Intel Core i5-10600K testing with a ASUS PRIME Z490M-PLUS (0603 BIOS) and Sapphire AMD Radeon RX 470/480/570/570X/580/580X/590 8GB on Ubuntu 20.04 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 2006163-NE-MKLDNNFFT18
mkl-dnn + fftw
Intel Core i5-10600K testing with a ASUS PRIME Z490M-PLUS (0603 BIOS) and Sapphire AMD Radeon RX 470/480/570/570X/580/580X/590 8GB on Ubuntu 20.04 via the Phoronix Test Suite.
,,"Intel Core i3-10100","Intel Core i5-10600K"
Processor,,Intel Core i3-10100 @ 4.30GHz (4 Cores / 8 Threads),Intel Core i5-10600K @ 4.80GHz (6 Cores / 12 Threads)
Motherboard,,ASUS PRIME Z490M-PLUS (0603 BIOS),ASUS PRIME Z490M-PLUS (0603 BIOS)
Chipset,,Intel Comet Lake PCH,Intel Comet Lake PCH
Memory,,16GB,16GB
Disk,,240GB Force MP510 + 2000GB Samsung SSD 860,240GB Force MP510 + 2000GB Samsung SSD 860
Graphics,,Sapphire AMD Radeon RX 470/480/570/570X/580/580X/590 8GB (1560/2100MHz),Sapphire AMD Radeon RX 470/480/570/570X/580/580X/590 8GB (1560/2100MHz)
Audio,,Realtek ALC887-VD,Realtek ALC887-VD
Monitor,,ASUS MG28U,ASUS MG28U
Network,,Intel,Intel
OS,,Ubuntu 20.04,Ubuntu 20.04
Kernel,,5.7.0-rc6-amd-energy (x86_64) 20200527,5.7.0-rc6-amd-energy (x86_64) 20200527
Desktop,,GNOME Shell 3.36.2,GNOME Shell 3.36.2
Display Server,,X Server 1.20.8,X Server 1.20.8
Display Driver,,modesetting 1.20.8,modesetting 1.20.8
OpenGL,,4.6 Mesa 20.0.4 (LLVM 9.0.1),4.6 Mesa 20.0.4 (LLVM 9.0.1)
Compiler,,GCC 9.3.0,GCC 9.3.0
File-System,,ext4,ext4
Screen Resolution,,3840x2160,3840x2160
,,"Intel Core i3-10100","Intel Core i5-10600K"
"FFTW - Build: Stock - Size: 1D FFT Size 32 (Mflops)",HIB,8698.8,9869.1
"FFTW - Build: Stock - Size: 1D FFT Size 64 (Mflops)",HIB,8482.1,9457.0
"FFTW - Build: Stock - Size: 2D FFT Size 32 (Mflops)",HIB,9711.3,10859
"FFTW - Build: Stock - Size: 2D FFT Size 64 (Mflops)",HIB,8257.5,9279.0
"FFTW - Build: Stock - Size: 1D FFT Size 128 (Mflops)",HIB,7968.3,9205.0
"FFTW - Build: Stock - Size: 1D FFT Size 256 (Mflops)",HIB,8153.3,9197.2
"FFTW - Build: Stock - Size: 1D FFT Size 512 (Mflops)",HIB,8307.4,9436.7
"FFTW - Build: Stock - Size: 2D FFT Size 128 (Mflops)",HIB,7932.2,8708.8
"FFTW - Build: Stock - Size: 2D FFT Size 256 (Mflops)",HIB,7520.5,8467.0
"FFTW - Build: Stock - Size: 2D FFT Size 512 (Mflops)",HIB,7495.8,8434.5
"FFTW - Build: Stock - Size: 1D FFT Size 1024 (Mflops)",HIB,8449.9,9478.6
"FFTW - Build: Stock - Size: 1D FFT Size 2048 (Mflops)",HIB,8070.1,8965.5
"FFTW - Build: Stock - Size: 1D FFT Size 4096 (Mflops)",HIB,7895.1,8752.5
"FFTW - Build: Stock - Size: 2D FFT Size 1024 (Mflops)",HIB,6657.9,7477.3
"FFTW - Build: Stock - Size: 2D FFT Size 2048 (Mflops)",HIB,6258.6,6548.7
"FFTW - Build: Stock - Size: 2D FFT Size 4096 (Mflops)",HIB,5964.1,6334.2
"FFTW - Build: Float + SSE - Size: 1D FFT Size 32 (Mflops)",HIB,16975,18442
"FFTW - Build: Float + SSE - Size: 1D FFT Size 64 (Mflops)",HIB,21112,23300
"FFTW - Build: Float + SSE - Size: 2D FFT Size 32 (Mflops)",HIB,49207,55199
"FFTW - Build: Float + SSE - Size: 2D FFT Size 64 (Mflops)",HIB,43885,49221
"FFTW - Build: Float + SSE - Size: 1D FFT Size 128 (Mflops)",HIB,25205,27902
"FFTW - Build: Float + SSE - Size: 1D FFT Size 256 (Mflops)",HIB,35177,38866
"FFTW - Build: Float + SSE - Size: 1D FFT Size 512 (Mflops)",HIB,44105,49009
"FFTW - Build: Float + SSE - Size: 2D FFT Size 128 (Mflops)",HIB,33950,38420
"FFTW - Build: Float + SSE - Size: 2D FFT Size 256 (Mflops)",HIB,32998,36522
"FFTW - Build: Float + SSE - Size: 2D FFT Size 512 (Mflops)",HIB,34677,38709
"FFTW - Build: Float + SSE - Size: 1D FFT Size 1024 (Mflops)",HIB,47510,53314
"FFTW - Build: Float + SSE - Size: 1D FFT Size 2048 (Mflops)",HIB,47673,53506
"FFTW - Build: Float + SSE - Size: 1D FFT Size 4096 (Mflops)",HIB,44598,49493
"FFTW - Build: Float + SSE - Size: 2D FFT Size 1024 (Mflops)",HIB,29909,37698
"FFTW - Build: Float + SSE - Size: 2D FFT Size 2048 (Mflops)",HIB,26279,26053
"FFTW - Build: Float + SSE - Size: 2D FFT Size 4096 (Mflops)",HIB,24354,22767
"oneDNN MKL-DNN - Harness: IP Batch 1D - Data Type: f32 (ms)",LIB,7.32233,4.54913
"oneDNN MKL-DNN - Harness: IP Batch All - Data Type: f32 (ms)",LIB,101.923,74.6247
"oneDNN MKL-DNN - Harness: IP Batch 1D - Data Type: u8s8f32 (ms)",LIB,3.13627,2.02339
"oneDNN MKL-DNN - Harness: IP Batch All - Data Type: u8s8f32 (ms)",LIB,42.9357,30.0636
"oneDNN MKL-DNN - Harness: Deconvolution Batch deconv_1d - Data Type: f32 (ms)",LIB,8.42008,5.46402
"oneDNN MKL-DNN - Harness: Deconvolution Batch deconv_3d - Data Type: f32 (ms)",LIB,12.5169,8.48212
"oneDNN MKL-DNN - Harness: Deconvolution Batch deconv_1d - Data Type: u8s8f32 (ms)",LIB,318.859,222.388
"oneDNN MKL-DNN - Harness: Deconvolution Batch deconv_3d - Data Type: u8s8f32 (ms)",LIB,6.47082,4.41247
"oneDNN MKL-DNN - Harness: Recurrent Neural Network Training - Data Type: f32 (ms)",LIB,428.081,285.862
"oneDNN MKL-DNN - Harness: Recurrent Neural Network Inference - Data Type: f32 (ms)",LIB,113.142,52.0325