Intel Core i7-1280P testing with a MSI MS-14C6 (E14C6IMS.115 BIOS) and MSI Intel ADL GT2 14GB on Ubuntu 22.10 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 2210085-NE-1280PTF6300 1280p tf - Phoronix Test Suite 1280p tf Intel Core i7-1280P testing with a MSI MS-14C6 (E14C6IMS.115 BIOS) and MSI Intel ADL GT2 14GB on Ubuntu 22.10 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2210085-NE-1280PTF6300 .
1280p tf Processor Motherboard Chipset Memory Disk Graphics Audio Network OS Kernel Desktop Display Server OpenGL Vulkan Compiler File-System Screen Resolution A B C D Intel Core i7-1280P @ 4.80GHz (14 Cores / 20 Threads) MSI MS-14C6 (E14C6IMS.115 BIOS) Intel Alder Lake PCH 16GB 1024GB Micron_3400_MTFDKBA1T0TFH MSI Intel ADL GT2 14GB (1450MHz) Realtek ALC274 Intel Alder Lake-P PCH CNVi WiFi Ubuntu 22.10 5.15.0-27-generic (x86_64) GNOME Shell X Server + Wayland 4.6 Mesa 22.1.7 1.3.211 GCC 12.2.0 ext4 1920x1080 OpenBenchmarking.org Kernel Details - Transparent Huge Pages: madvise Compiler Details - --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-Wbc0TK/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-Wbc0TK/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 -v Processor Details - Scaling Governor: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0x421 - Thermald 2.5.0 Python Details - Python 3.10.6 Security Details - 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 Enhanced IBRS IBPB: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected
1280p tf smhasher: wyhash smhasher: wyhash smhasher: SHA3-256 smhasher: SHA3-256 smhasher: Spooky32 smhasher: Spooky32 smhasher: fasthash32 smhasher: fasthash32 smhasher: FarmHash128 smhasher: FarmHash128 smhasher: t1ha2_atonce smhasher: t1ha2_atonce smhasher: FarmHash32 x86_64 AVX smhasher: FarmHash32 x86_64 AVX smhasher: t1ha0_aes_avx2 x86_64 smhasher: t1ha0_aes_avx2 x86_64 smhasher: MeowHash x86_64 AES-NI smhasher: MeowHash x86_64 AES-NI tensorflow: CPU - 16 - VGG-16 tensorflow: CPU - 32 - VGG-16 tensorflow: CPU - 64 - VGG-16 tensorflow: CPU - 16 - AlexNet tensorflow: CPU - 32 - AlexNet tensorflow: CPU - 64 - AlexNet tensorflow: CPU - 256 - AlexNet tensorflow: CPU - 512 - 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 - 512 - GoogLeNet tensorflow: CPU - 512 - ResNet-50 A B C D 40938.04 12.733 325.88 1203.149 25362.49 23.62 10861.08 19.556 27510.72 27.36 30977.36 17.573 39148.58 23.01 94329.69 17.601 64054.43 37.484 3.59 3.65 3.68 73.85 84.36 89.79 93.74 98.68 37.58 12.81 37.05 13.27 38.2 13.53 39.74 40.29 40858.09 12.732 326.06 1203.733 25371.39 23.635 10861.08 19.554 27465.42 27.359 30756.7 17.572 38656.01 23.008 103057.81 17.601 63986.83 37.484 3.58 3.64 3.7 73.62 84.37 88.71 92.78 97.05 37.63 12.8 37.07 13.28 38.28 13.04 39.36 40 40937.15 12.732 322.59 1204.003 25353.15 23.654 10861.09 19.555 27485.7 27.361 30057.97 17.591 38617.17 23.075 90812.67 17.6 64507.92 37.484 3.58 3.65 3.69 73.31 84.24 88.91 89.71 97.43 37.73 12.82 37.06 13.23 36.76 13.22 38.99 39.94 40805.18 12.732 326.17 1202.77 25358.5 23.65 10861.06 19.554 27494.74 27.356 30886.71 17.566 38548.28 23.03 102286.47 17.601 63986.78 37.484 3.58 3.64 3.67 50.27 69.47 90.26 92.8 97.52 37.68 12.85 37.2 13.27 38.15 13.5 37.24 40.02 OpenBenchmarking.org
SMHasher Hash: wyhash OpenBenchmarking.org MiB/sec, More Is Better SMHasher 2022-08-22 Hash: wyhash A B C D 9K 18K 27K 36K 45K 40938.04 40858.09 40937.15 40805.18 1. (CXX) g++ options: -march=native -O3 -flto=auto -fno-fat-lto-objects
SMHasher Hash: wyhash OpenBenchmarking.org cycles/hash, Fewer Is Better SMHasher 2022-08-22 Hash: wyhash A B C D 3 6 9 12 15 12.73 12.73 12.73 12.73 1. (CXX) g++ options: -march=native -O3 -flto=auto -fno-fat-lto-objects
SMHasher Hash: SHA3-256 OpenBenchmarking.org MiB/sec, More Is Better SMHasher 2022-08-22 Hash: SHA3-256 A B C D 70 140 210 280 350 325.88 326.06 322.59 326.17 1. (CXX) g++ options: -march=native -O3 -flto=auto -fno-fat-lto-objects
SMHasher Hash: SHA3-256 OpenBenchmarking.org cycles/hash, Fewer Is Better SMHasher 2022-08-22 Hash: SHA3-256 A B C D 300 600 900 1200 1500 1203.15 1203.73 1204.00 1202.77 1. (CXX) g++ options: -march=native -O3 -flto=auto -fno-fat-lto-objects
SMHasher Hash: Spooky32 OpenBenchmarking.org MiB/sec, More Is Better SMHasher 2022-08-22 Hash: Spooky32 A B C D 5K 10K 15K 20K 25K 25362.49 25371.39 25353.15 25358.50 1. (CXX) g++ options: -march=native -O3 -flto=auto -fno-fat-lto-objects
SMHasher Hash: Spooky32 OpenBenchmarking.org cycles/hash, Fewer Is Better SMHasher 2022-08-22 Hash: Spooky32 A B C D 6 12 18 24 30 23.62 23.64 23.65 23.65 1. (CXX) g++ options: -march=native -O3 -flto=auto -fno-fat-lto-objects
SMHasher Hash: fasthash32 OpenBenchmarking.org MiB/sec, More Is Better SMHasher 2022-08-22 Hash: fasthash32 A B C D 2K 4K 6K 8K 10K 10861.08 10861.08 10861.09 10861.06 1. (CXX) g++ options: -march=native -O3 -flto=auto -fno-fat-lto-objects
SMHasher Hash: fasthash32 OpenBenchmarking.org cycles/hash, Fewer Is Better SMHasher 2022-08-22 Hash: fasthash32 A B C D 5 10 15 20 25 19.56 19.55 19.56 19.55 1. (CXX) g++ options: -march=native -O3 -flto=auto -fno-fat-lto-objects
SMHasher Hash: FarmHash128 OpenBenchmarking.org MiB/sec, More Is Better SMHasher 2022-08-22 Hash: FarmHash128 A B C D 6K 12K 18K 24K 30K 27510.72 27465.42 27485.70 27494.74 1. (CXX) g++ options: -march=native -O3 -flto=auto -fno-fat-lto-objects
SMHasher Hash: FarmHash128 OpenBenchmarking.org cycles/hash, Fewer Is Better SMHasher 2022-08-22 Hash: FarmHash128 A B C D 6 12 18 24 30 27.36 27.36 27.36 27.36 1. (CXX) g++ options: -march=native -O3 -flto=auto -fno-fat-lto-objects
SMHasher Hash: t1ha2_atonce OpenBenchmarking.org MiB/sec, More Is Better SMHasher 2022-08-22 Hash: t1ha2_atonce A B C D 7K 14K 21K 28K 35K 30977.36 30756.70 30057.97 30886.71 1. (CXX) g++ options: -march=native -O3 -flto=auto -fno-fat-lto-objects
SMHasher Hash: t1ha2_atonce OpenBenchmarking.org cycles/hash, Fewer Is Better SMHasher 2022-08-22 Hash: t1ha2_atonce A B C D 4 8 12 16 20 17.57 17.57 17.59 17.57 1. (CXX) g++ options: -march=native -O3 -flto=auto -fno-fat-lto-objects
SMHasher Hash: FarmHash32 x86_64 AVX OpenBenchmarking.org MiB/sec, More Is Better SMHasher 2022-08-22 Hash: FarmHash32 x86_64 AVX A B C D 8K 16K 24K 32K 40K 39148.58 38656.01 38617.17 38548.28 1. (CXX) g++ options: -march=native -O3 -flto=auto -fno-fat-lto-objects
SMHasher Hash: FarmHash32 x86_64 AVX OpenBenchmarking.org cycles/hash, Fewer Is Better SMHasher 2022-08-22 Hash: FarmHash32 x86_64 AVX A B C D 6 12 18 24 30 23.01 23.01 23.08 23.03 1. (CXX) g++ options: -march=native -O3 -flto=auto -fno-fat-lto-objects
SMHasher Hash: t1ha0_aes_avx2 x86_64 OpenBenchmarking.org MiB/sec, More Is Better SMHasher 2022-08-22 Hash: t1ha0_aes_avx2 x86_64 A B C D 20K 40K 60K 80K 100K 94329.69 103057.81 90812.67 102286.47 1. (CXX) g++ options: -march=native -O3 -flto=auto -fno-fat-lto-objects
SMHasher Hash: t1ha0_aes_avx2 x86_64 OpenBenchmarking.org cycles/hash, Fewer Is Better SMHasher 2022-08-22 Hash: t1ha0_aes_avx2 x86_64 A B C D 4 8 12 16 20 17.60 17.60 17.60 17.60 1. (CXX) g++ options: -march=native -O3 -flto=auto -fno-fat-lto-objects
SMHasher Hash: MeowHash x86_64 AES-NI OpenBenchmarking.org MiB/sec, More Is Better SMHasher 2022-08-22 Hash: MeowHash x86_64 AES-NI A B C D 14K 28K 42K 56K 70K 64054.43 63986.83 64507.92 63986.78 1. (CXX) g++ options: -march=native -O3 -flto=auto -fno-fat-lto-objects
SMHasher Hash: MeowHash x86_64 AES-NI OpenBenchmarking.org cycles/hash, Fewer Is Better SMHasher 2022-08-22 Hash: MeowHash x86_64 AES-NI A B C D 9 18 27 36 45 37.48 37.48 37.48 37.48 1. (CXX) g++ options: -march=native -O3 -flto=auto -fno-fat-lto-objects
TensorFlow Device: CPU - Batch Size: 16 - Model: VGG-16 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.10 Device: CPU - Batch Size: 16 - Model: VGG-16 A B C D 0.8078 1.6156 2.4234 3.2312 4.039 3.59 3.58 3.58 3.58
TensorFlow Device: CPU - Batch Size: 32 - Model: VGG-16 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.10 Device: CPU - Batch Size: 32 - Model: VGG-16 A B C D 0.8213 1.6426 2.4639 3.2852 4.1065 3.65 3.64 3.65 3.64
TensorFlow Device: CPU - Batch Size: 64 - Model: VGG-16 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.10 Device: CPU - Batch Size: 64 - Model: VGG-16 A B C D 0.8325 1.665 2.4975 3.33 4.1625 3.68 3.70 3.69 3.67
TensorFlow Device: CPU - Batch Size: 16 - Model: AlexNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.10 Device: CPU - Batch Size: 16 - Model: AlexNet A B C D 16 32 48 64 80 73.85 73.62 73.31 50.27
TensorFlow Device: CPU - Batch Size: 32 - Model: AlexNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.10 Device: CPU - Batch Size: 32 - Model: AlexNet A B C D 20 40 60 80 100 84.36 84.37 84.24 69.47
TensorFlow Device: CPU - Batch Size: 64 - Model: AlexNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.10 Device: CPU - Batch Size: 64 - Model: AlexNet A B C D 20 40 60 80 100 89.79 88.71 88.91 90.26
TensorFlow Device: CPU - Batch Size: 256 - Model: AlexNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.10 Device: CPU - Batch Size: 256 - Model: AlexNet A B C D 20 40 60 80 100 93.74 92.78 89.71 92.80
TensorFlow Device: CPU - Batch Size: 512 - Model: AlexNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.10 Device: CPU - Batch Size: 512 - Model: AlexNet A B C D 20 40 60 80 100 98.68 97.05 97.43 97.52
TensorFlow Device: CPU - Batch Size: 16 - Model: GoogLeNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.10 Device: CPU - Batch Size: 16 - Model: GoogLeNet A B C D 9 18 27 36 45 37.58 37.63 37.73 37.68
TensorFlow Device: CPU - Batch Size: 16 - Model: ResNet-50 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.10 Device: CPU - Batch Size: 16 - Model: ResNet-50 A B C D 3 6 9 12 15 12.81 12.80 12.82 12.85
TensorFlow Device: CPU - Batch Size: 32 - Model: GoogLeNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.10 Device: CPU - Batch Size: 32 - Model: GoogLeNet A B C D 9 18 27 36 45 37.05 37.07 37.06 37.20
TensorFlow Device: CPU - Batch Size: 32 - Model: ResNet-50 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.10 Device: CPU - Batch Size: 32 - Model: ResNet-50 A B C D 3 6 9 12 15 13.27 13.28 13.23 13.27
TensorFlow Device: CPU - Batch Size: 64 - Model: GoogLeNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.10 Device: CPU - Batch Size: 64 - Model: GoogLeNet A B C D 9 18 27 36 45 38.20 38.28 36.76 38.15
TensorFlow Device: CPU - Batch Size: 64 - Model: ResNet-50 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.10 Device: CPU - Batch Size: 64 - Model: ResNet-50 A B C D 3 6 9 12 15 13.53 13.04 13.22 13.50
TensorFlow Device: CPU - Batch Size: 256 - Model: GoogLeNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.10 Device: CPU - Batch Size: 256 - Model: GoogLeNet A B C D 9 18 27 36 45 39.74 39.36 38.99 37.24
TensorFlow Device: CPU - Batch Size: 512 - Model: GoogLeNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.10 Device: CPU - Batch Size: 512 - Model: GoogLeNet A B C D 9 18 27 36 45 40.29 40.00 39.94 40.02
Phoronix Test Suite v10.8.4