Intel Core i7-1185G7 testing with a Dell XPS 13 9310 0DXP1F (3.7.0 BIOS) and Intel Xe TGL GT2 15GB on Ubuntu 23.10 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 2402202-NE-TGLTGL07808 tgl tgl - Phoronix Test Suite tgl tgl Intel Core i7-1185G7 testing with a Dell XPS 13 9310 0DXP1F (3.7.0 BIOS) and Intel Xe TGL GT2 15GB on Ubuntu 23.10 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2402202-NE-TGLTGL07808&grt&sro .
tgl tgl Processor Motherboard Chipset Memory Disk Graphics Audio Network OS Kernel Desktop Display Server OpenGL OpenCL Compiler File-System Screen Resolution a b c Intel Core i7-1185G7 @ 4.80GHz (4 Cores / 8 Threads) Dell XPS 13 9310 0DXP1F (3.7.0 BIOS) Intel Tiger Lake-LP 8 x 2GB LPDDR4-4267MT/s Micron 2300 NVMe 512GB Intel Xe TGL GT2 15GB (1350MHz) Realtek ALC289 Intel Wi-Fi 6 AX201 Ubuntu 23.10 6.7.0-060700rc5-generic (x86_64) GNOME Shell 45.1 X Server + Wayland 4.6 Mesa 24.0~git2312220600.68c53e~oibaf~m (git-68c53ec 2023-12-22 mantic-oibaf-ppa) OpenCL 3.0 GCC 13.2.0 ext4 1920x1200 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,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-defaulted --enable-offload-targets=nvptx-none=/build/gcc-13-XYspKM/gcc-13-13.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-13-XYspKM/gcc-13-13.2.0/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: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0xb4 - Thermald 2.5.4 Python Details - Python 3.11.6 Security Details - gather_data_sampling: Mitigation of Microcode + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_rstack_overflow: 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 / Automatic IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected
tgl tgl cachebench: Read cachebench: Write cachebench: Read / Modify / Write dav1d: Chimera 1080p dav1d: Summer Nature 4K dav1d: Summer Nature 1080p dav1d: Chimera 1080p 10-bit gromacs: MPI CPU - water_GMX50_bare oidn: RT.hdr_alb_nrm.3840x2160 - CPU-Only oidn: RT.ldr_alb_nrm.3840x2160 - CPU-Only oidn: RTLightmap.hdr.4096x4096 - CPU-Only libplacebo: deband_heavy libplacebo: polar_nocompute libplacebo: hdr_peakdetect libplacebo: hdr_lut libplacebo: av1_grain_lap libplacebo: gaussian llama-cpp: llama-2-7b.Q4_0.gguf llama-cpp: llama-2-13b.Q4_0.gguf llama-cpp: llama-2-70b-chat.Q5_0.gguf 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 compress-lz4: 1 - Compression Speed compress-lz4: 1 - Decompression Speed compress-lz4: 3 - Compression Speed compress-lz4: 3 - Decompression Speed compress-lz4: 9 - Compression Speed compress-lz4: 9 - Decompression Speed namd: ATPase with 327,506 Atoms namd: STMV with 1,066,628 Atoms onnx: GPT-2 - CPU - Parallel onnx: GPT-2 - CPU - Parallel onnx: GPT-2 - CPU - Standard onnx: GPT-2 - CPU - Standard onnx: yolov4 - CPU - Parallel onnx: yolov4 - CPU - Parallel onnx: yolov4 - CPU - Standard onnx: yolov4 - CPU - Standard onnx: T5 Encoder - CPU - Parallel onnx: T5 Encoder - CPU - Parallel onnx: T5 Encoder - CPU - Standard onnx: T5 Encoder - CPU - Standard onnx: bertsquad-12 - CPU - Parallel onnx: bertsquad-12 - CPU - Parallel onnx: bertsquad-12 - CPU - Standard onnx: bertsquad-12 - CPU - Standard onnx: CaffeNet 12-int8 - CPU - Parallel onnx: CaffeNet 12-int8 - CPU - Parallel onnx: CaffeNet 12-int8 - CPU - Standard onnx: CaffeNet 12-int8 - CPU - Standard onnx: fcn-resnet101-11 - CPU - Parallel onnx: fcn-resnet101-11 - CPU - Parallel onnx: fcn-resnet101-11 - CPU - Standard onnx: fcn-resnet101-11 - CPU - Standard onnx: ArcFace ResNet-100 - CPU - Parallel onnx: ArcFace ResNet-100 - CPU - Parallel onnx: ArcFace ResNet-100 - CPU - Standard onnx: ArcFace ResNet-100 - CPU - Standard onnx: ResNet50 v1-12-int8 - CPU - Parallel onnx: ResNet50 v1-12-int8 - CPU - Parallel onnx: ResNet50 v1-12-int8 - CPU - Standard onnx: ResNet50 v1-12-int8 - CPU - Standard onnx: super-resolution-10 - CPU - Parallel onnx: super-resolution-10 - CPU - Parallel onnx: super-resolution-10 - CPU - Standard onnx: super-resolution-10 - CPU - Standard onnx: Faster R-CNN R-50-FPN-int8 - CPU - Parallel onnx: Faster R-CNN R-50-FPN-int8 - CPU - Parallel onnx: Faster R-CNN R-50-FPN-int8 - CPU - Standard onnx: Faster R-CNN R-50-FPN-int8 - CPU - Standard vkfft: FFT + iFFT R2C / C2R vkfft: FFT + iFFT C2C 1D batched in half precision vkfft: FFT + iFFT C2C Bluestein in single precision vkfft: FFT + iFFT C2C 1D batched in single precision vkfft: FFT + iFFT C2C multidimensional in single precision vkfft: FFT + iFFT C2C 1D batched in single precision, no reshuffling a b c 8945.279885 109630.165987 103769.795772 403.43 92.92 325.6 296.56 0.573 0.15 0.16 0.07 78.22 151.38 336.77 371.63 405.16 370.73 7.37 3.84 0.03 7.07 4.26 0.05 755.41 4114.5 118.71 3850.6 41.13 4072.4 0.54640 0.16793 81.6105 12.2437 105.486 9.47309 2.89643 345.249 5.06166 197.56 90.9185 10.9972 146.861 6.80604 4.25933 234.775 6.90025 144.917 239.585 4.17219 333.924 2.99315 0.471017 2123.06 0.686147 1457.41 9.98691 100.13 14.919 67.0264 99.2785 10.0709 129.167 7.73997 26.964 37.0844 45.3275 22.0582 20.9179 47.8033 37.0478 26.9892 6310 13702 1112 7500 5869 8510 8946.160249 109813.145754 104513.363289 405.66 102.65 409.89 296.79 0.57 0.15 0.16 0.07 78.16 151.42 254.33 371.86 405.8 370.69 7.41 3.84 0.03 7.09 4.28 0.05 754.76 4123.5 119.04 3870.7 41.16 4077 0.55272 0.16810 77.2022 12.9464 101.597 9.83571 3.25429 307.283 4.72968 211.427 89.8118 11.1326 146.716 6.8134 4.8325 206.929 6.38547 156.599 238.164 4.19665 350.1 2.85482 0.415642 2405.91 0.753919 1326.4 8.98048 111.351 16.309 61.3135 98.4877 10.1511 129.057 7.74651 28.3989 35.2102 47.0396 21.2551 21.6011 46.2908 37.4595 26.6926 6146 13923 1116 7495 5952 8503 8946.289183 109693.870056 104746.114943 401.11 94.69 381.24 297.27 0.563 0.15 0.16 0.07 78.1 151.27 274.71 371.35 403.9 370.58 7.43 3.84 0.03 7.12 4.27 0.05 752.43 4139.1 117.87 3857.8 40.77 4080 0.53465 0.16812 83.3538 11.987 104.916 9.52371 3.12461 320.036 4.91617 203.406 89.5594 11.1641 147.496 6.77737 3.977 251.442 6.83843 146.226 240.221 4.16112 328.363 3.04357 0.462395 2162.65 0.680886 1468.67 10.1948 98.0872 14.8006 67.5622 97.333 10.2724 128.378 7.78713 28.2518 35.3934 42.8106 23.3554 23.1944 43.1113 35.5514 28.1255 6198 13748 1111 7496 5843 8506 OpenBenchmarking.org
CacheBench Test: Read OpenBenchmarking.org MB/s, More Is Better CacheBench Test: Read a b c 2K 4K 6K 8K 10K 8945.28 8946.16 8946.29 MIN: 8942.72 / MAX: 8947.89 MIN: 8944.76 / MAX: 8946.98 MIN: 8939.89 / MAX: 8948.19 1. (CC) gcc options: -O3 -lrt
CacheBench Test: Write OpenBenchmarking.org MB/s, More Is Better CacheBench Test: Write a b c 20K 40K 60K 80K 100K 109630.17 109813.15 109693.87 MIN: 78349.8 / MAX: 127046.33 MIN: 78789.09 / MAX: 126929.16 MIN: 78492.75 / MAX: 127175.97 1. (CC) gcc options: -O3 -lrt
CacheBench Test: Read / Modify / Write OpenBenchmarking.org MB/s, More Is Better CacheBench Test: Read / Modify / Write a b c 20K 40K 60K 80K 100K 103769.80 104513.36 104746.11 MIN: 79762.44 / MAX: 113377.99 MIN: 83065.75 / MAX: 113865.39 MIN: 80807.87 / MAX: 113668.22 1. (CC) gcc options: -O3 -lrt
dav1d Video Input: Chimera 1080p OpenBenchmarking.org FPS, More Is Better dav1d 1.4 Video Input: Chimera 1080p a b c 90 180 270 360 450 403.43 405.66 401.11 1. (CC) gcc options: -pthread
dav1d Video Input: Summer Nature 4K OpenBenchmarking.org FPS, More Is Better dav1d 1.4 Video Input: Summer Nature 4K a b c 20 40 60 80 100 92.92 102.65 94.69 1. (CC) gcc options: -pthread
dav1d Video Input: Summer Nature 1080p OpenBenchmarking.org FPS, More Is Better dav1d 1.4 Video Input: Summer Nature 1080p a b c 90 180 270 360 450 325.60 409.89 381.24 1. (CC) gcc options: -pthread
dav1d Video Input: Chimera 1080p 10-bit OpenBenchmarking.org FPS, More Is Better dav1d 1.4 Video Input: Chimera 1080p 10-bit a b c 60 120 180 240 300 296.56 296.79 297.27 1. (CC) gcc options: -pthread
GROMACS Implementation: MPI CPU - Input: water_GMX50_bare OpenBenchmarking.org Ns Per Day, More Is Better GROMACS 2024 Implementation: MPI CPU - Input: water_GMX50_bare a b c 0.1289 0.2578 0.3867 0.5156 0.6445 0.573 0.570 0.563 1. (CXX) g++ options: -O3 -lm
Intel Open Image Denoise Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only OpenBenchmarking.org Images / Sec, More Is Better Intel Open Image Denoise 2.2 Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only a b c 0.0338 0.0676 0.1014 0.1352 0.169 0.15 0.15 0.15
Intel Open Image Denoise Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only OpenBenchmarking.org Images / Sec, More Is Better Intel Open Image Denoise 2.2 Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only a b c 0.036 0.072 0.108 0.144 0.18 0.16 0.16 0.16
Intel Open Image Denoise Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only OpenBenchmarking.org Images / Sec, More Is Better Intel Open Image Denoise 2.2 Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only a b c 0.0158 0.0316 0.0474 0.0632 0.079 0.07 0.07 0.07
Libplacebo Test: deband_heavy OpenBenchmarking.org FPS, More Is Better Libplacebo 6.338.2 Test: deband_heavy a b c 20 40 60 80 100 78.22 78.16 78.10 1. (CXX) g++ options: -fvisibility=hidden -std=c++20 -O2 -fno-math-errno -fPIC -pthread -MD -MQ -MF
Libplacebo Test: polar_nocompute OpenBenchmarking.org FPS, More Is Better Libplacebo 6.338.2 Test: polar_nocompute a b c 30 60 90 120 150 151.38 151.42 151.27 1. (CXX) g++ options: -fvisibility=hidden -std=c++20 -O2 -fno-math-errno -fPIC -pthread -MD -MQ -MF
Libplacebo Test: hdr_peakdetect OpenBenchmarking.org FPS, More Is Better Libplacebo 6.338.2 Test: hdr_peakdetect a b c 70 140 210 280 350 336.77 254.33 274.71 1. (CXX) g++ options: -fvisibility=hidden -std=c++20 -O2 -fno-math-errno -fPIC -pthread -MD -MQ -MF
Libplacebo Test: hdr_lut OpenBenchmarking.org FPS, More Is Better Libplacebo 6.338.2 Test: hdr_lut a b c 80 160 240 320 400 371.63 371.86 371.35 1. (CXX) g++ options: -fvisibility=hidden -std=c++20 -O2 -fno-math-errno -fPIC -pthread -MD -MQ -MF
Libplacebo Test: av1_grain_lap OpenBenchmarking.org FPS, More Is Better Libplacebo 6.338.2 Test: av1_grain_lap a b c 90 180 270 360 450 405.16 405.80 403.90 1. (CXX) g++ options: -fvisibility=hidden -std=c++20 -O2 -fno-math-errno -fPIC -pthread -MD -MQ -MF
Libplacebo Test: gaussian OpenBenchmarking.org FPS, More Is Better Libplacebo 6.338.2 Test: gaussian a b c 80 160 240 320 400 370.73 370.69 370.58 1. (CXX) g++ options: -fvisibility=hidden -std=c++20 -O2 -fno-math-errno -fPIC -pthread -MD -MQ -MF
Llama.cpp Model: llama-2-7b.Q4_0.gguf OpenBenchmarking.org Tokens Per Second, More Is Better Llama.cpp b1808 Model: llama-2-7b.Q4_0.gguf a b c 2 4 6 8 10 7.37 7.41 7.43 1. (CXX) g++ options: -std=c++11 -fPIC -O3 -pthread -march=native -mtune=native -lopenblas
Llama.cpp Model: llama-2-13b.Q4_0.gguf OpenBenchmarking.org Tokens Per Second, More Is Better Llama.cpp b1808 Model: llama-2-13b.Q4_0.gguf a b c 0.864 1.728 2.592 3.456 4.32 3.84 3.84 3.84 1. (CXX) g++ options: -std=c++11 -fPIC -O3 -pthread -march=native -mtune=native -lopenblas
Llama.cpp Model: llama-2-70b-chat.Q5_0.gguf OpenBenchmarking.org Tokens Per Second, More Is Better Llama.cpp b1808 Model: llama-2-70b-chat.Q5_0.gguf a b c 0.0068 0.0136 0.0204 0.0272 0.034 0.03 0.03 0.03 1. (CXX) g++ options: -std=c++11 -fPIC -O3 -pthread -march=native -mtune=native -lopenblas
Llamafile Test: llava-v1.5-7b-q4 - Acceleration: CPU OpenBenchmarking.org Tokens Per Second, More Is Better Llamafile 0.6 Test: llava-v1.5-7b-q4 - Acceleration: CPU a b c 2 4 6 8 10 7.07 7.09 7.12
Llamafile Test: mistral-7b-instruct-v0.2.Q8_0 - Acceleration: CPU OpenBenchmarking.org Tokens Per Second, More Is Better Llamafile 0.6 Test: mistral-7b-instruct-v0.2.Q8_0 - Acceleration: CPU a b c 0.963 1.926 2.889 3.852 4.815 4.26 4.28 4.27
Llamafile Test: wizardcoder-python-34b-v1.0.Q6_K - Acceleration: CPU OpenBenchmarking.org Tokens Per Second, More Is Better Llamafile 0.6 Test: wizardcoder-python-34b-v1.0.Q6_K - Acceleration: CPU a b c 0.0113 0.0226 0.0339 0.0452 0.0565 0.05 0.05 0.05
LZ4 Compression Compression Level: 1 - Compression Speed OpenBenchmarking.org MB/s, More Is Better LZ4 Compression 1.9.4 Compression Level: 1 - Compression Speed a b c 160 320 480 640 800 755.41 754.76 752.43 1. (CC) gcc options: -O3
LZ4 Compression Compression Level: 1 - Decompression Speed OpenBenchmarking.org MB/s, More Is Better LZ4 Compression 1.9.4 Compression Level: 1 - Decompression Speed a b c 900 1800 2700 3600 4500 4114.5 4123.5 4139.1 1. (CC) gcc options: -O3
LZ4 Compression Compression Level: 3 - Compression Speed OpenBenchmarking.org MB/s, More Is Better LZ4 Compression 1.9.4 Compression Level: 3 - Compression Speed a b c 30 60 90 120 150 118.71 119.04 117.87 1. (CC) gcc options: -O3
LZ4 Compression Compression Level: 3 - Decompression Speed OpenBenchmarking.org MB/s, More Is Better LZ4 Compression 1.9.4 Compression Level: 3 - Decompression Speed a b c 800 1600 2400 3200 4000 3850.6 3870.7 3857.8 1. (CC) gcc options: -O3
LZ4 Compression Compression Level: 9 - Compression Speed OpenBenchmarking.org MB/s, More Is Better LZ4 Compression 1.9.4 Compression Level: 9 - Compression Speed a b c 9 18 27 36 45 41.13 41.16 40.77 1. (CC) gcc options: -O3
LZ4 Compression Compression Level: 9 - Decompression Speed OpenBenchmarking.org MB/s, More Is Better LZ4 Compression 1.9.4 Compression Level: 9 - Decompression Speed a b c 900 1800 2700 3600 4500 4072.4 4077.0 4080.0 1. (CC) gcc options: -O3
NAMD Input: ATPase with 327,506 Atoms OpenBenchmarking.org ns/day, More Is Better NAMD 3.0b6 Input: ATPase with 327,506 Atoms a b c 0.1244 0.2488 0.3732 0.4976 0.622 0.54640 0.55272 0.53465
NAMD Input: STMV with 1,066,628 Atoms OpenBenchmarking.org ns/day, More Is Better NAMD 3.0b6 Input: STMV with 1,066,628 Atoms a b c 0.0378 0.0756 0.1134 0.1512 0.189 0.16793 0.16810 0.16812
ONNX Runtime Model: GPT-2 - Device: CPU - Executor: Parallel OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.17 Model: GPT-2 - Device: CPU - Executor: Parallel a b c 20 40 60 80 100 81.61 77.20 83.35 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: GPT-2 - Device: CPU - Executor: Parallel OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.17 Model: GPT-2 - Device: CPU - Executor: Parallel a b c 3 6 9 12 15 12.24 12.95 11.99 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: GPT-2 - Device: CPU - Executor: Standard OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.17 Model: GPT-2 - Device: CPU - Executor: Standard a b c 20 40 60 80 100 105.49 101.60 104.92 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: GPT-2 - Device: CPU - Executor: Standard OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.17 Model: GPT-2 - Device: CPU - Executor: Standard a b c 3 6 9 12 15 9.47309 9.83571 9.52371 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: yolov4 - Device: CPU - Executor: Parallel OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.17 Model: yolov4 - Device: CPU - Executor: Parallel a b c 0.7322 1.4644 2.1966 2.9288 3.661 2.89643 3.25429 3.12461 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: yolov4 - Device: CPU - Executor: Parallel OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.17 Model: yolov4 - Device: CPU - Executor: Parallel a b c 80 160 240 320 400 345.25 307.28 320.04 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: yolov4 - Device: CPU - Executor: Standard OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.17 Model: yolov4 - Device: CPU - Executor: Standard a b c 1.1389 2.2778 3.4167 4.5556 5.6945 5.06166 4.72968 4.91617 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: yolov4 - Device: CPU - Executor: Standard OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.17 Model: yolov4 - Device: CPU - Executor: Standard a b c 50 100 150 200 250 197.56 211.43 203.41 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: T5 Encoder - Device: CPU - Executor: Parallel OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.17 Model: T5 Encoder - Device: CPU - Executor: Parallel a b c 20 40 60 80 100 90.92 89.81 89.56 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: T5 Encoder - Device: CPU - Executor: Parallel OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.17 Model: T5 Encoder - Device: CPU - Executor: Parallel a b c 3 6 9 12 15 11.00 11.13 11.16 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: T5 Encoder - Device: CPU - Executor: Standard OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.17 Model: T5 Encoder - Device: CPU - Executor: Standard a b c 30 60 90 120 150 146.86 146.72 147.50 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: T5 Encoder - Device: CPU - Executor: Standard OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.17 Model: T5 Encoder - Device: CPU - Executor: Standard a b c 2 4 6 8 10 6.80604 6.81340 6.77737 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: bertsquad-12 - Device: CPU - Executor: Parallel OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.17 Model: bertsquad-12 - Device: CPU - Executor: Parallel a b c 1.0873 2.1746 3.2619 4.3492 5.4365 4.25933 4.83250 3.97700 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: bertsquad-12 - Device: CPU - Executor: Parallel OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.17 Model: bertsquad-12 - Device: CPU - Executor: Parallel a b c 50 100 150 200 250 234.78 206.93 251.44 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: bertsquad-12 - Device: CPU - Executor: Standard OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.17 Model: bertsquad-12 - Device: CPU - Executor: Standard a b c 2 4 6 8 10 6.90025 6.38547 6.83843 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: bertsquad-12 - Device: CPU - Executor: Standard OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.17 Model: bertsquad-12 - Device: CPU - Executor: Standard a b c 30 60 90 120 150 144.92 156.60 146.23 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: CaffeNet 12-int8 - Device: CPU - Executor: Parallel OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.17 Model: CaffeNet 12-int8 - Device: CPU - Executor: Parallel a b c 50 100 150 200 250 239.59 238.16 240.22 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: CaffeNet 12-int8 - Device: CPU - Executor: Parallel OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.17 Model: CaffeNet 12-int8 - Device: CPU - Executor: Parallel a b c 0.9442 1.8884 2.8326 3.7768 4.721 4.17219 4.19665 4.16112 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: CaffeNet 12-int8 - Device: CPU - Executor: Standard OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.17 Model: CaffeNet 12-int8 - Device: CPU - Executor: Standard a b c 80 160 240 320 400 333.92 350.10 328.36 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: CaffeNet 12-int8 - Device: CPU - Executor: Standard OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.17 Model: CaffeNet 12-int8 - Device: CPU - Executor: Standard a b c 0.6848 1.3696 2.0544 2.7392 3.424 2.99315 2.85482 3.04357 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: fcn-resnet101-11 - Device: CPU - Executor: Parallel OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.17 Model: fcn-resnet101-11 - Device: CPU - Executor: Parallel a b c 0.106 0.212 0.318 0.424 0.53 0.471017 0.415642 0.462395 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: fcn-resnet101-11 - Device: CPU - Executor: Parallel OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.17 Model: fcn-resnet101-11 - Device: CPU - Executor: Parallel a b c 500 1000 1500 2000 2500 2123.06 2405.91 2162.65 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: fcn-resnet101-11 - Device: CPU - Executor: Standard OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.17 Model: fcn-resnet101-11 - Device: CPU - Executor: Standard a b c 0.1696 0.3392 0.5088 0.6784 0.848 0.686147 0.753919 0.680886 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: fcn-resnet101-11 - Device: CPU - Executor: Standard OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.17 Model: fcn-resnet101-11 - Device: CPU - Executor: Standard a b c 300 600 900 1200 1500 1457.41 1326.40 1468.67 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: ArcFace ResNet-100 - Device: CPU - Executor: Parallel OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.17 Model: ArcFace ResNet-100 - Device: CPU - Executor: Parallel a b c 3 6 9 12 15 9.98691 8.98048 10.19480 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: ArcFace ResNet-100 - Device: CPU - Executor: Parallel OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.17 Model: ArcFace ResNet-100 - Device: CPU - Executor: Parallel a b c 20 40 60 80 100 100.13 111.35 98.09 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: ArcFace ResNet-100 - Device: CPU - Executor: Standard OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.17 Model: ArcFace ResNet-100 - Device: CPU - Executor: Standard a b c 4 8 12 16 20 14.92 16.31 14.80 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: ArcFace ResNet-100 - Device: CPU - Executor: Standard OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.17 Model: ArcFace ResNet-100 - Device: CPU - Executor: Standard a b c 15 30 45 60 75 67.03 61.31 67.56 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: ResNet50 v1-12-int8 - Device: CPU - Executor: Parallel OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.17 Model: ResNet50 v1-12-int8 - Device: CPU - Executor: Parallel a b c 20 40 60 80 100 99.28 98.49 97.33 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: ResNet50 v1-12-int8 - Device: CPU - Executor: Parallel OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.17 Model: ResNet50 v1-12-int8 - Device: CPU - Executor: Parallel a b c 3 6 9 12 15 10.07 10.15 10.27 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: ResNet50 v1-12-int8 - Device: CPU - Executor: Standard OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.17 Model: ResNet50 v1-12-int8 - Device: CPU - Executor: Standard a b c 30 60 90 120 150 129.17 129.06 128.38 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: ResNet50 v1-12-int8 - Device: CPU - Executor: Standard OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.17 Model: ResNet50 v1-12-int8 - Device: CPU - Executor: Standard a b c 2 4 6 8 10 7.73997 7.74651 7.78713 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: super-resolution-10 - Device: CPU - Executor: Parallel OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.17 Model: super-resolution-10 - Device: CPU - Executor: Parallel a b c 7 14 21 28 35 26.96 28.40 28.25 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: super-resolution-10 - Device: CPU - Executor: Parallel OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.17 Model: super-resolution-10 - Device: CPU - Executor: Parallel a b c 9 18 27 36 45 37.08 35.21 35.39 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: super-resolution-10 - Device: CPU - Executor: Standard OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.17 Model: super-resolution-10 - Device: CPU - Executor: Standard a b c 11 22 33 44 55 45.33 47.04 42.81 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: super-resolution-10 - Device: CPU - Executor: Standard OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.17 Model: super-resolution-10 - Device: CPU - Executor: Standard a b c 6 12 18 24 30 22.06 21.26 23.36 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: Parallel OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.17 Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: Parallel a b c 6 12 18 24 30 20.92 21.60 23.19 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: Parallel OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.17 Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: Parallel a b c 11 22 33 44 55 47.80 46.29 43.11 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: Standard OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.17 Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: Standard a b c 9 18 27 36 45 37.05 37.46 35.55 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
ONNX Runtime Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: Standard OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.17 Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: Standard a b c 7 14 21 28 35 26.99 26.69 28.13 1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
VkFFT Test: FFT + iFFT R2C / C2R OpenBenchmarking.org Benchmark Score, More Is Better VkFFT 1.3.4 Test: FFT + iFFT R2C / C2R a b c 1400 2800 4200 5600 7000 6310 6146 6198 1. (CXX) g++ options: -O3
VkFFT Test: FFT + iFFT C2C 1D batched in half precision OpenBenchmarking.org Benchmark Score, More Is Better VkFFT 1.3.4 Test: FFT + iFFT C2C 1D batched in half precision a b c 3K 6K 9K 12K 15K 13702 13923 13748 1. (CXX) g++ options: -O3
VkFFT Test: FFT + iFFT C2C Bluestein in single precision OpenBenchmarking.org Benchmark Score, More Is Better VkFFT 1.3.4 Test: FFT + iFFT C2C Bluestein in single precision a b c 200 400 600 800 1000 1112 1116 1111 1. (CXX) g++ options: -O3
VkFFT Test: FFT + iFFT C2C 1D batched in single precision OpenBenchmarking.org Benchmark Score, More Is Better VkFFT 1.3.4 Test: FFT + iFFT C2C 1D batched in single precision a b c 1600 3200 4800 6400 8000 7500 7495 7496 1. (CXX) g++ options: -O3
VkFFT Test: FFT + iFFT C2C multidimensional in single precision OpenBenchmarking.org Benchmark Score, More Is Better VkFFT 1.3.4 Test: FFT + iFFT C2C multidimensional in single precision a b c 1300 2600 3900 5200 6500 5869 5952 5843 1. (CXX) g++ options: -O3
VkFFT Test: FFT + iFFT C2C 1D batched in single precision, no reshuffling OpenBenchmarking.org Benchmark Score, More Is Better VkFFT 1.3.4 Test: FFT + iFFT C2C 1D batched in single precision, no reshuffling a b c 2K 4K 6K 8K 10K 8510 8503 8506 1. (CXX) g++ options: -O3
Phoronix Test Suite v10.8.4