core-i5-4670-december

Intel Core i5-4670 testing with a MSI B85M-P33 (MS-7817) v1.0 (V4.9 BIOS) and MSI Intel HD 4600 2GB on Ubuntu 20.04 via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/2012193-HA-COREI546718&grs.

core-i5-4670-december ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLCompilerFile-SystemScreen Resolution11a234Intel Core i5-4670 @ 3.80GHz (4 Cores)MSI B85M-P33 (MS-7817) v1.0 (V4.9 BIOS)Intel 4th Gen Core DRAM8GB2000GB Samsung SSD 860MSI Intel HD 4600 2GB (1200MHz)Intel Xeon E3-1200 v3/4thDELL S2409WRealtek RTL8111/8168/8411Ubuntu 20.045.9.0-050900rc7daily20201002-generic (x86_64) 20201001GNOME Shell 3.36.3X Server 1.20.8modesetting 1.20.84.5 Mesa 20.0.8GCC 9.3.0ext41920x1080OpenBenchmarking.orgCompiler Details- --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --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++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none,hsa --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_cpufreq ondemand - CPU Microcode: 0x28 - Thermald 1.9.1 Security Details- itlb_multihit: KVM: Mitigation of VMX disabled + l1tf: Mitigation of PTE Inversion; VMX: conditional cache flushes SMT disabled + mds: Mitigation of Clear buffers; SMT disabled + 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: disabled RSB filling + srbds: Mitigation of Microcode + tsx_async_abort: Not affected

core-i5-4670-december onednn: IP Shapes 3D - f32 - CPUonednn: IP Shapes 3D - u8s8f32 - CPUonednn: IP Shapes 1D - f32 - CPUonednn: Deconvolution Batch shapes_3d - f32 - CPUonednn: Recurrent Neural Network Inference - u8s8f32 - CPUonednn: Convolution Batch Shapes Auto - f32 - CPUncnn: CPU - mnasnetonednn: Recurrent Neural Network Inference - bf16bf16bf16 - CPUncnn: CPU-v2-v2 - mobilenet-v2onednn: Recurrent Neural Network Training - f32 - CPUncnn: CPU - yolov4-tinyonednn: Convolution Batch Shapes Auto - u8s8f32 - CPUonednn: Recurrent Neural Network Inference - f32 - CPUncnn: CPU - regnety_400monednn: Recurrent Neural Network Training - u8s8f32 - CPUncnn: CPU - alexnetonednn: Matrix Multiply Batch Shapes Transformer - f32 - CPUncnn: CPU - mobilenetbuild2: Time To Compilencnn: CPU - squeezenet_ssdonednn: IP Shapes 1D - u8s8f32 - CPUncnn: CPU-v3-v3 - mobilenet-v3node-web-tooling: mafft: Multiple Sequence Alignment - LSU RNAncnn: CPU - resnet18ncnn: CPU - efficientnet-b0ncnn: CPU - resnet50onednn: Deconvolution Batch shapes_3d - u8s8f32 - CPUonednn: Recurrent Neural Network Training - bf16bf16bf16 - CPUcoremark: CoreMark Size 666 - Iterations Per Secondonednn: Matrix Multiply Batch Shapes Transformer - u8s8f32 - CPUonednn: Deconvolution Batch shapes_1d - f32 - CPUsqlite-speedtest: Timed Time - Size 1,000build-ffmpeg: Time To Compilencnn: CPU - googlenetncnn: CPU - vgg16ncnn: CPU - blazefaceonednn: Deconvolution Batch shapes_1d - u8s8f32 - CPUhmmer: Pfam Database Searchncnn: CPU - shufflenet-v2simdjson: Kostya11a23412.617140.0580.5913.64204.9239210.774617.55055407.3830.30467.935466.349.308703.9052.3130.54135460.1516.159031.7625.197.7001336.33364.76851.946.280978.109.7031.2313.2463.2313.89039078.4995428.2403807.5144212.585078.851163.11928.73134.382.6815.202410.7816.37265.6591711.238317.69335542.5831.43647.925604.529.328840.5952.2731.27445558.7716.209114.8225.717.8197836.95361.99552.256.355998.219.8012.51831.3413.4163.3014.03399159.9595542.9609747.5139912.681578.646162.23328.59134.042.6815.1543140.50510.780.5917.26575.7244111.075917.72845624.8431.42578.065563.079.598933.9353.5631.28205557.6516.519232.9425.537.8450536.87364.16452.006.378528.209.8412.43930.9113.3962.5613.91769174.7594952.4945657.5146612.688079.191162.07528.61133.932.6915.1584140.25610.810.5917.10325.7343911.400518.30295562.3331.37437.775652.749.588939.7452.4431.20575587.2516.179209.4425.327.8267536.93368.10951.406.330318.229.7412.46331.0913.3762.5414.05759171.8495883.7745167.5769012.640079.105162.65528.60134.482.6815.1490140.24010.790.59OpenBenchmarking.org

oneDNN

Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU1a23448121620SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.05, N = 3SE +/- 0.03, N = 313.6416.3717.2717.10MIN: 13.52MIN: 16.21MIN: 17.03MIN: 16.91. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

oneDNN

Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU1a2341.29022.58043.87065.16086.451SE +/- 0.00651, N = 3SE +/- 0.00675, N = 3SE +/- 0.00635, N = 3SE +/- 0.00987, N = 34.923925.659175.724415.73439MIN: 4.88MIN: 5.61MIN: 5.67MIN: 5.681. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

oneDNN

Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU1a2343691215SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.04, N = 3SE +/- 0.17, N = 310.7711.2411.0811.40MIN: 10.6MIN: 11.08MIN: 10.83MIN: 10.841. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

oneDNN

Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU1a234510152025SE +/- 0.04, N = 3SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.15, N = 317.5517.6917.7318.30MIN: 17.38MIN: 17.54MIN: 17.51MIN: 17.821. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

oneDNN

Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU1a23412002400360048006000SE +/- 28.62, N = 3SE +/- 26.83, N = 3SE +/- 21.34, N = 3SE +/- 42.01, N = 35407.385542.585624.845562.33MIN: 5323.35MIN: 5471.62MIN: 5559.14MIN: 5470.241. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

oneDNN

Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU1a234714212835SE +/- 0.05, N = 3SE +/- 0.03, N = 3SE +/- 0.02, N = 3SE +/- 0.05, N = 330.3031.4431.4331.37MIN: 29.87MIN: 31.29MIN: 31.24MIN: 31.111. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

NCNN

Target: CPU - Model: mnasnet

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: mnasnet1a234246810SE +/- 0.14, N = 3SE +/- 0.08, N = 3SE +/- 0.14, N = 3SE +/- 0.03, N = 37.937.928.067.77MIN: 7.75 / MAX: 8.36MIN: 7.76 / MAX: 8.26MIN: 7.76 / MAX: 10MIN: 7.7 / MAX: 7.851. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

oneDNN

Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU1a23412002400360048006000SE +/- 38.18, N = 3SE +/- 22.30, N = 3SE +/- 18.31, N = 3SE +/- 16.53, N = 35466.345604.525563.075652.74MIN: 5366.55MIN: 5533.62MIN: 5497.5MIN: 5550.051. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

NCNN

Target: CPU-v2-v2 - Model: mobilenet-v2

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU-v2-v2 - Model: mobilenet-v21a2343691215SE +/- 0.02, N = 3SE +/- 0.03, N = 3SE +/- 0.30, N = 3SE +/- 0.31, N = 39.309.329.599.58MIN: 9.21 / MAX: 11.83MIN: 9.22 / MAX: 21.83MIN: 9.2 / MAX: 10.85MIN: 9.18 / MAX: 11.851. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

oneDNN

Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU1a2342K4K6K8K10KSE +/- 86.69, N = 3SE +/- 91.42, N = 3SE +/- 86.21, N = 3SE +/- 113.41, N = 38703.908840.598933.938939.74MIN: 8416.9MIN: 8597.38MIN: 8695.66MIN: 8605.751. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

NCNN

Target: CPU - Model: yolov4-tiny

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: yolov4-tiny1a2341224364860SE +/- 0.18, N = 3SE +/- 0.28, N = 3SE +/- 0.67, N = 3SE +/- 0.55, N = 352.3152.2753.5652.44MIN: 51.39 / MAX: 75.07MIN: 51.34 / MAX: 63.11MIN: 51.95 / MAX: 63.32MIN: 51.3 / MAX: 54.851. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

oneDNN

Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU1a234714212835SE +/- 0.02, N = 3SE +/- 0.04, N = 3SE +/- 0.03, N = 3SE +/- 0.02, N = 330.5431.2731.2831.21MIN: 30.28MIN: 30.95MIN: 31.06MIN: 30.961. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

oneDNN

Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU1a23412002400360048006000SE +/- 28.56, N = 3SE +/- 1.45, N = 3SE +/- 36.92, N = 3SE +/- 15.69, N = 35460.155558.775557.655587.25MIN: 5386.7MIN: 5514.32MIN: 5449.82MIN: 5532.381. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

NCNN

Target: CPU - Model: regnety_400m

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: regnety_400m1a23448121620SE +/- 0.01, N = 3SE +/- 0.05, N = 3SE +/- 0.16, N = 3SE +/- 0.01, N = 316.1516.2016.5116.17MIN: 16.08 / MAX: 17.02MIN: 16.07 / MAX: 28.3MIN: 16.14 / MAX: 19.26MIN: 16.12 / MAX: 16.951. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

oneDNN

Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU1a2342K4K6K8K10KSE +/- 15.55, N = 3SE +/- 14.11, N = 3SE +/- 39.97, N = 3SE +/- 29.31, N = 39031.769114.829232.949209.44MIN: 8754.79MIN: 8823.44MIN: 8959.28MIN: 8882.881. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

NCNN

Target: CPU - Model: alexnet

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: alexnet1a234612182430SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.17, N = 3SE +/- 0.08, N = 325.1925.7125.5325.32MIN: 25.08 / MAX: 33.51MIN: 25.62 / MAX: 27.63MIN: 25.1 / MAX: 32.92MIN: 25.1 / MAX: 35.861. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

oneDNN

Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU1a234246810SE +/- 0.00354, N = 3SE +/- 0.00431, N = 3SE +/- 0.01551, N = 3SE +/- 0.00461, N = 37.700137.819787.845057.82675MIN: 7.61MIN: 7.74MIN: 7.75MIN: 7.741. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

NCNN

Target: CPU - Model: mobilenet

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: mobilenet1a234816243240SE +/- 0.02, N = 3SE +/- 0.21, N = 3SE +/- 0.33, N = 3SE +/- 0.36, N = 336.3336.9536.8736.93MIN: 36.21 / MAX: 38.04MIN: 36.53 / MAX: 38.66MIN: 36.18 / MAX: 39.62MIN: 36.12 / MAX: 50.811. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

Build2

Time To Compile

OpenBenchmarking.orgSeconds, Fewer Is BetterBuild2 0.13Time To Compile1a23480160240320400SE +/- 1.06, N = 3SE +/- 1.03, N = 3SE +/- 1.02, N = 3SE +/- 0.42, N = 3364.77362.00364.16368.11

NCNN

Target: CPU - Model: squeezenet_ssd

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: squeezenet_ssd1a2341224364860SE +/- 0.32, N = 3SE +/- 0.26, N = 3SE +/- 0.63, N = 3SE +/- 0.21, N = 351.9452.2552.0051.40MIN: 51.15 / MAX: 55.05MIN: 51.5 / MAX: 55.44MIN: 51.17 / MAX: 53.56MIN: 51.03 / MAX: 611. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

oneDNN

Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU1a234246810SE +/- 0.01198, N = 3SE +/- 0.01670, N = 3SE +/- 0.03782, N = 3SE +/- 0.03023, N = 36.280976.355996.378526.33031MIN: 6.23MIN: 6.28MIN: 6.29MIN: 6.221. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

NCNN

Target: CPU-v3-v3 - Model: mobilenet-v3

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU-v3-v3 - Model: mobilenet-v31a234246810SE +/- 0.02, N = 3SE +/- 0.13, N = 3SE +/- 0.13, N = 3SE +/- 0.11, N = 38.108.218.208.22MIN: 8.01 / MAX: 9.63MIN: 8.01 / MAX: 9.57MIN: 8 / MAX: 11.87MIN: 7.99 / MAX: 10.181. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

Node.js V8 Web Tooling Benchmark

OpenBenchmarking.orgruns/s, More Is BetterNode.js V8 Web Tooling Benchmark1a2343691215SE +/- 0.07, N = 3SE +/- 0.09, N = 3SE +/- 0.04, N = 3SE +/- 0.06, N = 39.709.809.849.741. Nodejs v10.19.0

Timed MAFFT Alignment

Multiple Sequence Alignment - LSU RNA

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed MAFFT Alignment 7.471Multiple Sequence Alignment - LSU RNA12343691215SE +/- 0.18, N = 3SE +/- 0.02, N = 3SE +/- 0.10, N = 3SE +/- 0.06, N = 312.6212.5212.4412.461. (CC) gcc options: -std=c99 -O3 -lm -lpthread

NCNN

Target: CPU - Model: resnet18

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: resnet181a234714212835SE +/- 0.42, N = 3SE +/- 0.12, N = 3SE +/- 0.09, N = 3SE +/- 0.37, N = 331.2331.3430.9131.09MIN: 30.71 / MAX: 32.24MIN: 31.01 / MAX: 44.79MIN: 30.66 / MAX: 31.53MIN: 30.57 / MAX: 34.741. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

NCNN

Target: CPU - Model: efficientnet-b0

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: efficientnet-b01a2343691215SE +/- 0.05, N = 3SE +/- 0.15, N = 3SE +/- 0.15, N = 3SE +/- 0.19, N = 313.2413.4113.3913.37MIN: 13.14 / MAX: 15.99MIN: 13.16 / MAX: 13.83MIN: 13.17 / MAX: 15.94MIN: 13.14 / MAX: 13.861. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

NCNN

Target: CPU - Model: resnet50

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: resnet501a2341428425670SE +/- 0.71, N = 3SE +/- 0.84, N = 3SE +/- 0.74, N = 3SE +/- 0.65, N = 363.2363.3062.5662.54MIN: 61.59 / MAX: 66.79MIN: 61.67 / MAX: 77.71MIN: 61.64 / MAX: 67.01MIN: 61.66 / MAX: 65.951. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

oneDNN

Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU1a23448121620SE +/- 0.04, N = 3SE +/- 0.00, N = 3SE +/- 0.07, N = 3SE +/- 0.01, N = 313.8914.0313.9214.06MIN: 13.73MIN: 13.95MIN: 13.79MIN: 13.991. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

oneDNN

Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU1a2342K4K6K8K10KSE +/- 88.44, N = 3SE +/- 29.34, N = 3SE +/- 22.47, N = 3SE +/- 25.64, N = 39078.499159.959174.759171.84MIN: 8599.52MIN: 8936.59MIN: 8941.68MIN: 8945.741. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

Coremark

CoreMark Size 666 - Iterations Per Second

OpenBenchmarking.orgIterations/Sec, More Is BetterCoremark 1.0CoreMark Size 666 - Iterations Per Second1a23420K40K60K80K100KSE +/- 1175.16, N = 3SE +/- 272.63, N = 3SE +/- 910.46, N = 15SE +/- 1036.68, N = 1595428.2495542.9694952.4995883.771. (CC) gcc options: -O2 -lrt" -lrt

oneDNN

Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU1a234246810SE +/- 0.00608, N = 3SE +/- 0.00444, N = 3SE +/- 0.00223, N = 3SE +/- 0.02615, N = 37.514427.513997.514667.57690MIN: 7.45MIN: 7.46MIN: 7.46MIN: 7.461. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

oneDNN

Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU1a2343691215SE +/- 0.03, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.06, N = 312.5912.6812.6912.64MIN: 12.45MIN: 12.57MIN: 12.56MIN: 12.51. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

SQLite Speedtest

Timed Time - Size 1,000

OpenBenchmarking.orgSeconds, Fewer Is BetterSQLite Speedtest 3.30Timed Time - Size 1,0001a23420406080100SE +/- 0.16, N = 3SE +/- 0.16, N = 3SE +/- 0.12, N = 3SE +/- 0.17, N = 378.8578.6579.1979.111. (CC) gcc options: -O2 -ldl -lz -lpthread

Timed FFmpeg Compilation

Time To Compile

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed FFmpeg Compilation 4.2.2Time To Compile1a2344080120160200SE +/- 0.30, N = 3SE +/- 0.29, N = 3SE +/- 0.08, N = 3SE +/- 0.09, N = 3163.12162.23162.08162.66

NCNN

Target: CPU - Model: googlenet

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: googlenet1a234714212835SE +/- 0.18, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.03, N = 328.7328.5928.6128.60MIN: 28.43 / MAX: 30.19MIN: 28.51 / MAX: 31.16MIN: 28.51 / MAX: 30.66MIN: 28.48 / MAX: 41.571. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

NCNN

Target: CPU - Model: vgg16

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: vgg161a234306090120150SE +/- 0.25, N = 3SE +/- 0.10, N = 3SE +/- 0.13, N = 3SE +/- 0.46, N = 3134.38134.04133.93134.48MIN: 133.8 / MAX: 148.18MIN: 133.61 / MAX: 145.21MIN: 133.42 / MAX: 157.33MIN: 133.44 / MAX: 146.51. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

NCNN

Target: CPU - Model: blazeface

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: blazeface1a2340.60531.21061.81592.42123.0265SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 32.682.682.692.68MIN: 2.65 / MAX: 2.78MIN: 2.65 / MAX: 2.87MIN: 2.65 / MAX: 3.46MIN: 2.65 / MAX: 2.871. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

oneDNN

Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU1a23448121620SE +/- 0.04, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 315.2015.1515.1615.15MIN: 15.09MIN: 15.1MIN: 15.1MIN: 15.091. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

Timed HMMer Search

Pfam Database Search

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed HMMer Search 3.3.1Pfam Database Search1234306090120150SE +/- 0.03, N = 3SE +/- 0.17, N = 3SE +/- 0.10, N = 3SE +/- 0.18, N = 3140.06140.51140.26140.241. (CC) gcc options: -O3 -pthread -lhmmer -leasel -lm

NCNN

Target: CPU - Model: shufflenet-v2

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: shufflenet-v21a2343691215SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 310.7810.7810.8110.79MIN: 10.74 / MAX: 13.51MIN: 10.73 / MAX: 11.61MIN: 10.77 / MAX: 11.05MIN: 10.74 / MAX: 11.011. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

simdjson

Throughput Test: Kostya

OpenBenchmarking.orgGB/s, More Is Bettersimdjson 0.7.1Throughput Test: Kostya12340.13280.26560.39840.53120.664SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 30.590.590.590.591. (CXX) g++ options: -O3 -pthread

Phoronix Test Suite v10.8.4