new rn AMD Ryzen Threadripper 3970X 32-Core testing with a ASUS ROG ZENITH II EXTREME (1802 BIOS) and AMD Radeon RX 5700 8GB on Ubuntu 22.04 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2410152-NE-NEWRN099440&grw .
new rn Processor Motherboard Chipset Memory Disk Graphics Audio Monitor Network OS Kernel Desktop Display Server OpenGL Vulkan Compiler File-System Screen Resolution a b c d AMD Ryzen Threadripper 3970X 32-Core @ 3.70GHz (32 Cores / 64 Threads) ASUS ROG ZENITH II EXTREME (1802 BIOS) AMD Starship/Matisse 4 x 16GB DDR4-3600MT/s Corsair CMT64GX4M4Z3600C16 Samsung SSD 980 PRO 500GB AMD Radeon RX 5700 8GB AMD Navi 10 HDMI Audio ASUS VP28U Aquantia AQC107 NBase-T/IEEE + Intel I211 + Intel Wi-Fi 6 AX200 Ubuntu 22.04 6.8.0-45-generic (x86_64) GNOME Shell 42.9 X Server + Wayland 4.6 Mesa 22.0.1 (LLVM 13.0.1 DRM 3.57) 1.2.204 GCC 11.4.0 ext4 3840x2160 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-XeT9lY/gcc-11-11.4.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-XeT9lY/gcc-11-11.4.0/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: 0x830107a Security Details - gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + reg_file_data_sampling: Not affected + retbleed: Mitigation of untrained return thunk; SMT enabled with STIBP protection + spec_rstack_overflow: Mitigation of Safe RET + 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; STIBP: always-on; RSB filling; PBRSB-eIBRS: Not affected; BHI: Not affected + srbds: Not affected + tsx_async_abort: Not affected
new rn xnnpack: FP32MobileNetV1 litert: Inception ResNet V2 litert: Quantized COCO SSD MobileNet v1 litert: Mobilenet Float litert: Inception V4 litert: NASNet Mobile litert: DeepLab V3 litert: SqueezeNet xnnpack: FP32MobileNetV2 xnnpack: FP32MobileNetV3Large xnnpack: FP32MobileNetV3Small xnnpack: FP16MobileNetV1 xnnpack: FP16MobileNetV2 xnnpack: FP16MobileNetV3Large xnnpack: FP16MobileNetV3Small litert: Mobilenet Quant xnnpack: QS8MobileNetV2 onednn: IP Shapes 1D - CPU onednn: IP Shapes 3D - CPU onednn: Convolution Batch Shapes Auto - CPU onednn: Deconvolution Batch shapes_1d - CPU onednn: Deconvolution Batch shapes_3d - CPU onednn: Recurrent Neural Network Training - CPU onednn: Recurrent Neural Network Inference - CPU a b c d 1929 29125 2356.92 1820.83 30460.8 21130.2 3924.43 2506.99 2695 3828 2310 1614 2200 3100 2270 1405.64 2086 1.11186 6.26589 5.41074 8.92496 2.74673 1063.25 544.588 1920 29065.3 2344.66 1890.63 30192.8 21246.2 3884.51 2507.88 2678 3872 2209 1606 2156 3099 2151 1299.31 2058 1.10833 9.69956 5.94199 8.96791 2.71999 1065.95 545.194 1925 29257.6 2356.07 1830.85 30102.7 21105.6 3892.22 2533.05 2788 3938 2266 1616 2194 3106 2074 1300.82 2060 1.10933 9.83021 5.92981 8.68858 2.71566 1068.48 546.139 1935 29288.1 2366.82 1827.86 30176.1 21148.3 3963.25 2524.93 2692 3904 2219 1597 2242 3080 2455 1291.57 2097 1.10728 9.98705 5.9588 8.80404 2.74986 3079.07 551.716 OpenBenchmarking.org
XNNPACK Model: FP32MobileNetV1 OpenBenchmarking.org us, Fewer Is Better XNNPACK b7b048 Model: FP32MobileNetV1 a b c d 400 800 1200 1600 2000 1929 1920 1925 1935 1. (CXX) g++ options: -O3 -lrt -lm
LiteRT Model: Inception ResNet V2 OpenBenchmarking.org Microseconds, Fewer Is Better LiteRT 2024-10-15 Model: Inception ResNet V2 a b c d 6K 12K 18K 24K 30K 29125.0 29065.3 29257.6 29288.1
LiteRT Model: Quantized COCO SSD MobileNet v1 OpenBenchmarking.org Microseconds, Fewer Is Better LiteRT 2024-10-15 Model: Quantized COCO SSD MobileNet v1 a b c d 500 1000 1500 2000 2500 2356.92 2344.66 2356.07 2366.82
LiteRT Model: Mobilenet Float OpenBenchmarking.org Microseconds, Fewer Is Better LiteRT 2024-10-15 Model: Mobilenet Float a b c d 400 800 1200 1600 2000 1820.83 1890.63 1830.85 1827.86
LiteRT Model: Inception V4 OpenBenchmarking.org Microseconds, Fewer Is Better LiteRT 2024-10-15 Model: Inception V4 a b c d 7K 14K 21K 28K 35K 30460.8 30192.8 30102.7 30176.1
LiteRT Model: NASNet Mobile OpenBenchmarking.org Microseconds, Fewer Is Better LiteRT 2024-10-15 Model: NASNet Mobile a b c d 5K 10K 15K 20K 25K 21130.2 21246.2 21105.6 21148.3
LiteRT Model: DeepLab V3 OpenBenchmarking.org Microseconds, Fewer Is Better LiteRT 2024-10-15 Model: DeepLab V3 a b c d 800 1600 2400 3200 4000 3924.43 3884.51 3892.22 3963.25
LiteRT Model: SqueezeNet OpenBenchmarking.org Microseconds, Fewer Is Better LiteRT 2024-10-15 Model: SqueezeNet a b c d 500 1000 1500 2000 2500 2506.99 2507.88 2533.05 2524.93
XNNPACK Model: FP32MobileNetV2 OpenBenchmarking.org us, Fewer Is Better XNNPACK b7b048 Model: FP32MobileNetV2 a b c d 600 1200 1800 2400 3000 2695 2678 2788 2692 1. (CXX) g++ options: -O3 -lrt -lm
XNNPACK Model: FP32MobileNetV3Large OpenBenchmarking.org us, Fewer Is Better XNNPACK b7b048 Model: FP32MobileNetV3Large a b c d 800 1600 2400 3200 4000 3828 3872 3938 3904 1. (CXX) g++ options: -O3 -lrt -lm
XNNPACK Model: FP32MobileNetV3Small OpenBenchmarking.org us, Fewer Is Better XNNPACK b7b048 Model: FP32MobileNetV3Small a b c d 500 1000 1500 2000 2500 2310 2209 2266 2219 1. (CXX) g++ options: -O3 -lrt -lm
XNNPACK Model: FP16MobileNetV1 OpenBenchmarking.org us, Fewer Is Better XNNPACK b7b048 Model: FP16MobileNetV1 a b c d 300 600 900 1200 1500 1614 1606 1616 1597 1. (CXX) g++ options: -O3 -lrt -lm
XNNPACK Model: FP16MobileNetV2 OpenBenchmarking.org us, Fewer Is Better XNNPACK b7b048 Model: FP16MobileNetV2 a b c d 500 1000 1500 2000 2500 2200 2156 2194 2242 1. (CXX) g++ options: -O3 -lrt -lm
XNNPACK Model: FP16MobileNetV3Large OpenBenchmarking.org us, Fewer Is Better XNNPACK b7b048 Model: FP16MobileNetV3Large a b c d 700 1400 2100 2800 3500 3100 3099 3106 3080 1. (CXX) g++ options: -O3 -lrt -lm
XNNPACK Model: FP16MobileNetV3Small OpenBenchmarking.org us, Fewer Is Better XNNPACK b7b048 Model: FP16MobileNetV3Small a b c d 500 1000 1500 2000 2500 2270 2151 2074 2455 1. (CXX) g++ options: -O3 -lrt -lm
LiteRT Model: Mobilenet Quant OpenBenchmarking.org Microseconds, Fewer Is Better LiteRT 2024-10-15 Model: Mobilenet Quant a b c d 300 600 900 1200 1500 1405.64 1299.31 1300.82 1291.57
XNNPACK Model: QS8MobileNetV2 OpenBenchmarking.org us, Fewer Is Better XNNPACK b7b048 Model: QS8MobileNetV2 a b c d 500 1000 1500 2000 2500 2086 2058 2060 2097 1. (CXX) g++ options: -O3 -lrt -lm
oneDNN Harness: IP Shapes 1D - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.6 Harness: IP Shapes 1D - Engine: CPU a b c d 0.2502 0.5004 0.7506 1.0008 1.251 1.11186 1.10833 1.10933 1.10728 MIN: 1.08 MIN: 1.07 MIN: 1.08 MIN: 1.07 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -fcf-protection=full -pie -ldl
oneDNN Harness: IP Shapes 3D - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.6 Harness: IP Shapes 3D - Engine: CPU a b c d 3 6 9 12 15 6.26589 9.69956 9.83021 9.98705 MIN: 6.22 MIN: 9.64 MIN: 9.79 MIN: 9.95 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -fcf-protection=full -pie -ldl
oneDNN Harness: Convolution Batch Shapes Auto - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.6 Harness: Convolution Batch Shapes Auto - Engine: CPU a b c d 1.3407 2.6814 4.0221 5.3628 6.7035 5.41074 5.94199 5.92981 5.95880 MIN: 5.33 MIN: 5.86 MIN: 5.86 MIN: 5.88 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -fcf-protection=full -pie -ldl
oneDNN Harness: Deconvolution Batch shapes_1d - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.6 Harness: Deconvolution Batch shapes_1d - Engine: CPU a b c d 3 6 9 12 15 8.92496 8.96791 8.68858 8.80404 MIN: 8.08 MIN: 8.24 MIN: 6.99 MIN: 8.13 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -fcf-protection=full -pie -ldl
oneDNN Harness: Deconvolution Batch shapes_3d - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.6 Harness: Deconvolution Batch shapes_3d - Engine: CPU a b c d 0.6187 1.2374 1.8561 2.4748 3.0935 2.74673 2.71999 2.71566 2.74986 MIN: 2.68 MIN: 2.65 MIN: 2.66 MIN: 2.68 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -fcf-protection=full -pie -ldl
oneDNN Harness: Recurrent Neural Network Training - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.6 Harness: Recurrent Neural Network Training - Engine: CPU a b c d 700 1400 2100 2800 3500 1063.25 1065.95 1068.48 3079.07 MIN: 1055.25 MIN: 1056.53 MIN: 1059.46 MIN: 1894.93 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -fcf-protection=full -pie -ldl
oneDNN Harness: Recurrent Neural Network Inference - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.6 Harness: Recurrent Neural Network Inference - Engine: CPU a b c d 120 240 360 480 600 544.59 545.19 546.14 551.72 MIN: 540.62 MIN: 541.34 MIN: 542.08 MIN: 538.72 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -fcf-protection=full -pie -ldl
Phoronix Test Suite v10.8.5