2 x AMD EPYC 75F3 32-Core testing with a ASRockRack ROME2D16-2T (P3.30 BIOS) and ASPEED on Ubuntu 21.10 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 2204097-NE-EPYC75F3N46 epyc-75f3-new - Phoronix Test Suite epyc-75f3-new 2 x AMD EPYC 75F3 32-Core testing with a ASRockRack ROME2D16-2T (P3.30 BIOS) and ASPEED on Ubuntu 21.10 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2204097-NE-EPYC75F3N46&gru&rdt .
epyc-75f3-new Processor Motherboard Chipset Memory Disk Graphics Audio Network OS Kernel Desktop Display Server Vulkan Compiler File-System Screen Resolution A AA B C 2 x AMD EPYC 75F3 32-Core @ 2.95GHz (64 Cores / 128 Threads) ASRockRack ROME2D16-2T (P3.30 BIOS) AMD Starship/Matisse 128GB 1000GB Western Digital WD_BLACK SN850 1TB ASPEED AMD Starship/Matisse 2 x Intel 10G X550T Ubuntu 21.10 5.17.0-051700rc4daily20220219-generic (x86_64) GNOME Shell 40.5 X Server 1.1.182 GCC 11.2.0 ext4 1024x768 OpenBenchmarking.org Kernel Details - Transparent Huge Pages: madvise Compiler Details - --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-11-ZPT0kp/gcc-11-11.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-ZPT0kp/gcc-11-11.2.0/debian/tmp-gcn/usr --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-build-config=bootstrap-lto-lean --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v Processor Details - Scaling Governor: acpi-cpufreq schedutil (Boost: Enabled) - CPU Microcode: 0xa001114 Python Details - Python 3.9.7 Security Details - itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: 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 Full AMD retpoline IBPB: conditional IBRS_FW STIBP: always-on RSB filling + srbds: Not affected + tsx_async_abort: Not affected
epyc-75f3-new perf-bench: Memcpy 1MB perf-bench: Memset 1MB onnx: GPT-2 - CPU - Parallel onnx: GPT-2 - CPU - Standard onnx: yolov4 - CPU - Parallel onnx: yolov4 - CPU - Standard onnx: bertsquad-12 - CPU - Parallel onnx: bertsquad-12 - CPU - Standard onnx: fcn-resnet101-11 - CPU - Parallel onnx: fcn-resnet101-11 - CPU - Standard onnx: ArcFace ResNet-100 - CPU - Parallel onnx: ArcFace ResNet-100 - CPU - Standard onnx: super-resolution-10 - CPU - Parallel onnx: super-resolution-10 - CPU - Standard perf-bench: Epoll Wait perf-bench: Futex Hash perf-bench: Sched Pipe perf-bench: Futex Lock-Pi perf-bench: Syscall Basic onednn: IP Shapes 1D - f32 - CPU onednn: IP Shapes 3D - f32 - CPU onednn: IP Shapes 1D - u8s8f32 - CPU onednn: IP Shapes 3D - u8s8f32 - CPU onednn: Convolution Batch Shapes Auto - f32 - CPU onednn: Deconvolution Batch shapes_1d - f32 - CPU onednn: Deconvolution Batch shapes_3d - f32 - CPU onednn: Convolution Batch Shapes Auto - u8s8f32 - CPU onednn: Deconvolution Batch shapes_1d - u8s8f32 - CPU onednn: Deconvolution Batch shapes_3d - u8s8f32 - CPU onednn: Recurrent Neural Network Training - f32 - CPU onednn: Recurrent Neural Network Inference - f32 - CPU onednn: Recurrent Neural Network Training - u8s8f32 - CPU onednn: Recurrent Neural Network Inference - u8s8f32 - CPU onednn: Matrix Multiply Batch Shapes Transformer - f32 - CPU onednn: Recurrent Neural Network Training - bf16bf16bf16 - CPU onednn: Recurrent Neural Network Inference - bf16bf16bf16 - CPU onednn: Matrix Multiply Batch Shapes Transformer - u8s8f32 - CPU avifenc: 0 avifenc: 2 avifenc: 6 avifenc: 6, Lossless avifenc: 10, Lossless A AA B C 42.868389 62.455072 2352 2976792 345990 77 17051621 2.94158 2.63912 4.05569 0.747084 0.705380 11.2361 2.12767 0.897288 1.68391 0.878553 3874.18 1693.03 3819.45 1624.246 11.51214 69.460 38.784 4.278 7.215 5.010 42.829829 63.415414 1308 13234 434 355 594 540 123 170 1225 1194 4320 4626 2299 2976712 351368 77 17052202 3.7792 2.54811 4.25865 0.815632 0.708812 11.1395 2.10407 1.24701 1.07515 0.904662 4530.24 1803.51 4416.22 2016.94 17.5534 4276.7 1711.61 22.9061 69.411 38.728 4.093 7.389 5.229 44.147916 63.789341 1225 13106 436 291 592 643 123 158 1235 1244 4242 7762 2572 2979134 346133 80 16941879 3.18091 2.56643 4.77292 0.757826 0.684799 11.2174 1.94632 0.928893 1.853 0.803426 4336.25 1810.37 4623.03 1801.29 12.4965 4464.12 1734.92 27.3436 70.327 37.566 3.986 7.514 5.197 42.926485 63.185354 1242 9094 436 316 592 539 124 152 1229 1279 4233 4488 2062 2945494 339461 77 16924594 3.85444 2.54404 2.55861 0.74301 0.689583 11.1942 1.99639 0.78443 1.23753 0.829217 4224.87 1713.39 4390.23 1696.6 21.6718 3862.48 1721.12 29.1013 70.646 39.573 4.215 7.185 4.971 OpenBenchmarking.org
perf-bench Benchmark: Memcpy 1MB OpenBenchmarking.org GB/sec, More Is Better perf-bench Benchmark: Memcpy 1MB A AA B C 10 20 30 40 50 SE +/- 0.17, N = 3 42.87 42.83 44.15 42.93 1. (CC) gcc options: -O6 -ggdb3 -funwind-tables -std=gnu99 -lunwind-x86_64 -lunwind -llzma -Xlinker -lpthread -lrt -lm -ldl -lelf -lcrypto -lslang -lz -lnuma
perf-bench Benchmark: Memset 1MB OpenBenchmarking.org GB/sec, More Is Better perf-bench Benchmark: Memset 1MB A AA B C 14 28 42 56 70 SE +/- 0.65, N = 5 62.46 63.42 63.79 63.19 1. (CC) gcc options: -O6 -ggdb3 -funwind-tables -std=gnu99 -lunwind-x86_64 -lunwind -llzma -Xlinker -lpthread -lrt -lm -ldl -lelf -lcrypto -lslang -lz -lnuma
ONNX Runtime Model: GPT-2 - Device: CPU - Executor: Parallel OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.11 Model: GPT-2 - Device: CPU - Executor: Parallel AA B C 300 600 900 1200 1500 1308 1225 1242 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: GPT-2 - Device: CPU - Executor: Standard OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.11 Model: GPT-2 - Device: CPU - Executor: Standard AA B C 3K 6K 9K 12K 15K 13234 13106 9094 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: yolov4 - Device: CPU - Executor: Parallel OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.11 Model: yolov4 - Device: CPU - Executor: Parallel AA B C 90 180 270 360 450 434 436 436 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: yolov4 - Device: CPU - Executor: Standard OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.11 Model: yolov4 - Device: CPU - Executor: Standard AA B C 80 160 240 320 400 355 291 316 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: bertsquad-12 - Device: CPU - Executor: Parallel OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.11 Model: bertsquad-12 - Device: CPU - Executor: Parallel AA B C 130 260 390 520 650 594 592 592 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: bertsquad-12 - Device: CPU - Executor: Standard OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.11 Model: bertsquad-12 - Device: CPU - Executor: Standard AA B C 140 280 420 560 700 540 643 539 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: fcn-resnet101-11 - Device: CPU - Executor: Parallel OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.11 Model: fcn-resnet101-11 - Device: CPU - Executor: Parallel AA B C 30 60 90 120 150 123 123 124 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: fcn-resnet101-11 - Device: CPU - Executor: Standard OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.11 Model: fcn-resnet101-11 - Device: CPU - Executor: Standard AA B C 40 80 120 160 200 170 158 152 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: ArcFace ResNet-100 - Device: CPU - Executor: Parallel OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.11 Model: ArcFace ResNet-100 - Device: CPU - Executor: Parallel AA B C 300 600 900 1200 1500 1225 1235 1229 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: ArcFace ResNet-100 - Device: CPU - Executor: Standard OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.11 Model: ArcFace ResNet-100 - Device: CPU - Executor: Standard AA B C 300 600 900 1200 1500 1194 1244 1279 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: super-resolution-10 - Device: CPU - Executor: Parallel OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.11 Model: super-resolution-10 - Device: CPU - Executor: Parallel AA B C 900 1800 2700 3600 4500 4320 4242 4233 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: super-resolution-10 - Device: CPU - Executor: Standard OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.11 Model: super-resolution-10 - Device: CPU - Executor: Standard AA B C 1700 3400 5100 6800 8500 4626 7762 4488 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt
perf-bench Benchmark: Epoll Wait OpenBenchmarking.org ops/sec, More Is Better perf-bench Benchmark: Epoll Wait A AA B C 600 1200 1800 2400 3000 SE +/- 23.81, N = 12 2352 2299 2572 2062 1. (CC) gcc options: -O6 -ggdb3 -funwind-tables -std=gnu99 -lunwind-x86_64 -lunwind -llzma -Xlinker -lpthread -lrt -lm -ldl -lelf -lcrypto -lslang -lz -lnuma
perf-bench Benchmark: Futex Hash OpenBenchmarking.org ops/sec, More Is Better perf-bench Benchmark: Futex Hash A AA B C 600K 1200K 1800K 2400K 3000K SE +/- 6620.62, N = 3 2976792 2976712 2979134 2945494 1. (CC) gcc options: -O6 -ggdb3 -funwind-tables -std=gnu99 -lunwind-x86_64 -lunwind -llzma -Xlinker -lpthread -lrt -lm -ldl -lelf -lcrypto -lslang -lz -lnuma
perf-bench Benchmark: Sched Pipe OpenBenchmarking.org ops/sec, More Is Better perf-bench Benchmark: Sched Pipe A AA B C 80K 160K 240K 320K 400K SE +/- 3279.19, N = 3 345990 351368 346133 339461 1. (CC) gcc options: -O6 -ggdb3 -funwind-tables -std=gnu99 -lunwind-x86_64 -lunwind -llzma -Xlinker -lpthread -lrt -lm -ldl -lelf -lcrypto -lslang -lz -lnuma
perf-bench Benchmark: Futex Lock-Pi OpenBenchmarking.org ops/sec, More Is Better perf-bench Benchmark: Futex Lock-Pi A AA B C 20 40 60 80 100 SE +/- 0.58, N = 3 77 77 80 77 1. (CC) gcc options: -O6 -ggdb3 -funwind-tables -std=gnu99 -lunwind-x86_64 -lunwind -llzma -Xlinker -lpthread -lrt -lm -ldl -lelf -lcrypto -lslang -lz -lnuma
perf-bench Benchmark: Syscall Basic OpenBenchmarking.org ops/sec, More Is Better perf-bench Benchmark: Syscall Basic A AA B C 4M 8M 12M 16M 20M SE +/- 7517.61, N = 3 17051621 17052202 16941879 16924594 1. (CC) gcc options: -O6 -ggdb3 -funwind-tables -std=gnu99 -lunwind-x86_64 -lunwind -llzma -Xlinker -lpthread -lrt -lm -ldl -lelf -lcrypto -lslang -lz -lnuma
oneDNN Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU A AA B C 0.8672 1.7344 2.6016 3.4688 4.336 SE +/- 0.19680, N = 15 2.94158 3.77920 3.18091 3.85444 MIN: 1.53 MIN: 2.55 MIN: 2.24 MIN: 2.65 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU A AA B C 0.5938 1.1876 1.7814 2.3752 2.969 SE +/- 0.01578, N = 3 2.63912 2.54811 2.56643 2.54404 MIN: 2.08 MIN: 2.06 MIN: 2.05 MIN: 2.05 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU A AA B C 1.0739 2.1478 3.2217 4.2956 5.3695 SE +/- 0.14420, N = 15 4.05569 4.25865 4.77292 2.55861 MIN: 2.07 MIN: 2.63 MIN: 2.83 MIN: 1.85 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU A AA B C 0.1835 0.367 0.5505 0.734 0.9175 SE +/- 0.011604, N = 15 0.747084 0.815632 0.757826 0.743010 MIN: 0.57 MIN: 0.62 MIN: 0.62 MIN: 0.61 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU A AA B C 0.1595 0.319 0.4785 0.638 0.7975 SE +/- 0.006925, N = 3 0.705380 0.708812 0.684799 0.689583 MIN: 0.64 MIN: 0.67 MIN: 0.64 MIN: 0.64 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU A AA B C 3 6 9 12 15 SE +/- 0.09, N = 3 11.24 11.14 11.22 11.19 MIN: 8.6 MIN: 9 MIN: 9 MIN: 8.84 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU A AA B C 0.4787 0.9574 1.4361 1.9148 2.3935 SE +/- 0.02508, N = 3 2.12767 2.10407 1.94632 1.99639 MIN: 1.72 MIN: 1.79 MIN: 1.74 MIN: 1.73 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU A AA B C 0.2806 0.5612 0.8418 1.1224 1.403 SE +/- 0.048482, N = 15 0.897288 1.247010 0.928893 0.784430 MIN: 0.51 MIN: 0.56 MIN: 0.54 MIN: 0.54 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU A AA B C 0.4169 0.8338 1.2507 1.6676 2.0845 SE +/- 0.09292, N = 15 1.68391 1.07515 1.85300 1.23753 MIN: 0.87 MIN: 0.92 MIN: 1.67 MIN: 1.09 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU A AA B C 0.2035 0.407 0.6105 0.814 1.0175 SE +/- 0.011448, N = 12 0.878553 0.904662 0.803426 0.829217 MIN: 0.65 MIN: 0.68 MIN: 0.57 MIN: 0.6 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU A AA B C 1000 2000 3000 4000 5000 SE +/- 239.78, N = 14 3874.18 4530.24 4336.25 4224.87 MIN: 1544.77 MIN: 3953.07 MIN: 3938.66 MIN: 3842.95 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU A AA B C 400 800 1200 1600 2000 SE +/- 64.86, N = 12 1693.03 1803.51 1810.37 1713.39 MIN: 1036.24 MIN: 1650.67 MIN: 1535.85 MIN: 1504.13 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU A AA B C 1000 2000 3000 4000 5000 SE +/- 242.60, N = 12 3819.45 4416.22 4623.03 4390.23 MIN: 1342.54 MIN: 4047.45 MIN: 4242.04 MIN: 3742.53 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU A AA B C 400 800 1200 1600 2000 SE +/- 88.05, N = 12 1624.25 2016.94 1801.29 1696.60 MIN: 827.28 MIN: 1858.23 MIN: 1534.31 MIN: 1543.98 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU A AA B C 5 10 15 20 25 SE +/- 1.25, N = 15 11.51 17.55 12.50 21.67 MIN: 5.15 MIN: 12.56 MIN: 8.99 MIN: 15.66 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU AA B C 1000 2000 3000 4000 5000 4276.70 4464.12 3862.48 MIN: 3959.8 MIN: 4162.92 MIN: 3242.51 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU AA B C 400 800 1200 1600 2000 1711.61 1734.92 1721.12 MIN: 1495.43 MIN: 1463.54 MIN: 1603.97 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU AA B C 7 14 21 28 35 22.91 27.34 29.10 MIN: 16.94 MIN: 19.51 MIN: 20.22 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
libavif avifenc Encoder Speed: 0 OpenBenchmarking.org Seconds, Fewer Is Better libavif avifenc 0.10 Encoder Speed: 0 A AA B C 16 32 48 64 80 SE +/- 0.35, N = 3 69.46 69.41 70.33 70.65 1. (CXX) g++ options: -O3 -fPIC -lm
libavif avifenc Encoder Speed: 2 OpenBenchmarking.org Seconds, Fewer Is Better libavif avifenc 0.10 Encoder Speed: 2 A AA B C 9 18 27 36 45 SE +/- 0.11, N = 3 38.78 38.73 37.57 39.57 1. (CXX) g++ options: -O3 -fPIC -lm
libavif avifenc Encoder Speed: 6 OpenBenchmarking.org Seconds, Fewer Is Better libavif avifenc 0.10 Encoder Speed: 6 A AA B C 0.9626 1.9252 2.8878 3.8504 4.813 SE +/- 0.011, N = 3 4.278 4.093 3.986 4.215 1. (CXX) g++ options: -O3 -fPIC -lm
libavif avifenc Encoder Speed: 6, Lossless OpenBenchmarking.org Seconds, Fewer Is Better libavif avifenc 0.10 Encoder Speed: 6, Lossless A AA B C 2 4 6 8 10 SE +/- 0.066, N = 7 7.215 7.389 7.514 7.185 1. (CXX) g++ options: -O3 -fPIC -lm
libavif avifenc Encoder Speed: 10, Lossless OpenBenchmarking.org Seconds, Fewer Is Better libavif avifenc 0.10 Encoder Speed: 10, Lossless A AA B C 1.1765 2.353 3.5295 4.706 5.8825 SE +/- 0.030, N = 3 5.010 5.229 5.197 4.971 1. (CXX) g++ options: -O3 -fPIC -lm
Phoronix Test Suite v10.8.4