 0.7151 1.4302 2.1453 2.8604 3.5755 SE +/- 0.030, N = 15 2.712 2.904 2.938 3.178 1. (CC) gcc options: -O2 -lz -lm
SQLite Threads / Copies: 8 OpenBenchmarking.org Seconds, Fewer Is Better SQLite 3.41.2 Threads / Copies: 8 d b c a 1.1396 2.2792 3.4188 4.5584 5.698 SE +/- 0.038, N = 3 3.761 3.856 3.966 5.065 1. (CC) gcc options: -O2 -lz -lm
SQLite Threads / Copies: 16 OpenBenchmarking.org Seconds, Fewer Is Better SQLite 3.41.2 Threads / Copies: 16 d b c a 2 4 6 8 10 SE +/- 0.163, N = 13 6.075 6.209 7.198 8.476 1. (CC) gcc options: -O2 -lz -lm
SQLite Threads / Copies: 32 OpenBenchmarking.org Seconds, Fewer Is Better SQLite 3.41.2 Threads / Copies: 32 a d c b 3 6 9 12 15 SE +/- 0.05, N = 3 11.32 11.60 11.74 11.81 1. (CC) gcc options: -O2 -lz -lm
SVT-AV1 Encoder Mode: Preset 4 - Input: Bosphorus 4K OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.5 Encoder Mode: Preset 4 - Input: Bosphorus 4K c d b a 0.853 1.706 2.559 3.412 4.265 SE +/- 0.019, N = 3 3.791 3.784 3.782 3.766 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 8 - Input: Bosphorus 4K OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.5 Encoder Mode: Preset 8 - Input: Bosphorus 4K a d c b 12 24 36 48 60 SE +/- 0.19, N = 3 52.58 52.57 52.52 51.98 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 12 - Input: Bosphorus 4K OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.5 Encoder Mode: Preset 12 - Input: Bosphorus 4K b d a c 40 80 120 160 200 SE +/- 0.56, N = 3 175.68 174.84 174.52 172.70 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 13 - Input: Bosphorus 4K OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.5 Encoder Mode: Preset 13 - Input: Bosphorus 4K b a c d 40 80 120 160 200 SE +/- 0.85, N = 3 160.66 160.50 160.14 159.52 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 4 - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.5 Encoder Mode: Preset 4 - Input: Bosphorus 1080p d c b a 3 6 9 12 15 SE +/- 0.031, N = 3 9.280 9.121 9.064 9.027 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 8 - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.5 Encoder Mode: Preset 8 - Input: Bosphorus 1080p c a b d 20 40 60 80 100 SE +/- 0.42, N = 3 96.33 95.93 95.71 95.65 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 12 - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.5 Encoder Mode: Preset 12 - Input: Bosphorus 1080p a b d c 120 240 360 480 600 SE +/- 0.64, N = 3 547.50 542.03 539.59 535.68 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 13 - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.5 Encoder Mode: Preset 13 - Input: Bosphorus 1080p a d c b 120 240 360 480 600 SE +/- 0.34, N = 3 548.01 547.43 545.86 542.63 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
Phoronix Test Suite v10.8.4