AMD EPYC 7601 32-Core testing with a TYAN B8026T70AE24HR (V1.02.B10 BIOS) and ASPEED on Ubuntu 19.04 via the Phoronix Test Suite.
Ubuntu 19.04 Processor: AMD EPYC 7601 32-Core @ 2.20GHz (32 Cores / 64 Threads), Motherboard: TYAN B8026T70AE24HR (V1.02.B10 BIOS), Chipset: AMD 17h, Memory: 126GB, Disk: 280GB INTEL SSDPE21D280GA, Graphics: ASPEED, Monitor: VE228, Network: 2 x Broadcom NetXtreme BCM5720 PCIe
OS: Ubuntu 19.04, Kernel: 5.5.0-rc7-phx-k10temp6 (x86_64) 20200123, Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: modesetting 1.20.4, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 1920x1080
Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --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++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --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-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -vProcessor Notes: Scaling Governor: acpi-cpufreq ondemand - CPU Microcode: 0x8001227Python Notes: Python 2.7.16 + Python 3.7.3Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional STIBP: disabled RSB filling + tsx_async_abort: Not affected
AMD EPYC 7601 Ubuntu 19.04 OpenBenchmarking.org Phoronix Test Suite AMD EPYC 7601 32-Core @ 2.20GHz (32 Cores / 64 Threads) TYAN B8026T70AE24HR (V1.02.B10 BIOS) AMD 17h 126GB 280GB INTEL SSDPE21D280GA ASPEED VE228 2 x Broadcom NetXtreme BCM5720 PCIe Ubuntu 19.04 5.5.0-rc7-phx-k10temp6 (x86_64) 20200123 GNOME Shell 3.32.2 X Server 1.20.4 modesetting 1.20.4 GCC 8.3.0 ext4 1920x1080 Processor Motherboard Chipset Memory Disk Graphics Monitor Network OS Kernel Desktop Display Server Display Driver Compiler File-System Screen Resolution AMD EPYC 7601 Ubuntu 19.04 Benchmarks System Logs - --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --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++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --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-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v - Scaling Governor: acpi-cpufreq ondemand - CPU Microcode: 0x8001227 - Python 2.7.16 + Python 3.7.3 - itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional STIBP: disabled RSB filling + tsx_async_abort: Not affected
AMD EPYC 7601 Ubuntu 19.04 tesseract-ocr: Time To OCR 7 Images astcenc: Fast astcenc: Medium astcenc: Thorough astcenc: Exhaustive gmic: 2D Function Plotting, 1000 Times gmic: Plotting Isosurface Of A 3D Volume, 1000 Times gmic: 3D Elevated Function In Rand Colors, 100 Times hugin: Panorama Photo Assistant + Stitching Time rawtherapee: Total Benchmark Time rsvg: SVG Files To PNG ocrmypdf: Processing 60 Page PDF Document plaidml: No - Inference - VGG16 - CPU plaidml: No - Inference - VGG19 - CPU plaidml: No - Inference - IMDB LSTM - CPU plaidml: No - Inference - Mobilenet - CPU plaidml: No - Inference - ResNet 50 - CPU plaidml: No - Inference - DenseNet 201 - CPU plaidml: No - Inference - Inception V3 - CPU plaidml: No - Inference - NASNer Large - CPU tensorflow-lite: SqueezeNet tensorflow-lite: Inception V4 tensorflow-lite: NASNet Mobile tensorflow-lite: Mobilenet Float tensorflow-lite: Mobilenet Quant tensorflow-lite: Inception ResNet V2 gromacs: Water Benchmark namd: ATPase Simulation - 327,506 Atoms onednn: IP Batch 1D - f32 - CPU onednn: IP Batch All - f32 - CPU onednn: IP Batch 1D - u8s8f32 - CPU onednn: IP Batch All - u8s8f32 - CPU onednn: Convolution Batch Shapes Auto - f32 - CPU onednn: Deconvolution Batch deconv_1d - f32 - CPU onednn: Deconvolution Batch deconv_3d - f32 - CPU onednn: Convolution Batch Shapes Auto - u8s8f32 - CPU onednn: Deconvolution Batch deconv_1d - u8s8f32 - CPU onednn: Deconvolution Batch deconv_3d - u8s8f32 - CPU onednn: Recurrent Neural Network Training - f32 - CPU onednn: Recurrent Neural Network Inference - f32 - CPU onednn: Matrix Multiply Batch Shapes Transformer - f32 - CPU onednn: Matrix Multiply Batch Shapes Transformer - u8s8f32 - CPU perf-bench: Epoll Wait perf-bench: Futex Hash perf-bench: Memcpy 1MB perf-bench: Memset 1MB perf-bench: Sched Pipe perf-bench: Futex Lock-Pi perf-bench: Syscall Basic compress-zstd: 3 compress-zstd: 19 build-linux-kernel: Time To Compile svt-av1: Enc Mode 0 - 1080p svt-av1: Enc Mode 4 - 1080p svt-av1: Enc Mode 8 - 1080p blender: BMW27 - CPU-Only blender: Classroom - CPU-Only blender: Fishy Cat - CPU-Only blender: Barbershop - CPU-Only blender: Pabellon Barcelona - CPU-Only avifenc: 0 avifenc: 2 avifenc: 8 avifenc: 10 Ubuntu 19.04 42.516 6.65 8.02 11.93 91.62 335.089 26.994 115.672 73.929 64.842 37.624 31.976 15.78 13.09 716.04 11.74 5.38 2.35 7.13 0.74 99445.7 1303037 129628 59349.2 64549.9 1151380 1.942 0.96900 4.20128 70.3344 2.67082 36.7829 18.9315 3.75791 8.93657 20.5573 4.40219 4.29952 442.987 111.613 1.83780 1.73814 6511 2468188 14.996074 42.002642 263943 124 14977770 4652.9 61.2 43.089 0.097 4.237 36.916 76.25 212.84 111.65 337.51 252.92 91.153 55.614 7.084 7.021 OpenBenchmarking.org
ASTC Encoder ASTC Encoder (astcenc) is for the Adaptive Scalable Texture Compression (ASTC) format commonly used with OpenGL, OpenGL ES, and Vulkan graphics APIs. This test profile does a coding test of both compression/decompression. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better ASTC Encoder 2.0 Preset: Fast Ubuntu 19.04 2 4 6 8 10 SE +/- 0.05, N = 3 6.65 1. (CXX) g++ options: -std=c++14 -fvisibility=hidden -O3 -flto -mfpmath=sse -mavx2 -mpopcnt -lpthread
OpenBenchmarking.org Seconds, Fewer Is Better ASTC Encoder 2.0 Preset: Medium Ubuntu 19.04 2 4 6 8 10 SE +/- 0.04, N = 3 8.02 1. (CXX) g++ options: -std=c++14 -fvisibility=hidden -O3 -flto -mfpmath=sse -mavx2 -mpopcnt -lpthread
OpenBenchmarking.org Seconds, Fewer Is Better ASTC Encoder 2.0 Preset: Thorough Ubuntu 19.04 3 6 9 12 15 SE +/- 0.03, N = 3 11.93 1. (CXX) g++ options: -std=c++14 -fvisibility=hidden -O3 -flto -mfpmath=sse -mavx2 -mpopcnt -lpthread
OpenBenchmarking.org Seconds, Fewer Is Better ASTC Encoder 2.0 Preset: Exhaustive Ubuntu 19.04 20 40 60 80 100 SE +/- 0.22, N = 3 91.62 1. (CXX) g++ options: -std=c++14 -fvisibility=hidden -O3 -flto -mfpmath=sse -mavx2 -mpopcnt -lpthread
OpenBenchmarking.org Seconds, Fewer Is Better G'MIC Test: Plotting Isosurface Of A 3D Volume, 1000 Times Ubuntu 19.04 6 12 18 24 30 SE +/- 0.02, N = 3 26.99 1. Version 2.4.5, Copyright (c) 2008-2019, David Tschumperle.
OpenBenchmarking.org Seconds, Fewer Is Better G'MIC Test: 3D Elevated Function In Random Colors, 100 Times Ubuntu 19.04 30 60 90 120 150 SE +/- 0.08, N = 3 115.67 1. Version 2.4.5, Copyright (c) 2008-2019, David Tschumperle.
Hugin Hugin is an open-source, cross-platform panorama photo stitcher software package. This test profile times how long it takes to run the assistant and panorama photo stitching on a set of images. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better Hugin Panorama Photo Assistant + Stitching Time Ubuntu 19.04 16 32 48 64 80 SE +/- 0.74, N = 15 73.93
RawTherapee RawTherapee is a cross-platform, open-source multi-threaded RAW image processing program. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better RawTherapee Total Benchmark Time Ubuntu 19.04 14 28 42 56 70 SE +/- 0.15, N = 3 64.84 1. RawTherapee, version 5.5, command line.
An advanced, cross-platform program for developing raw photos.
Website: http://www.rawtherapee.com/
Documentation: http://rawpedia.rawtherapee.com/
Forum: https://discuss.pixls.us/c/software/rawtherapee
Code and bug reports: https://github.com/Beep6581/RawTherapee
Symbols:
<Chevrons> indicate parameters you can change.
[Square brackets] mean the parameter is optional.
The pipe symbol | indicates a choice of one or the other.
The dash symbol - denotes a range of possible values from one to the other.
Usage:
rawtherapee-cli -c <dir>|<files> Convert files in batch with default parameters.
rawtherapee-cli <other options> -c <dir>|<files> Convert files in batch with your own settings.
Options:
rawtherapee-cli[-o <output>|-O <output>] [-q] [-a] [-s|-S] [-p <one.pp3> [-p <two.pp3> ...] ] [-d] [ -j[1-100] -js<1-3> | -t[z] -b<8|16|16f|32> | -n -b<8|16> ] [-Y] [-f] -c <input>
-c <files> Specify one or more input files or folders.
When specifying folders, Rawtherapee will look for image file types which comply
with the selected extensions (see also '-a').
-c must be the last option.
-o <file>|<dir> Set output file or folder.
Saves output file alongside input file if -o is not specified.
-O <file>|<dir> Set output file or folder and copy pp3 file into it.
Saves output file alongside input file if -O is not specified.
-q Quick-start mode. Does not load cached files to speedup start time.
-a Process all supported image file types when specifying a folder, even those
not currently selected in Preferences > File Browser > Parsed Extensions.
-s Use the existing sidecar file to build the processing parameters,
e.g. for photo.raw there should be a photo.raw.pp3 file in the same folder.
If the sidecar file does not exist, neutral values will be used.
-S Like -s but skip if the sidecar file does not exist.
-p <file.pp3> Specify processing profile to be used for all conversions.
You can specify as many sets of "-p <file.pp3>" options as you like,
each will be built on top of the previous one, as explained below.
-d Use the default raw or non-raw processing profile as set in
Preferences > Image Processing > Default Processing Profile
-j[1-100] Specify output to be JPEG (default, if -t and -n are not set).
Optionally, specify compression 1-100 (default value: 92).
-js<1-3> Specify the JPEG chroma subsampling parameter, where:
1 = Best compression: 2x2, 1x1, 1x1 (4:2:0)
Chroma halved vertically and horizontally.
2 = Balanced (default): 2x1, 1x1, 1x1 (4:2:2)
Chroma halved horizontally.
3 = Best quality: 1x1, 1x1, 1x1 (4:4:4)
No chroma subsampling.
-b<8|16|16f|32> Specify bit depth per channel.
8 = 8-bit integer. Applies to JPEG, PNG and TIFF. Default for JPEG and PNG.
16 = 16-bit integer. Applies to TIFF and PNG. Default for TIFF.
16f = 16-bit float. Applies to TIFF.
32 = 32-bit float. Applies to TIFF.
-t[z] Specify output to be TIFF.
Uncompressed by default, or deflate compression with 'z'.
-n Specify output to be compressed PNG.
Compression is hard-coded to PNG_FILTER_PAETH, Z_RLE.
-Y Overwrite output if present.
-f Use the custom fast-export processing pipeline.
Your pp3 files can be incomplete, RawTherapee will build the final values as follows:
1- A new processing profile is created using neutral values,
2- If the "-d" option is set, the values are overridden by those found in
the default raw or non-raw processing profile.
3- If one or more "-p" options are set, the values are overridden by those
found in these processing profiles.
4- If the "-s" or "-S" options are set, the values are finally overridden by those
found in the sidecar files.
The processing profiles are processed in the order specified on the command line.
OpenBenchmarking.org FPS, More Is Better PlaidML FP16: No - Mode: Inference - Network: VGG19 - Device: CPU Ubuntu 19.04 3 6 9 12 15 SE +/- 0.07, N = 3 13.09
OpenBenchmarking.org FPS, More Is Better PlaidML FP16: No - Mode: Inference - Network: IMDB LSTM - Device: CPU Ubuntu 19.04 150 300 450 600 750 SE +/- 1.69, N = 3 716.04
OpenBenchmarking.org FPS, More Is Better PlaidML FP16: No - Mode: Inference - Network: Mobilenet - Device: CPU Ubuntu 19.04 3 6 9 12 15 SE +/- 0.07, N = 3 11.74
OpenBenchmarking.org FPS, More Is Better PlaidML FP16: No - Mode: Inference - Network: ResNet 50 - Device: CPU Ubuntu 19.04 1.2105 2.421 3.6315 4.842 6.0525 SE +/- 0.03, N = 3 5.38
OpenBenchmarking.org FPS, More Is Better PlaidML FP16: No - Mode: Inference - Network: DenseNet 201 - Device: CPU Ubuntu 19.04 0.5288 1.0576 1.5864 2.1152 2.644 SE +/- 0.00, N = 3 2.35
OpenBenchmarking.org FPS, More Is Better PlaidML FP16: No - Mode: Inference - Network: Inception V3 - Device: CPU Ubuntu 19.04 2 4 6 8 10 SE +/- 0.05, N = 3 7.13
OpenBenchmarking.org FPS, More Is Better PlaidML FP16: No - Mode: Inference - Network: NASNer Large - Device: CPU Ubuntu 19.04 0.1665 0.333 0.4995 0.666 0.8325 SE +/- 0.00, N = 3 0.74
NAMD NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. NAMD was developed by the Theoretical and Computational Biophysics Group in the Beckman Institute for Advanced Science and Technology at the University of Illinois at Urbana-Champaign. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org days/ns, Fewer Is Better NAMD 2.14 ATPase Simulation - 327,506 Atoms Ubuntu 19.04 0.218 0.436 0.654 0.872 1.09 SE +/- 0.00501, N = 3 0.96900
oneDNN This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the oneAPI initiative. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: IP Batch 1D - Data Type: f32 - Engine: CPU Ubuntu 19.04 0.9453 1.8906 2.8359 3.7812 4.7265 SE +/- 0.09463, N = 14 4.20128 MIN: 2.85 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: IP Batch All - Data Type: f32 - Engine: CPU Ubuntu 19.04 16 32 48 64 80 SE +/- 0.57, N = 3 70.33 MIN: 63.69 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: IP Batch 1D - Data Type: u8s8f32 - Engine: CPU Ubuntu 19.04 0.6009 1.2018 1.8027 2.4036 3.0045 SE +/- 0.00259, N = 3 2.67082 MIN: 2.59 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: IP Batch All - Data Type: u8s8f32 - Engine: CPU Ubuntu 19.04 8 16 24 32 40 SE +/- 0.54, N = 15 36.78 MIN: 32.82 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU Ubuntu 19.04 5 10 15 20 25 SE +/- 0.02, N = 3 18.93 MIN: 17.83 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: Deconvolution Batch deconv_1d - Data Type: f32 - Engine: CPU Ubuntu 19.04 0.8455 1.691 2.5365 3.382 4.2275 SE +/- 0.02933, N = 3 3.75791 MIN: 3.44 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: Deconvolution Batch deconv_3d - Data Type: f32 - Engine: CPU Ubuntu 19.04 2 4 6 8 10 SE +/- 0.14257, N = 3 8.93657 MIN: 6.95 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU Ubuntu 19.04 5 10 15 20 25 SE +/- 0.02, N = 3 20.56 MIN: 19.44 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: Deconvolution Batch deconv_1d - Data Type: u8s8f32 - Engine: CPU Ubuntu 19.04 0.9905 1.981 2.9715 3.962 4.9525 SE +/- 0.08113, N = 15 4.40219 MIN: 3.98 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: Deconvolution Batch deconv_3d - Data Type: u8s8f32 - Engine: CPU Ubuntu 19.04 0.9674 1.9348 2.9022 3.8696 4.837 SE +/- 0.05187, N = 3 4.29952 MIN: 4.06 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU Ubuntu 19.04 100 200 300 400 500 SE +/- 7.32, N = 3 442.99 MIN: 421.25 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU Ubuntu 19.04 20 40 60 80 100 SE +/- 0.40, N = 3 111.61 MIN: 109.39 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU Ubuntu 19.04 0.4135 0.827 1.2405 1.654 2.0675 SE +/- 0.06760, N = 15 1.83780 MIN: 1 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU Ubuntu 19.04 0.3911 0.7822 1.1733 1.5644 1.9555 SE +/- 0.00231, N = 3 1.73814 MIN: 1.62 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
perf-bench OpenBenchmarking.org ops/sec, More Is Better perf-bench Benchmark: Epoll Wait Ubuntu 19.04 1400 2800 4200 5600 7000 SE +/- 106.51, N = 3 6511 1. (CC) gcc options: -pthread -shared -Xlinker -export-dynamic -O6 -ggdb3 -funwind-tables -std=gnu99 -lnuma
OpenBenchmarking.org ops/sec, More Is Better perf-bench Benchmark: Futex Hash Ubuntu 19.04 500K 1000K 1500K 2000K 2500K SE +/- 548.36, N = 3 2468188 1. (CC) gcc options: -pthread -shared -Xlinker -export-dynamic -O6 -ggdb3 -funwind-tables -std=gnu99 -lnuma
OpenBenchmarking.org GB/sec, More Is Better perf-bench Benchmark: Memcpy 1MB Ubuntu 19.04 4 8 12 16 20 SE +/- 0.03, N = 3 15.00 1. (CC) gcc options: -pthread -shared -Xlinker -export-dynamic -O6 -ggdb3 -funwind-tables -std=gnu99 -lnuma
OpenBenchmarking.org GB/sec, More Is Better perf-bench Benchmark: Memset 1MB Ubuntu 19.04 10 20 30 40 50 SE +/- 0.22, N = 3 42.00 1. (CC) gcc options: -pthread -shared -Xlinker -export-dynamic -O6 -ggdb3 -funwind-tables -std=gnu99 -lnuma
OpenBenchmarking.org ops/sec, More Is Better perf-bench Benchmark: Sched Pipe Ubuntu 19.04 60K 120K 180K 240K 300K SE +/- 2700.16, N = 3 263943 1. (CC) gcc options: -pthread -shared -Xlinker -export-dynamic -O6 -ggdb3 -funwind-tables -std=gnu99 -lnuma
OpenBenchmarking.org ops/sec, More Is Better perf-bench Benchmark: Futex Lock-Pi Ubuntu 19.04 30 60 90 120 150 SE +/- 1.13, N = 15 124 1. (CC) gcc options: -pthread -shared -Xlinker -export-dynamic -O6 -ggdb3 -funwind-tables -std=gnu99 -lnuma
OpenBenchmarking.org ops/sec, More Is Better perf-bench Benchmark: Syscall Basic Ubuntu 19.04 3M 6M 9M 12M 15M SE +/- 2524.94, N = 3 14977770 1. (CC) gcc options: -pthread -shared -Xlinker -export-dynamic -O6 -ggdb3 -funwind-tables -std=gnu99 -lnuma
SVT-AV1 This is a test of the Intel Open Visual Cloud Scalable Video Technology SVT-AV1 CPU-based multi-threaded video encoder for the AV1 video format with a sample 1080p YUV video file. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 0.8 Encoder Mode: Enc Mode 0 - Input: 1080p Ubuntu 19.04 0.0218 0.0436 0.0654 0.0872 0.109 SE +/- 0.000, N = 3 0.097 1. (CXX) g++ options: -O3 -fcommon -fPIE -fPIC -pie
OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 0.8 Encoder Mode: Enc Mode 4 - Input: 1080p Ubuntu 19.04 0.9533 1.9066 2.8599 3.8132 4.7665 SE +/- 0.057, N = 3 4.237 1. (CXX) g++ options: -O3 -fcommon -fPIE -fPIC -pie
OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 0.8 Encoder Mode: Enc Mode 8 - Input: 1080p Ubuntu 19.04 8 16 24 32 40 SE +/- 0.37, N = 3 36.92 1. (CXX) g++ options: -O3 -fcommon -fPIE -fPIC -pie
Ubuntu 19.04 Processor: AMD EPYC 7601 32-Core @ 2.20GHz (32 Cores / 64 Threads), Motherboard: TYAN B8026T70AE24HR (V1.02.B10 BIOS), Chipset: AMD 17h, Memory: 126GB, Disk: 280GB INTEL SSDPE21D280GA, Graphics: ASPEED, Monitor: VE228, Network: 2 x Broadcom NetXtreme BCM5720 PCIe
OS: Ubuntu 19.04, Kernel: 5.5.0-rc7-phx-k10temp6 (x86_64) 20200123, Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: modesetting 1.20.4, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 1920x1080
Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --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++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --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-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -vProcessor Notes: Scaling Governor: acpi-cpufreq ondemand - CPU Microcode: 0x8001227Python Notes: Python 2.7.16 + Python 3.7.3Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional STIBP: disabled RSB filling + tsx_async_abort: Not affected
Testing initiated at 7 September 2020 11:09 by user phoronix.