lfld 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/2404067-NE-LFLD4610042&grw&sro .
lfld Processor Motherboard Chipset Memory Disk Graphics Audio Monitor Network OS Kernel Desktop Display Server OpenGL Vulkan Compiler File-System Screen Resolution a b c 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 (1750/875MHz) AMD Navi 10 HDMI Audio ASUS VP28U Aquantia AQC107 NBase-T/IEEE + Intel I211 + Intel Wi-Fi 6 AX200 Ubuntu 22.04 6.5.0-25-generic (x86_64) GNOME Shell 42.2 X Server + Wayland 4.6 Mesa 22.0.1 (LLVM 13.0.1 DRM 3.54) 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 Python Details - Python 3.10.12 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 + 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 + srbds: Not affected + tsx_async_abort: Not affected
lfld brl-cad: VGR Performance Metric tensorflow: CPU - 1 - AlexNet tensorflow: CPU - 16 - AlexNet tensorflow: CPU - 32 - AlexNet tensorflow: CPU - 64 - AlexNet tensorflow: CPU - 1 - GoogLeNet tensorflow: CPU - 1 - ResNet-50 tensorflow: CPU - 256 - AlexNet tensorflow: CPU - 16 - GoogLeNet tensorflow: CPU - 16 - ResNet-50 tensorflow: CPU - 32 - GoogLeNet tensorflow: CPU - 32 - ResNet-50 tensorflow: CPU - 64 - GoogLeNet tensorflow: CPU - 64 - ResNet-50 tensorflow: CPU - 256 - GoogLeNet tensorflow: CPU - 256 - ResNet-50 pytorch: CPU - 1 - ResNet-50 pytorch: CPU - 1 - ResNet-152 pytorch: CPU - 16 - ResNet-50 pytorch: CPU - 32 - ResNet-50 pytorch: CPU - 64 - ResNet-50 pytorch: CPU - 16 - ResNet-152 pytorch: CPU - 32 - ResNet-152 pytorch: CPU - 64 - ResNet-152 pytorch: CPU - 1 - Efficientnet_v2_l pytorch: CPU - 16 - Efficientnet_v2_l pytorch: CPU - 32 - Efficientnet_v2_l pytorch: CPU - 64 - Efficientnet_v2_l llamafile: llava-v1.5-7b-q4 - CPU llamafile: mistral-7b-instruct-v0.2.Q8_0 - CPU llamafile: wizardcoder-python-34b-v1.0.Q6_K - CPU build-ffmpeg: Time To Compile stockfish: Chess Benchmark x265: Bosphorus 4K x265: Bosphorus 1080p blender: BMW27 - CPU-Only blender: Junkshop - CPU-Only blender: Classroom - CPU-Only blender: Fishy Cat - CPU-Only blender: Barbershop - CPU-Only blender: Pabellon Barcelona - CPU-Only ffmpeg: libx264 - Live ffmpeg: libx265 - Live ffmpeg: libx264 - Upload ffmpeg: libx265 - Upload ffmpeg: libx264 - Platform ffmpeg: libx265 - Platform ffmpeg: libx264 - Video On Demand ffmpeg: libx265 - Video On Demand build-mesa: Time To Compile rocksdb: Overwrite rocksdb: Rand Fill rocksdb: Rand Read rocksdb: Update Rand rocksdb: Seq Fill rocksdb: Rand Fill Sync rocksdb: Read While Writing rocksdb: Read Rand Write Rand a b c 520682 9.37 59.39 77.71 99.75 11.17 7.58 131.52 47.61 13.31 51.17 13.95 52.21 14.01 51.24 15.29 36.04 14.10 30.34 30.43 30.09 11.69 11.66 11.53 7.82 5.94 5.93 5.92 15.7 10.33 3.05 31.104 60626388 24.55 45.31 42.71 63.19 115.6 53.41 440.72 135.1 192.88 68.63 12.31 13.56 46.41 28.17 46.43 28.14 15.846 382834 384236 122971162 535854 391130 5689 6378204 3157205 522046 9.28 59.16 76.7 99.54 11.18 7.6 131.69 47.95 13.4 51.37 14.07 51.43 14.02 51.1 15.26 34.83 14.03 30.16 29.44 29.73 11.70 11.56 11.54 7.75 5.96 5.90 5.92 15.79 10.42 3.06 30.829 59422978 24.39 45.57 42.62 63.6 116.23 53.48 443.49 135.77 190.36 67.94 12.27 13.56 46.37 28.05 46.53 28.05 15.799 379919 384641 122722305 545830 391156 5637 6342025 3170105 518977 9.34 58.03 76.07 100.26 11.09 7.46 131.83 47.32 13.14 51.87 13.93 51.79 14.07 50.99 15.32 35.36 13.98 30.56 30.14 30.14 11.72 11.52 11.47 7.73 5.93 5.90 5.94 15.7 10.35 3.05 30.948 57142188 24.45 45 42.52 64 116.67 53.89 440.39 135.16 191.03 67.71 12.33 13.53 46.47 28.09 46.51 28.03 15.746 382424 382241 125016375 545086 390464 5511 6326219 3162012 OpenBenchmarking.org
BRL-CAD VGR Performance Metric OpenBenchmarking.org VGR Performance Metric, More Is Better BRL-CAD 7.38.2 VGR Performance Metric a b c 110K 220K 330K 440K 550K 520682 522046 518977 1. (CXX) g++ options: -std=c++17 -pipe -fvisibility=hidden -fno-strict-aliasing -fno-common -fexceptions -ftemplate-depth-128 -m64 -ggdb3 -O3 -fipa-pta -fstrength-reduce -finline-functions -flto -ltcl8.6 -lnetpbm -lregex_brl -lz_brl -lassimp -ldl -lm -ltk8.6
TensorFlow Device: CPU - Batch Size: 1 - Model: AlexNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 1 - Model: AlexNet a b c 3 6 9 12 15 9.37 9.28 9.34
TensorFlow Device: CPU - Batch Size: 16 - Model: AlexNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 16 - Model: AlexNet a b c 13 26 39 52 65 59.39 59.16 58.03
TensorFlow Device: CPU - Batch Size: 32 - Model: AlexNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 32 - Model: AlexNet a b c 20 40 60 80 100 77.71 76.70 76.07
TensorFlow Device: CPU - Batch Size: 64 - Model: AlexNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 64 - Model: AlexNet a b c 20 40 60 80 100 99.75 99.54 100.26
TensorFlow Device: CPU - Batch Size: 1 - Model: GoogLeNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 1 - Model: GoogLeNet a b c 3 6 9 12 15 11.17 11.18 11.09
TensorFlow Device: CPU - Batch Size: 1 - Model: ResNet-50 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 a b c 2 4 6 8 10 7.58 7.60 7.46
TensorFlow Device: CPU - Batch Size: 256 - Model: AlexNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 256 - Model: AlexNet a b c 30 60 90 120 150 131.52 131.69 131.83
TensorFlow Device: CPU - Batch Size: 16 - Model: GoogLeNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 16 - Model: GoogLeNet a b c 11 22 33 44 55 47.61 47.95 47.32
TensorFlow Device: CPU - Batch Size: 16 - Model: ResNet-50 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 16 - Model: ResNet-50 a b c 3 6 9 12 15 13.31 13.40 13.14
TensorFlow Device: CPU - Batch Size: 32 - Model: GoogLeNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 32 - Model: GoogLeNet a b c 12 24 36 48 60 51.17 51.37 51.87
TensorFlow Device: CPU - Batch Size: 32 - Model: ResNet-50 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 32 - Model: ResNet-50 a b c 4 8 12 16 20 13.95 14.07 13.93
TensorFlow Device: CPU - Batch Size: 64 - Model: GoogLeNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 64 - Model: GoogLeNet a b c 12 24 36 48 60 52.21 51.43 51.79
TensorFlow Device: CPU - Batch Size: 64 - Model: ResNet-50 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 64 - Model: ResNet-50 a b c 4 8 12 16 20 14.01 14.02 14.07
TensorFlow Device: CPU - Batch Size: 256 - Model: GoogLeNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 256 - Model: GoogLeNet a b c 12 24 36 48 60 51.24 51.10 50.99
TensorFlow Device: CPU - Batch Size: 256 - Model: ResNet-50 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 256 - Model: ResNet-50 a b c 4 8 12 16 20 15.29 15.26 15.32
PyTorch Device: CPU - Batch Size: 1 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 a b c 8 16 24 32 40 36.04 34.83 35.36 MIN: 35.37 / MAX: 36.38 MIN: 33.83 / MAX: 35.56 MIN: 34.11 / MAX: 35.87
PyTorch Device: CPU - Batch Size: 1 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 1 - Model: ResNet-152 a b c 4 8 12 16 20 14.10 14.03 13.98 MIN: 14.02 / MAX: 14.26 MIN: 13.81 / MAX: 14.13 MIN: 13.81 / MAX: 14.1
PyTorch Device: CPU - Batch Size: 16 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 16 - Model: ResNet-50 a b c 7 14 21 28 35 30.34 30.16 30.56 MIN: 28.23 / MAX: 30.9 MIN: 29.46 / MAX: 30.57 MIN: 30.05 / MAX: 30.85
PyTorch Device: CPU - Batch Size: 32 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 32 - Model: ResNet-50 a b c 7 14 21 28 35 30.43 29.44 30.14 MIN: 29.92 / MAX: 30.77 MIN: 28.71 / MAX: 29.78 MIN: 27.74 / MAX: 30.47
PyTorch Device: CPU - Batch Size: 64 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 64 - Model: ResNet-50 a b c 7 14 21 28 35 30.09 29.73 30.14 MIN: 28.19 / MAX: 30.53 MIN: 29.08 / MAX: 30.16 MIN: 29.4 / MAX: 30.57
PyTorch Device: CPU - Batch Size: 16 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 16 - Model: ResNet-152 a b c 3 6 9 12 15 11.69 11.70 11.72 MIN: 11.45 / MAX: 11.76 MIN: 11.52 / MAX: 11.79 MIN: 10.4 / MAX: 11.89
PyTorch Device: CPU - Batch Size: 32 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 32 - Model: ResNet-152 a b c 3 6 9 12 15 11.66 11.56 11.52 MIN: 11.44 / MAX: 11.83 MIN: 11.37 / MAX: 11.68 MIN: 11.43 / MAX: 11.62
PyTorch Device: CPU - Batch Size: 64 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 64 - Model: ResNet-152 a b c 3 6 9 12 15 11.53 11.54 11.47 MIN: 11.4 / MAX: 11.63 MIN: 11.39 / MAX: 11.67 MIN: 11.36 / MAX: 11.54
PyTorch Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l a b c 2 4 6 8 10 7.82 7.75 7.73 MIN: 7.73 / MAX: 7.91 MIN: 7.54 / MAX: 7.82 MIN: 7.63 / MAX: 7.82
PyTorch Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l a b c 1.341 2.682 4.023 5.364 6.705 5.94 5.96 5.93 MIN: 5.89 / MAX: 6.01 MIN: 5.92 / MAX: 6.01 MIN: 5.82 / MAX: 6
PyTorch Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l a b c 1.3343 2.6686 4.0029 5.3372 6.6715 5.93 5.90 5.90 MIN: 5.89 / MAX: 5.97 MIN: 5.82 / MAX: 5.93 MIN: 5.85 / MAX: 5.93
PyTorch Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l a b c 1.3365 2.673 4.0095 5.346 6.6825 5.92 5.92 5.94 MIN: 5.88 / MAX: 5.94 MIN: 5.88 / MAX: 5.95 MIN: 5.9 / MAX: 5.97
Llamafile Test: llava-v1.5-7b-q4 - Acceleration: CPU OpenBenchmarking.org Tokens Per Second, More Is Better Llamafile 0.7 Test: llava-v1.5-7b-q4 - Acceleration: CPU a b c 4 8 12 16 20 15.70 15.79 15.70
Llamafile Test: mistral-7b-instruct-v0.2.Q8_0 - Acceleration: CPU OpenBenchmarking.org Tokens Per Second, More Is Better Llamafile 0.7 Test: mistral-7b-instruct-v0.2.Q8_0 - Acceleration: CPU a b c 3 6 9 12 15 10.33 10.42 10.35
Llamafile Test: wizardcoder-python-34b-v1.0.Q6_K - Acceleration: CPU OpenBenchmarking.org Tokens Per Second, More Is Better Llamafile 0.7 Test: wizardcoder-python-34b-v1.0.Q6_K - Acceleration: CPU a b c 0.6885 1.377 2.0655 2.754 3.4425 3.05 3.06 3.05
Timed FFmpeg Compilation Time To Compile OpenBenchmarking.org Seconds, Fewer Is Better Timed FFmpeg Compilation 7.0 Time To Compile a b c 7 14 21 28 35 31.10 30.83 30.95
Stockfish Chess Benchmark OpenBenchmarking.org Nodes Per Second, More Is Better Stockfish 16.1 Chess Benchmark a b c 13M 26M 39M 52M 65M 60626388 59422978 57142188 1. (CXX) g++ options: -lgcov -m64 -lpthread -fno-exceptions -std=c++17 -fno-peel-loops -fno-tracer -pedantic -O3 -funroll-loops -msse -msse3 -mpopcnt -mavx2 -mbmi -msse4.1 -mssse3 -msse2 -flto -flto-partition=one -flto=jobserver
x265 Video Input: Bosphorus 4K OpenBenchmarking.org Frames Per Second, More Is Better x265 3.6 Video Input: Bosphorus 4K a b c 6 12 18 24 30 24.55 24.39 24.45 1. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma
x265 Video Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better x265 3.6 Video Input: Bosphorus 1080p a b c 10 20 30 40 50 45.31 45.57 45.00 1. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma
Blender Blend File: BMW27 - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 4.1 Blend File: BMW27 - Compute: CPU-Only a b c 10 20 30 40 50 42.71 42.62 42.52
Blender Blend File: Junkshop - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 4.1 Blend File: Junkshop - Compute: CPU-Only a b c 14 28 42 56 70 63.19 63.60 64.00
Blender Blend File: Classroom - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 4.1 Blend File: Classroom - Compute: CPU-Only a b c 30 60 90 120 150 115.60 116.23 116.67
Blender Blend File: Fishy Cat - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 4.1 Blend File: Fishy Cat - Compute: CPU-Only a b c 12 24 36 48 60 53.41 53.48 53.89
Blender Blend File: Barbershop - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 4.1 Blend File: Barbershop - Compute: CPU-Only a b c 100 200 300 400 500 440.72 443.49 440.39
Blender Blend File: Pabellon Barcelona - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 4.1 Blend File: Pabellon Barcelona - Compute: CPU-Only a b c 30 60 90 120 150 135.10 135.77 135.16
FFmpeg Encoder: libx264 - Scenario: Live OpenBenchmarking.org FPS, More Is Better FFmpeg 7.0 Encoder: libx264 - Scenario: Live a b c 40 80 120 160 200 192.88 190.36 191.03 1. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma
FFmpeg Encoder: libx265 - Scenario: Live OpenBenchmarking.org FPS, More Is Better FFmpeg 7.0 Encoder: libx265 - Scenario: Live a b c 15 30 45 60 75 68.63 67.94 67.71 1. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma
FFmpeg Encoder: libx264 - Scenario: Upload OpenBenchmarking.org FPS, More Is Better FFmpeg 7.0 Encoder: libx264 - Scenario: Upload a b c 3 6 9 12 15 12.31 12.27 12.33 1. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma
FFmpeg Encoder: libx265 - Scenario: Upload OpenBenchmarking.org FPS, More Is Better FFmpeg 7.0 Encoder: libx265 - Scenario: Upload a b c 3 6 9 12 15 13.56 13.56 13.53 1. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma
FFmpeg Encoder: libx264 - Scenario: Platform OpenBenchmarking.org FPS, More Is Better FFmpeg 7.0 Encoder: libx264 - Scenario: Platform a b c 11 22 33 44 55 46.41 46.37 46.47 1. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma
FFmpeg Encoder: libx265 - Scenario: Platform OpenBenchmarking.org FPS, More Is Better FFmpeg 7.0 Encoder: libx265 - Scenario: Platform a b c 7 14 21 28 35 28.17 28.05 28.09 1. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma
FFmpeg Encoder: libx264 - Scenario: Video On Demand OpenBenchmarking.org FPS, More Is Better FFmpeg 7.0 Encoder: libx264 - Scenario: Video On Demand a b c 11 22 33 44 55 46.43 46.53 46.51 1. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma
FFmpeg Encoder: libx265 - Scenario: Video On Demand OpenBenchmarking.org FPS, More Is Better FFmpeg 7.0 Encoder: libx265 - Scenario: Video On Demand a b c 7 14 21 28 35 28.14 28.05 28.03 1. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma
Timed Mesa Compilation Time To Compile OpenBenchmarking.org Seconds, Fewer Is Better Timed Mesa Compilation 24.0 Time To Compile a b c 4 8 12 16 20 15.85 15.80 15.75
RocksDB Test: Overwrite OpenBenchmarking.org Op/s, More Is Better RocksDB 9.0 Test: Overwrite a b c 80K 160K 240K 320K 400K 382834 379919 382424 1. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread
RocksDB Test: Random Fill OpenBenchmarking.org Op/s, More Is Better RocksDB 9.0 Test: Random Fill a b c 80K 160K 240K 320K 400K 384236 384641 382241 1. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread
RocksDB Test: Random Read OpenBenchmarking.org Op/s, More Is Better RocksDB 9.0 Test: Random Read a b c 30M 60M 90M 120M 150M 122971162 122722305 125016375 1. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread
RocksDB Test: Update Random OpenBenchmarking.org Op/s, More Is Better RocksDB 9.0 Test: Update Random a b c 120K 240K 360K 480K 600K 535854 545830 545086 1. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread
RocksDB Test: Sequential Fill OpenBenchmarking.org Op/s, More Is Better RocksDB 9.0 Test: Sequential Fill a b c 80K 160K 240K 320K 400K 391130 391156 390464 1. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread
RocksDB Test: Random Fill Sync OpenBenchmarking.org Op/s, More Is Better RocksDB 9.0 Test: Random Fill Sync a b c 1200 2400 3600 4800 6000 5689 5637 5511 1. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread
RocksDB Test: Read While Writing OpenBenchmarking.org Op/s, More Is Better RocksDB 9.0 Test: Read While Writing a b c 1.4M 2.8M 4.2M 5.6M 7M 6378204 6342025 6326219 1. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread
RocksDB Test: Read Random Write Random OpenBenchmarking.org Op/s, More Is Better RocksDB 9.0 Test: Read Random Write Random a b c 700K 1400K 2100K 2800K 3500K 3157205 3170105 3162012 1. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread
Phoronix Test Suite v10.8.5