qwq Intel Core i7-4790K testing with a Apple Mac-42FD25EABCABB274 (IM151.88Z.0207.B01.1411201235 BIOS) and AMD Radeon R7 370 R9 270X/370X 2GB on Fedora 32 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2009241-AS-QWQ90484900 .
qwq Processor Motherboard Chipset Memory Disk Graphics Audio Monitor Network OS Kernel Desktop Display Server Display Driver OpenGL OpenCL Vulkan Compiler File-System Screen Resolution qwq Intel Core i7-4790K @ 4.40GHz (4 Cores / 8 Threads) Apple Mac-42FD25EABCABB274 (IM151.88Z.0207.B01.1411201235 BIOS) Intel 4th Gen Core DRAM 16384MB 1000GB APPLE HDD ST1000 + 121GB APPLE SSD SD0128 + 2000GB Basic AMD Radeon R7 370 R9 270X/370X 2GB Cirrus Logic CS4206 iMac Broadcom NetXtreme BCM57766 PCIe + Broadcom BCM4360 802.11ac Fedora 32 5.8.4-200.fc32.x86_64 (x86_64) KDE Plasma 5.18.5 X Server 1.20.8 amdgpu 19.1.0 4.6 Mesa 20.1.6 (LLVM 10.0.0) OpenCL 1.1 Mesa 20.1.6 + OpenCL 1.2 pocl 1.5 RelWithDebInfo LLVM 10.0.0 RELOC SLEEF DISTRO POCL_DEBUG + OpenCL 2.0 beignet 1.3 1.2.131 Clang 10.0.0 + LLVM 10.0.1 ext4 3840x2160 OpenBenchmarking.org - radeon.si_support=0 amdgpu.si_support=1 - Scaling Governor: intel_cpufreq ondemand - SELinux + itlb_multihit: KVM: Mitigation of VMX disabled + l1tf: Mitigation of PTE Inversion; VMX: conditional cache flushes SMT vulnerable + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Mitigation of PTI + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling + srbds: Mitigation of Microcode + tsx_async_abort: Not affected
qwq qwq OpenBenchmarking.org
NCNN Target: CPU - Model: squeezenet OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: CPU - Model: squeezenet qwq 10 20 30 40 50 SE +/- 0.36, N = 6 44.03 MIN: 42.9 / MAX: 49.68
NCNN Target: CPU - Model: mobilenet OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: CPU - Model: mobilenet qwq 7 14 21 28 35 SE +/- 0.10, N = 6 31.60 MIN: 31.09 / MAX: 32.25
NCNN Target: CPU-v2-v2 - Model: mobilenet-v2 OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: CPU-v2-v2 - Model: mobilenet-v2 qwq 2 4 6 8 10 SE +/- 0.02, N = 6 8.56 MIN: 8.45 / MAX: 9.08
NCNN Target: CPU-v3-v3 - Model: mobilenet-v3 OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: CPU-v3-v3 - Model: mobilenet-v3 qwq 2 4 6 8 10 SE +/- 0.03, N = 6 7.26 MIN: 7.17 / MAX: 8.36
NCNN Target: CPU - Model: shufflenet-v2 OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: CPU - Model: shufflenet-v2 qwq 1.089 2.178 3.267 4.356 5.445 SE +/- 0.01, N = 6 4.84 MIN: 4.79 / MAX: 5.55
NCNN Target: CPU - Model: mnasnet OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: CPU - Model: mnasnet qwq 2 4 6 8 10 SE +/- 0.04, N = 6 6.84 MIN: 6.68 / MAX: 7.57
NCNN Target: CPU - Model: efficientnet-b0 OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: CPU - Model: efficientnet-b0 qwq 3 6 9 12 15 SE +/- 0.03, N = 6 11.42 MIN: 11.21 / MAX: 11.67
NCNN Target: CPU - Model: blazeface OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: CPU - Model: blazeface qwq 0.432 0.864 1.296 1.728 2.16 SE +/- 0.01, N = 6 1.92 MIN: 1.89 / MAX: 2.16
NCNN Target: CPU - Model: googlenet OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: CPU - Model: googlenet qwq 15 30 45 60 75 SE +/- 0.61, N = 6 69.26 MIN: 68.15 / MAX: 99.18
NCNN Target: CPU - Model: vgg16 OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: CPU - Model: vgg16 qwq 50 100 150 200 250 SE +/- 0.31, N = 6 249.01 MIN: 247.5 / MAX: 250.91
NCNN Target: CPU - Model: resnet18 OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: CPU - Model: resnet18 qwq 9 18 27 36 45 SE +/- 0.07, N = 6 39.59 MIN: 39.16 / MAX: 41.59
NCNN Target: CPU - Model: alexnet OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: CPU - Model: alexnet qwq 6 12 18 24 30 SE +/- 0.89, N = 6 26.24 MIN: 24.89 / MAX: 62.25
NCNN Target: CPU - Model: resnet50 OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: CPU - Model: resnet50 qwq 30 60 90 120 150 SE +/- 0.18, N = 6 139.84 MIN: 139.2 / MAX: 141.02
NCNN Target: CPUv2-yolov3v2-yolov3 - Model: mobilenetv2-yolov3 OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: CPUv2-yolov3v2-yolov3 - Model: mobilenetv2-yolov3 qwq 7 14 21 28 35 SE +/- 0.10, N = 6 31.60 MIN: 31.09 / MAX: 32.25
NCNN Target: CPU - Model: yolov4-tiny OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: CPU - Model: yolov4-tiny qwq 11 22 33 44 55 SE +/- 0.30, N = 6 46.97 MIN: 45.47 / MAX: 48.92
NCNN Target: GPU - Model: squeezenet OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: GPU - Model: squeezenet qwq 10 20 30 40 50 SE +/- 0.28, N = 6 44.85 MIN: 43.87 / MAX: 48.51
NCNN Target: GPU - Model: mobilenet OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: GPU - Model: mobilenet qwq 5 10 15 20 25 SE +/- 0.04, N = 6 20.03 MIN: 19.46 / MAX: 21.34
NCNN Target: GPU-v2-v2 - Model: mobilenet-v2 OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: GPU-v2-v2 - Model: mobilenet-v2 qwq 3 6 9 12 15 SE +/- 0.11, N = 6 9.16 MIN: 8.79 / MAX: 11.79
NCNN Target: GPU-v3-v3 - Model: mobilenet-v3 OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: GPU-v3-v3 - Model: mobilenet-v3 qwq 3 6 9 12 15 SE +/- 0.03, N = 6 11.44 MIN: 11.23 / MAX: 11.95
NCNN Target: GPU - Model: shufflenet-v2 OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: GPU - Model: shufflenet-v2 qwq 1.3185 2.637 3.9555 5.274 6.5925 SE +/- 0.01, N = 6 5.86 MIN: 5.71 / MAX: 6.03
NCNN Target: GPU - Model: mnasnet OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: GPU - Model: mnasnet qwq 3 6 9 12 15 SE +/- 0.06, N = 6 9.63 MIN: 9.44 / MAX: 11.69
NCNN Target: GPU - Model: efficientnet-b0 OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: GPU - Model: efficientnet-b0 qwq 5 10 15 20 25 SE +/- 0.05, N = 6 22.26 MIN: 21.86 / MAX: 24.92
NCNN Target: GPU - Model: blazeface OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: GPU - Model: blazeface qwq 0.4725 0.945 1.4175 1.89 2.3625 SE +/- 0.07, N = 6 2.10 MIN: 1.8 / MAX: 4.48
NCNN Target: GPU - Model: googlenet OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: GPU - Model: googlenet qwq 15 30 45 60 75 SE +/- 0.09, N = 6 69.14 MIN: 68.56 / MAX: 70.19
NCNN Target: GPU - Model: vgg16 OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: GPU - Model: vgg16 qwq 50 100 150 200 250 SE +/- 1.63, N = 6 246.60 MIN: 239.36 / MAX: 252.02
NCNN Target: GPU - Model: resnet18 OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: GPU - Model: resnet18 qwq 9 18 27 36 45 SE +/- 0.13, N = 6 40.06 MIN: 39.55 / MAX: 43.68
NCNN Target: GPU - Model: alexnet OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: GPU - Model: alexnet qwq 5 10 15 20 25 SE +/- 0.04, N = 6 21.40 MIN: 20.83 / MAX: 23.78
NCNN Target: GPU - Model: resnet50 OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: GPU - Model: resnet50 qwq 30 60 90 120 150 SE +/- 0.29, N = 6 141.09 MIN: 139.36 / MAX: 146.1
NCNN Target: GPUv2-yolov3v2-yolov3 - Model: mobilenetv2-yolov3 OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: GPUv2-yolov3v2-yolov3 - Model: mobilenetv2-yolov3 qwq 5 10 15 20 25 SE +/- 0.04, N = 6 20.03 MIN: 19.46 / MAX: 21.34
NCNN Target: GPU - Model: yolov4-tiny OpenBenchmarking.org ms, Fewer Is Better NCNN 20200916 Target: GPU - Model: yolov4-tiny qwq 10 20 30 40 50 SE +/- 0.07, N = 6 42.59 MIN: 41.98 / MAX: 44.89
Phoronix Test Suite v10.8.4