Intel Core i7-1165G7 testing with a Dell 0GG9PT (3.15.0 BIOS) and Intel Xe TGL GT2 15GB on Ubuntu 23.04 via the Phoronix Test Suite.
a Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-12-Pa930Z/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-Pa930Z/gcc-12-12.2.0/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-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 -vProcessor Notes: Scaling Governor: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0xa6 - Thermald 2.5.2Java Notes: OpenJDK Runtime Environment (build 11.0.19+7-post-Ubuntu-0ubuntu123.04)Security Notes: 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 Enhanced IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected
b c Processor: Intel Core i7-1165G7 @ 4.70GHz (4 Cores / 8 Threads), Motherboard: Dell 0GG9PT (3.15.0 BIOS), Chipset: Intel Tiger Lake-LP, Memory: 16GB, Disk: Kioxia KBG40ZNS256G NVMe 256GB, Graphics: Intel Xe TGL GT2 15GB (1300MHz), Audio: Realtek ALC289, Network: Intel Wi-Fi 6 AX201
OS: Ubuntu 23.04, Kernel: 6.2.0-24-generic (x86_64), Desktop: GNOME Shell 44.0, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 23.0.2, Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 1920x1200
OpenBenchmarking.org Average Latency, More Is Better Apache IoTDB 1.1.2 Device Count: 200 - Batch Size Per Write: 100 - Sensor Count: 500 c b a 160 320 480 640 800 757.34 370.36 284.41 MAX: 21117.8 MAX: 7948.19 MAX: 2551.38
OpenBenchmarking.org Average Latency, More Is Better Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 500 c a b 110 220 330 440 550 499.98 211.96 200.97 MAX: 7223.32 MAX: 1593.95 MAX: 1387.04
OpenBenchmarking.org Average Latency, More Is Better Apache IoTDB 1.1.2 Device Count: 200 - Batch Size Per Write: 100 - Sensor Count: 200 c a b 40 80 120 160 200 164.99 91.67 85.64 MAX: 11718.16 MAX: 7883.93 MAX: 1651.27
NCNN NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: blazeface b c a 0.297 0.594 0.891 1.188 1.485 SE +/- 0.02, N = 2 SE +/- 0.03, N = 2 SE +/- 0.03, N = 2 0.94 0.96 1.32 MIN: 0.9 / MAX: 1.09 MIN: 0.9 / MAX: 5.52 MIN: 1.2 / MAX: 4.08 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: regnety_400m c b a 3 6 9 12 15 SE +/- 0.01, N = 2 SE +/- 0.03, N = 2 SE +/- 0.10, N = 2 8.39 8.61 11.76 MIN: 8.14 / MAX: 18.42 MIN: 8.21 / MAX: 17.64 MIN: 11.26 / MAX: 22.16 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: efficientnet-b0 c b a 2 4 6 8 10 SE +/- 0.05, N = 2 SE +/- 0.04, N = 2 SE +/- 0.29, N = 2 6.64 6.92 8.85 MIN: 6.38 / MAX: 17.34 MIN: 6.5 / MAX: 16.04 MIN: 6.6 / MAX: 21.28 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: regnety_400m b c a 3 6 9 12 15 SE +/- 0.01, N = 2 SE +/- 1.13, N = 2 SE +/- 0.30, N = 2 8.57 9.62 11.19 MIN: 8.18 / MAX: 21.08 MIN: 8.23 / MAX: 23.19 MIN: 10.38 / MAX: 21.88 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Apache IoTDB OpenBenchmarking.org point/sec, More Is Better Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 200 a b c 5M 10M 15M 20M 25M 22588608.67 21253793.53 17612257.13
NCNN NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: googlenet c b a 4 8 12 16 20 SE +/- 0.27, N = 2 SE +/- 0.20, N = 2 SE +/- 0.07, N = 2 12.42 12.78 15.82 MIN: 11.68 / MAX: 23.37 MIN: 11.9 / MAX: 22.46 MIN: 15.12 / MAX: 28.62 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: blazeface b c a 0.2835 0.567 0.8505 1.134 1.4175 SE +/- 0.05, N = 2 SE +/- 0.14, N = 2 SE +/- 0.02, N = 2 0.99 1.08 1.26 MIN: 0.91 / MAX: 3.77 MIN: 0.91 / MAX: 3.75 MIN: 1.16 / MAX: 4.12 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: resnet18 c b a 3 6 9 12 15 SE +/- 0.50, N = 2 SE +/- 0.11, N = 2 SE +/- 0.04, N = 2 9.19 9.25 11.17 MIN: 8.38 / MAX: 20.09 MIN: 8.51 / MAX: 24.74 MIN: 10.66 / MAX: 21.33 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: mnasnet c b a 1.0238 2.0476 3.0714 4.0952 5.119 SE +/- 0.01, N = 2 SE +/- 0.07, N = 2 SE +/- 0.63, N = 2 3.83 3.86 4.55 MIN: 3.68 / MAX: 12.77 MIN: 3.69 / MAX: 12.48 MIN: 3.81 / MAX: 15.97 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: alexnet c b a 2 4 6 8 10 SE +/- 0.25, N = 2 SE +/- 0.09, N = 2 SE +/- 0.04, N = 2 7.30 7.43 8.61 MIN: 6.79 / MAX: 17.09 MIN: 6.9 / MAX: 16.46 MIN: 8.27 / MAX: 20.05 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: shufflenet-v2 b c a 0.9068 1.8136 2.7204 3.6272 4.534 SE +/- 0.01, N = 2 SE +/- 0.02, N = 2 SE +/- 0.57, N = 2 3.47 3.47 4.03 MIN: 3.32 / MAX: 12.41 MIN: 3.36 / MAX: 13.07 MIN: 3.35 / MAX: 10.89 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: googlenet c b a 4 8 12 16 20 SE +/- 1.79, N = 2 SE +/- 1.53, N = 2 SE +/- 0.02, N = 2 14.01 14.09 15.86 MIN: 11.83 / MAX: 25.65 MIN: 12.03 / MAX: 25.74 MIN: 15.16 / MAX: 26.57 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Apache IoTDB OpenBenchmarking.org Average Latency, More Is Better Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 200 c b a 20 40 60 80 100 76.87 74.08 68.48 MAX: 9168.34 MAX: 1547.17 MAX: 1696.56
Dragonflydb Dragonfly is an open-source database server that is a "modern Redis replacement" that aims to be the fastest memory store while being compliant with the Redis and Memcached protocols. For benchmarking Dragonfly, Memtier_benchmark is used as a NoSQL Redis/Memcache traffic generation plus benchmarking tool developed by Redis Labs. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Ops/sec, More Is Better Dragonflydb 1.6.2 Clients Per Thread: 20 - Set To Get Ratio: 1:100 c b a 400K 800K 1200K 1600K 2000K SE +/- 168860.22, N = 2 SE +/- 71249.46, N = 2 SE +/- 66621.90, N = 2 1655250.86 1532061.63 1504800.26 1. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre
NCNN NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: vision_transformer c b a 50 100 150 200 250 SE +/- 0.68, N = 2 SE +/- 0.73, N = 2 SE +/- 8.01, N = 2 188.79 193.90 207.46 MIN: 169.1 / MAX: 243.33 MIN: 167.64 / MAX: 231.56 MIN: 169.78 / MAX: 244.36 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: resnet18 b c a 3 6 9 12 15 SE +/- 1.05, N = 2 SE +/- 0.82, N = 2 SE +/- 0.02, N = 2 10.22 10.40 11.18 MIN: 8.49 / MAX: 20.91 MIN: 8.57 / MAX: 21.1 MIN: 10.62 / MAX: 21.34 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
VVenC VVenC is the Fraunhofer Versatile Video Encoder as a fast/efficient H.266/VVC encoder. The vvenc encoder makes use of SIMD Everywhere (SIMDe). The vvenc software is published under the Clear BSD License. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Frames Per Second, More Is Better VVenC 1.9 Video Input: Bosphorus 1080p - Video Preset: Faster c a b 4 8 12 16 20 SE +/- 0.79, N = 2 SE +/- 0.08, N = 2 SE +/- 0.11, N = 2 13.80 12.80 12.64 1. (CXX) g++ options: -O3 -flto=auto -fno-fat-lto-objects
NCNN NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: vgg16 c b a 13 26 39 52 65 SE +/- 2.37, N = 2 SE +/- 1.96, N = 2 SE +/- 0.11, N = 2 54.13 54.25 59.09 MIN: 48.55 / MAX: 72.36 MIN: 50.32 / MAX: 71.7 MIN: 57.54 / MAX: 76.29 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: resnet50 b c a 7 14 21 28 35 SE +/- 2.23, N = 2 SE +/- 2.20, N = 2 SE +/- 0.18, N = 2 26.57 26.57 28.74 MIN: 23.28 / MAX: 38.91 MIN: 23.37 / MAX: 38.7 MIN: 27.89 / MAX: 40 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: vision_transformer a c b 40 80 120 160 200 SE +/- 4.42, N = 2 SE +/- 5.48, N = 2 SE +/- 3.85, N = 2 189.40 200.23 204.36 MIN: 169.61 / MAX: 225.69 MIN: 169.16 / MAX: 234.64 MIN: 168.8 / MAX: 231.88 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: squeezenet_ssd c b a 3 6 9 12 15 SE +/- 0.97, N = 2 SE +/- 0.86, N = 2 SE +/- 0.03, N = 2 12.05 12.23 12.95 MIN: 10.72 / MAX: 23.89 MIN: 10.77 / MAX: 31.43 MIN: 12.67 / MAX: 23.3 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: alexnet b c a 2 4 6 8 10 SE +/- 0.52, N = 2 SE +/- 0.55, N = 2 SE +/- 0.04, N = 2 8.08 8.15 8.68 MIN: 7.01 / MAX: 17.55 MIN: 7.01 / MAX: 17.98 MIN: 8.25 / MAX: 19.5 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Apache IoTDB OpenBenchmarking.org Average Latency, More Is Better Apache IoTDB 1.1.2 Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 200 c b a 3 6 9 12 15 12.78 12.52 12.00 MAX: 800.68 MAX: 794.23 MAX: 771.24
Dragonflydb Dragonfly is an open-source database server that is a "modern Redis replacement" that aims to be the fastest memory store while being compliant with the Redis and Memcached protocols. For benchmarking Dragonfly, Memtier_benchmark is used as a NoSQL Redis/Memcache traffic generation plus benchmarking tool developed by Redis Labs. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Ops/sec, More Is Better Dragonflydb 1.6.2 Clients Per Thread: 10 - Set To Get Ratio: 1:5 c a b 300K 600K 900K 1200K 1500K SE +/- 156954.29, N = 2 SE +/- 124523.27, N = 2 SE +/- 115490.54, N = 2 1394989.58 1331051.90 1310891.48 1. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre
OpenBenchmarking.org Ops/sec, More Is Better Dragonflydb 1.6.2 Clients Per Thread: 20 - Set To Get Ratio: 1:10 c a b 300K 600K 900K 1200K 1500K SE +/- 153108.99, N = 2 SE +/- 93795.63, N = 2 SE +/- 144264.17, N = 2 1620928.16 1553942.49 1532531.22 1. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre
VVenC VVenC is the Fraunhofer Versatile Video Encoder as a fast/efficient H.266/VVC encoder. The vvenc encoder makes use of SIMD Everywhere (SIMDe). The vvenc software is published under the Clear BSD License. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Frames Per Second, More Is Better VVenC 1.9 Video Input: Bosphorus 4K - Video Preset: Faster c b a 0.8669 1.7338 2.6007 3.4676 4.3345 SE +/- 0.081, N = 2 SE +/- 0.014, N = 2 SE +/- 0.014, N = 2 3.853 3.781 3.680 1. (CXX) g++ options: -O3 -flto=auto -fno-fat-lto-objects
Apache IoTDB OpenBenchmarking.org Average Latency, More Is Better Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 200 a b c 4 8 12 16 20 16.78 16.41 16.03 MAX: 906.87 MAX: 1017.33 MAX: 1027.73
OpenBenchmarking.org Average Latency, More Is Better Apache IoTDB 1.1.2 Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 500 b c a 6 12 18 24 30 23.10 22.63 22.08 MAX: 906.47 MAX: 909.27 MAX: 863.43
Dragonflydb Dragonfly is an open-source database server that is a "modern Redis replacement" that aims to be the fastest memory store while being compliant with the Redis and Memcached protocols. For benchmarking Dragonfly, Memtier_benchmark is used as a NoSQL Redis/Memcache traffic generation plus benchmarking tool developed by Redis Labs. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Ops/sec, More Is Better Dragonflydb 1.6.2 Clients Per Thread: 10 - Set To Get Ratio: 1:10 c a b 300K 600K 900K 1200K 1500K SE +/- 143882.01, N = 2 SE +/- 119195.59, N = 2 SE +/- 90004.70, N = 2 1325104.13 1283252.40 1275557.39 1. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre
OpenBenchmarking.org Ops/sec, More Is Better Dragonflydb 1.6.2 Clients Per Thread: 20 - Set To Get Ratio: 1:5 a b c 300K 600K 900K 1200K 1500K SE +/- 138897.05, N = 2 SE +/- 146499.45, N = 2 SE +/- 157442.25, N = 2 1620397.17 1572424.89 1561730.49 1. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre
OpenBenchmarking.org Ops/sec, More Is Better Dragonflydb 1.6.2 Clients Per Thread: 50 - Set To Get Ratio: 1:5 c b a 300K 600K 900K 1200K 1500K SE +/- 148775.44, N = 2 SE +/- 81765.99, N = 2 SE +/- 35029.57, N = 2 1559859.23 1546553.32 1509161.50 1. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre
OpenBenchmarking.org Ops/sec, More Is Better Dragonflydb 1.6.2 Clients Per Thread: 50 - Set To Get Ratio: 1:100 a c b 300K 600K 900K 1200K 1500K SE +/- 113274.82, N = 2 SE +/- 65233.84, N = 2 SE +/- 98659.37, N = 2 1590238.43 1548401.54 1538729.61 1. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre
VkFFT OpenBenchmarking.org Benchmark Score, More Is Better VkFFT 1.2.31 Test: FFT + iFFT C2C multidimensional in single precision c a b 1100 2200 3300 4400 5500 SE +/- 9.00, N = 2 SE +/- 17.50, N = 2 SE +/- 6.50, N = 2 5087 4944 4937 1. (CXX) g++ options: -O3
Dragonflydb Dragonfly is an open-source database server that is a "modern Redis replacement" that aims to be the fastest memory store while being compliant with the Redis and Memcached protocols. For benchmarking Dragonfly, Memtier_benchmark is used as a NoSQL Redis/Memcache traffic generation plus benchmarking tool developed by Redis Labs. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Ops/sec, More Is Better Dragonflydb 1.6.2 Clients Per Thread: 10 - Set To Get Ratio: 1:100 b c a 300K 600K 900K 1200K 1500K SE +/- 95110.31, N = 2 SE +/- 141978.48, N = 2 SE +/- 117619.34, N = 2 1305698.48 1297415.25 1267626.25 1. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre
Apache IoTDB OpenBenchmarking.org point/sec, More Is Better Apache IoTDB 1.1.2 Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 500 a c b 400K 800K 1200K 1600K 2000K 1696504.02 1659495.29 1651562.36
NCNN NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: efficientnet-b0 c b a 2 4 6 8 10 SE +/- 0.15, N = 2 SE +/- 0.02, N = 2 SE +/- 0.02, N = 2 6.81 6.98 6.99 MIN: 6.42 / MAX: 17.77 MIN: 6.57 / MAX: 17.79 MIN: 6.55 / MAX: 16.31 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
VVenC VVenC is the Fraunhofer Versatile Video Encoder as a fast/efficient H.266/VVC encoder. The vvenc encoder makes use of SIMD Everywhere (SIMDe). The vvenc software is published under the Clear BSD License. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Frames Per Second, More Is Better VVenC 1.9 Video Input: Bosphorus 1080p - Video Preset: Fast c a b 1.181 2.362 3.543 4.724 5.905 SE +/- 0.115, N = 2 SE +/- 0.000, N = 2 SE +/- 0.008, N = 2 5.249 5.140 5.124 1. (CXX) g++ options: -O3 -flto=auto -fno-fat-lto-objects
NCNN NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: FastestDet b a c 0.9068 1.8136 2.7204 3.6272 4.534 SE +/- 0.00, N = 2 SE +/- 0.09, N = 2 SE +/- 0.10, N = 2 3.94 3.97 4.03 MIN: 3.73 / MAX: 12.78 MIN: 3.7 / MAX: 15.04 MIN: 3.74 / MAX: 10.51 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU-v3-v3 - Model: mobilenet-v3 c a b 0.8078 1.6156 2.4234 3.2312 4.039 SE +/- 0.00, N = 2 SE +/- 0.03, N = 2 SE +/- 0.04, N = 2 3.51 3.58 3.59 MIN: 3.32 / MAX: 11.83 MIN: 3.35 / MAX: 13.78 MIN: 3.37 / MAX: 14.17 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: FastestDet c b a 0.8933 1.7866 2.6799 3.5732 4.4665 SE +/- 0.03, N = 2 SE +/- 0.00, N = 2 SE +/- 0.00, N = 2 3.89 3.91 3.97 MIN: 3.67 / MAX: 13.73 MIN: 3.71 / MAX: 13.7 MIN: 3.76 / MAX: 14.59 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: mobilenet b c a 5 10 15 20 25 SE +/- 0.03, N = 2 SE +/- 0.03, N = 2 SE +/- 0.19, N = 2 20.65 20.69 21.07 MIN: 20.22 / MAX: 31.66 MIN: 20.24 / MAX: 31.31 MIN: 20.27 / MAX: 31.83 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: vgg16 b c a 13 26 39 52 65 SE +/- 1.40, N = 2 SE +/- 0.65, N = 2 SE +/- 0.15, N = 2 57.88 58.28 59.03 MIN: 52 / MAX: 70.84 MIN: 52.14 / MAX: 69.93 MIN: 57.6 / MAX: 79.49 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Dragonflydb Dragonfly is an open-source database server that is a "modern Redis replacement" that aims to be the fastest memory store while being compliant with the Redis and Memcached protocols. For benchmarking Dragonfly, Memtier_benchmark is used as a NoSQL Redis/Memcache traffic generation plus benchmarking tool developed by Redis Labs. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Ops/sec, More Is Better Dragonflydb 1.6.2 Clients Per Thread: 50 - Set To Get Ratio: 1:10 c a b 300K 600K 900K 1200K 1500K SE +/- 128692.32, N = 2 SE +/- 99951.62, N = 2 SE +/- 111709.66, N = 2 1574780.45 1559408.51 1545294.47 1. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre
VkFFT OpenBenchmarking.org Benchmark Score, More Is Better VkFFT 1.2.31 Test: FFT + iFFT R2C / C2R c b a 1200 2400 3600 4800 6000 SE +/- 69.00, N = 2 SE +/- 30.50, N = 2 SE +/- 3.50, N = 2 5688 5589 5585 1. (CXX) g++ options: -O3
NCNN NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3 c b a 0.81 1.62 2.43 3.24 4.05 SE +/- 0.01, N = 2 SE +/- 0.02, N = 2 SE +/- 0.03, N = 2 3.54 3.59 3.60 MIN: 3.33 / MAX: 11.68 MIN: 3.4 / MAX: 12.21 MIN: 3.38 / MAX: 12.52 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: yolov4-tiny c b a 7 14 21 28 35 SE +/- 0.05, N = 2 SE +/- 0.15, N = 2 SE +/- 0.26, N = 2 29.11 29.23 29.60 MIN: 28.38 / MAX: 40.39 MIN: 28.34 / MAX: 41.02 MIN: 28.6 / MAX: 44.5 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Apache IoTDB OpenBenchmarking.org Average Latency, More Is Better Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 500 b a c 6 12 18 24 30 25.14 24.98 24.73 MAX: 1026.24 MAX: 1064.56 MAX: 998.23
VVenC VVenC is the Fraunhofer Versatile Video Encoder as a fast/efficient H.266/VVC encoder. The vvenc encoder makes use of SIMD Everywhere (SIMDe). The vvenc software is published under the Clear BSD License. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Frames Per Second, More Is Better VVenC 1.9 Video Input: Bosphorus 4K - Video Preset: Fast c a b 0.3773 0.7546 1.1319 1.5092 1.8865 SE +/- 0.036, N = 2 SE +/- 0.037, N = 2 SE +/- 0.028, N = 2 1.677 1.654 1.650 1. (CXX) g++ options: -O3 -flto=auto -fno-fat-lto-objects
NCNN NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: mnasnet c b a 0.8843 1.7686 2.6529 3.5372 4.4215 SE +/- 0.04, N = 2 SE +/- 0.03, N = 2 SE +/- 0.01, N = 2 3.87 3.89 3.93 MIN: 3.71 / MAX: 12.28 MIN: 3.74 / MAX: 12.97 MIN: 3.73 / MAX: 14.41 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU-v2-v2 - Model: mobilenet-v2 c a b 1.035 2.07 3.105 4.14 5.175 SE +/- 0.02, N = 2 SE +/- 0.04, N = 2 SE +/- 0.02, N = 2 4.53 4.60 4.60 MIN: 4.3 / MAX: 15.17 MIN: 4.38 / MAX: 12.37 MIN: 4.34 / MAX: 14.83 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Apache IoTDB OpenBenchmarking.org point/sec, More Is Better Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 500 c a b 300K 600K 900K 1200K 1500K 1266283.94 1265418.91 1247796.00
NCNN NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: yolov4-tiny b c a 7 14 21 28 35 SE +/- 0.03, N = 2 SE +/- 0.03, N = 2 SE +/- 0.42, N = 2 29.03 29.25 29.44 MIN: 28.45 / MAX: 40.14 MIN: 28.42 / MAX: 40.16 MIN: 28.43 / MAX: 46.03 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2 c b a 1.0485 2.097 3.1455 4.194 5.2425 SE +/- 0.04, N = 2 SE +/- 0.03, N = 2 SE +/- 0.00, N = 2 4.60 4.63 4.66 MIN: 4.38 / MAX: 14 MIN: 4.44 / MAX: 14.09 MIN: 4.46 / MAX: 14.54 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: resnet50 b c a 7 14 21 28 35 SE +/- 0.12, N = 2 SE +/- 0.15, N = 2 SE +/- 0.19, N = 2 28.71 28.78 28.84 MIN: 27.9 / MAX: 39.22 MIN: 27.96 / MAX: 39.21 MIN: 27.92 / MAX: 41.94 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
NCNN NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: squeezenet_ssd c b a 3 6 9 12 15 SE +/- 0.03, N = 2 SE +/- 0.01, N = 2 SE +/- 0.04, N = 2 13.00 13.01 13.05 MIN: 12.68 / MAX: 23.98 MIN: 12.67 / MAX: 27.85 MIN: 12.7 / MAX: 23.56 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: shufflenet-v2 b c a 0.7875 1.575 2.3625 3.15 3.9375 SE +/- 0.01, N = 2 SE +/- 0.02, N = 2 SE +/- 0.01, N = 2 3.49 3.49 3.50 MIN: 3.33 / MAX: 13.62 MIN: 3.35 / MAX: 11.83 MIN: 3.35 / MAX: 12.33 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
BRL-CAD BRL-CAD is a cross-platform, open-source solid modeling system with built-in benchmark mode. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org VGR Performance Metric, More Is Better BRL-CAD 7.36 VGR Performance Metric a b c 11K 22K 33K 44K 55K SE +/- 16.50, N = 2 SE +/- 147.00, N = 2 SE +/- 34.00, N = 2 52008 51967 51880 1. (CXX) g++ options: -std=c++14 -pipe -fvisibility=hidden -fno-strict-aliasing -fno-common -fexceptions -ftemplate-depth-128 -m64 -ggdb3 -O3 -fipa-pta -fstrength-reduce -finline-functions -flto -ltcl8.6 -lregex_brl -lz_brl -lnetpbm -ldl -lm -ltk8.6
VkFFT OpenBenchmarking.org Benchmark Score, More Is Better VkFFT 1.2.31 Test: FFT + iFFT C2C Bluestein in single precision c b a 200 400 600 800 1000 SE +/- 1.00, N = 2 SE +/- 1.00, N = 2 SE +/- 0.50, N = 2 1035 1034 1033 1. (CXX) g++ options: -O3
OpenBenchmarking.org Benchmark Score, More Is Better VkFFT 1.2.31 Test: FFT + iFFT C2C 1D batched in single precision a b c 1600 3200 4800 6400 8000 SE +/- 14.00, N = 2 SE +/- 4.00, N = 2 SE +/- 3.50, N = 2 7486 7482 7478 1. (CXX) g++ options: -O3
OpenBenchmarking.org Benchmark Score, More Is Better VkFFT 1.2.31 Test: FFT + iFFT C2C 1D batched in half precision a c b 3K 6K 9K 12K 15K SE +/- 5.00, N = 2 SE +/- 4.00, N = 2 SE +/- 1.50, N = 2 14246 14241 14232 1. (CXX) g++ options: -O3
OpenBenchmarking.org Benchmark Score, More Is Better VkFFT 1.2.31 Test: FFT + iFFT C2C 1D batched in single precision, no reshuffling c b a 2K 4K 6K 8K 10K SE +/- 5.00, N = 2 SE +/- 0.50, N = 2 SE +/- 4.00, N = 2 8183 8176 8176 1. (CXX) g++ options: -O3
NCNN NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: mobilenet a b c 5 10 15 20 25 SE +/- 0.05, N = 2 SE +/- 0.04, N = 2 SE +/- 0.07, N = 2 20.74 20.74 20.74 MIN: 20.17 / MAX: 31.42 MIN: 20.23 / MAX: 31.9 MIN: 20.26 / MAX: 32.28 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
VkFFT Test: FFT + iFFT C2C Bluestein benchmark in double precision
a: The test quit with a non-zero exit status.
b: The test quit with a non-zero exit status.
c: The test quit with a non-zero exit status.
Test: FFT + iFFT C2C 1D batched in double precision
a: The test quit with a non-zero exit status.
b: The test quit with a non-zero exit status.
c: The test quit with a non-zero exit status.
a Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-12-Pa930Z/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-Pa930Z/gcc-12-12.2.0/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-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 -vProcessor Notes: Scaling Governor: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0xa6 - Thermald 2.5.2Java Notes: OpenJDK Runtime Environment (build 11.0.19+7-post-Ubuntu-0ubuntu123.04)Security Notes: 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 Enhanced IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 3 August 2023 14:30 by user phoronix.
b Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-12-Pa930Z/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-Pa930Z/gcc-12-12.2.0/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-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 -vProcessor Notes: Scaling Governor: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0xa6 - Thermald 2.5.2Java Notes: OpenJDK Runtime Environment (build 11.0.19+7-post-Ubuntu-0ubuntu123.04)Security Notes: 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 Enhanced IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 3 August 2023 18:07 by user phoronix.
c Processor: Intel Core i7-1165G7 @ 4.70GHz (4 Cores / 8 Threads), Motherboard: Dell 0GG9PT (3.15.0 BIOS), Chipset: Intel Tiger Lake-LP, Memory: 16GB, Disk: Kioxia KBG40ZNS256G NVMe 256GB, Graphics: Intel Xe TGL GT2 15GB (1300MHz), Audio: Realtek ALC289, Network: Intel Wi-Fi 6 AX201
OS: Ubuntu 23.04, Kernel: 6.2.0-24-generic (x86_64), Desktop: GNOME Shell 44.0, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 23.0.2, Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 1920x1200
Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-12-Pa930Z/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-Pa930Z/gcc-12-12.2.0/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-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 -vProcessor Notes: Scaling Governor: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0xa6 - Thermald 2.5.2Java Notes: OpenJDK Runtime Environment (build 11.0.19+7-post-Ubuntu-0ubuntu123.04)Security Notes: 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 Enhanced IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 3 August 2023 21:36 by user phoronix.