AMD Ryzen Threadripper 3990X 64-Core testing with a Gigabyte TRX40 AORUS PRO WIFI (F6 BIOS) and AMD Radeon RX 5700 8GB on Ubuntu 23.04 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 2308016-PTS-VULKANTE10
vulkan tests,
"NCNN 20230517 - Target: CPU - Model: mobilenet",
Lower Results Are Better
"a",25.22,25.3,25.12
"b",26.35,25.55,25.45
"c",25.68,26.38,25.83
"NCNN 20230517 - Target: CPU-v2-v2 - Model: mobilenet-v2",
Lower Results Are Better
"a",10.92,13.9,16.66
"b",13.34,17.5,12.64
"c",14.07,16.56,17.41
"NCNN 20230517 - Target: CPU-v3-v3 - Model: mobilenet-v3",
Lower Results Are Better
"a",10.76,13.49,13.95
"b",13,15.32,12.03
"c",12.47,13.9,14.43
"NCNN 20230517 - Target: CPU - Model: shufflenet-v2",
Lower Results Are Better
"a",11.98,14.22,16.03
"b",15.35,15.26,12.52
"c",12.86,13.32,16.17
"NCNN 20230517 - Target: CPU - Model: mnasnet",
Lower Results Are Better
"a",10.15,13.91,15.32
"b",15,11.84,11.86
"c",13.98,15.79,16.03
"NCNN 20230517 - Target: CPU - Model: efficientnet-b0",
Lower Results Are Better
"a",15.04,18.01,20.94
"b",22.08,20.55,16.44
"c",16.97,19.68,20.52
"NCNN 20230517 - Target: CPU - Model: blazeface",
Lower Results Are Better
"a",4.96,5.73,6.98
"b",7.38,7.97,6.02
"c",6.08,7.42,7.36
"NCNN 20230517 - Target: CPU - Model: googlenet",
Lower Results Are Better
"a",30.87,31.24,30.5
"b",31.13,31.86,31.66
"c",30.89,32.3,31.73
"NCNN 20230517 - Target: CPU - Model: vgg16",
Lower Results Are Better
"a",44.25,45.92,46.76
"b",46.86,47.76,47.96
"c",45.72,46.92,48.01
"NCNN 20230517 - Target: CPU - Model: resnet18",
Lower Results Are Better
"a",18.87,19.39,18.96
"b",19.23,19.82,19.15
"c",18.84,18.95,18.93
"NCNN 20230517 - Target: CPU - Model: alexnet",
Lower Results Are Better
"a",10.63,11.88,12.78
"b",13.28,13.82,14.82
"c",11.9,12.71,12.51
"NCNN 20230517 - Target: CPU - Model: resnet50",
Lower Results Are Better
"a",34.75,35.72,35.13
"b",38.09,39.91,39.09
"c",36.19,38.77,39.59
"NCNN 20230517 - Target: CPU - Model: yolov4-tiny",
Lower Results Are Better
"a",38.35,37.4,37.41
"b",36.49,37.2,38.46
"c",36.64,37.07,37.71
"NCNN 20230517 - Target: CPU - Model: squeezenet_ssd",
Lower Results Are Better
"a",21.87,23.24,21.78
"b",21.9,23.05,21.87
"c",22.84,22.4,23.43
"NCNN 20230517 - Target: CPU - Model: regnety_400m",
Lower Results Are Better
"a",42.64,45.94,47.72
"b",47.25,49.43,47.42
"c",46.45,47.61,47.01
"NCNN 20230517 - Target: CPU - Model: vision_transformer",
Lower Results Are Better
"a",71.11,70.75,78.55
"b",71.68,79.45,71.2
"c",78.78,77.51,71.58
"NCNN 20230517 - Target: CPU - Model: FastestDet",
Lower Results Are Better
"a",12.62,16.04,15.31
"b",14.51,13.9,12.69
"c",16.99,15.35,15.75
"NCNN 20230517 - Target: Vulkan GPU - Model: mobilenet",
Lower Results Are Better
"a",24.43,25.06,24.5
"b",24.94,24.29,26.83,25.66,24.62,23.89,23.55,26.81,25.17,25.68,27.73,23.81
"c",25.44,25.35,25.32
"NCNN 20230517 - Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2",
Lower Results Are Better
"a",11.89,21.63,13.62
"b",11.32,12.8,17.06,17.17,15.23,11.84,14.84,20.19,15,12.12,18.29,11.54
"c",12.2,14.67,14.01
"NCNN 20230517 - Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3",
Lower Results Are Better
"a",11.26,15.65,12.01
"b",11.18,12.4,14.64,16.56,13.45,10.83,12.57,14.4,13.96,11.33,17.04,10.68
"c",12.23,13.22,12.27
"NCNN 20230517 - Target: Vulkan GPU - Model: shufflenet-v2",
Lower Results Are Better
"a",12.86,17.09,14.31
"b",12.32,13.66,15.55,16.41,14.88,12.36,14.15,15.35,14.24,13.16,16.91,12.25
"c",12.9,13.36,13.61
"NCNN 20230517 - Target: Vulkan GPU - Model: mnasnet",
Lower Results Are Better
"a",11.88,18.63,12.03
"b",10.7,11.83,16.17,16.34,14.06,10.62,13.46,17.28,14.85,12.32,16.78,10.25
"c",11.89,15.71,11.2
"NCNN 20230517 - Target: Vulkan GPU - Model: efficientnet-b0",
Lower Results Are Better
"a",17.55,18.95,18.77
"b",15.85,19.18,22.3,23.13,20.66,16.08,18.93,22.69,19.71,16.86,22.68,15.55
"c",17,18.41,18.66
"NCNN 20230517 - Target: Vulkan GPU - Model: blazeface",
Lower Results Are Better
"a",7.04,7.84,6.77
"b",5.46,6.38,8.28,7.93,7.64,5.39,6.23,9.06,7.2,6.33,9.1,6.07
"c",6.46,6.03,5.76
"NCNN 20230517 - Target: Vulkan GPU - Model: googlenet",
Lower Results Are Better
"a",31.35,31.77,31.18
"b",30.91,30.91,31.19,32.36,31.02,30.36,30.62,31.77,31.07,31.53,31.76,31.37
"c",31.57,31.55,31.25
"NCNN 20230517 - Target: Vulkan GPU - Model: vgg16",
Lower Results Are Better
"a",47.5,47.43,47.62
"b",48.35,48.74,48.37,47.78,48.22,47.21,48.22,48.73,47.23,48.22,47.9,48.64
"c",47.52,47.35,47.63
"NCNN 20230517 - Target: Vulkan GPU - Model: resnet18",
Lower Results Are Better
"a",19.13,19.32,19.16
"b",19.85,19.05,18.94,19.46,19.67,19.77,19.35,19.56,18.92,19.29,19.44,19.73
"c",18.77,19.01,19.35
"NCNN 20230517 - Target: Vulkan GPU - Model: alexnet",
Lower Results Are Better
"a",14.5,15.52,15.64
"b",16.01,15.74,14.99,15.04,16.17,15.31,14.76,15.73,14.02,15.52,15.29,15.45
"c",12.53,13.2,13.47
"NCNN 20230517 - Target: Vulkan GPU - Model: resnet50",
Lower Results Are Better
"a",39.54,37.94,39.24
"b",40.3,39.52,39.51,40.62,38.87,38.57,40.11,39.42,39.07,41.43,40.2,40.49
"c",39.35,37.33,38.6
"NCNN 20230517 - Target: Vulkan GPU - Model: yolov4-tiny",
Lower Results Are Better
"a",37.81,36.05,36.29
"b",38.02,38.43,38.11,38.87,37.36,36.52,36.73,37.38,36.19,38.9,38.56,38.44
"c",36.82,37.38,37.88
"NCNN 20230517 - Target: Vulkan GPU - Model: squeezenet_ssd",
Lower Results Are Better
"a",22.21,21.7,21.52
"b",21.48,22.21,21.87,22.08,21.77,22.05,21.89,22.24,22.14,22.41,21.63,22.3
"c",22.08,21.88,21.39
"NCNN 20230517 - Target: Vulkan GPU - Model: regnety_400m",
Lower Results Are Better
"a",46.78,47.35,46.06
"b",44.08,46.28,46.71,48.41,47.3,43.97,45.3,48.27,45.44,45.51,49.08,44.29
"c",47.39,44.87,46.03
"NCNN 20230517 - Target: Vulkan GPU - Model: vision_transformer",
Lower Results Are Better
"a",77.48,77.14,70.89
"b",77.15,70.89,76.73,70.54,70.72,74.66,69.77,70.08,70.43,70.82,75.09,70.28
"c",71.09,70.5,76.52
"NCNN 20230517 - Target: Vulkan GPU - Model: FastestDet",
Lower Results Are Better
"a",12.97,17.22,12.55
"b",11.73,13.14,15.76,15.8,14.63,13.69,11.69,18.58,13.98,13.93,18.06,13.34
"c",14.78,14.26,12.6
"VkFFT 1.2.31 - Test: FFT + iFFT R2C / C2R",
Higher Results Are Better
"a",25673,25448,25455
"b",25456,25443,25443
"c",25447,25454,25451
"VkFFT 1.2.31 - Test: FFT + iFFT C2C 1D batched in half precision",
Higher Results Are Better
"a",101097,100779,100832
"b",101147,101040,101001
"c",101034,100401,101083
"VkFFT 1.2.31 - Test: FFT + iFFT C2C Bluestein in single precision",
Higher Results Are Better
"a",7298,7250,7255
"b",7255,7255,7263
"c",7263,7250,7265
"VkFFT 1.2.31 - Test: FFT + iFFT C2C 1D batched in double precision",
Higher Results Are Better
"a",18419,18438,18437
"b",18430,18421,18433
"c",18422,18427,18428
"VkFFT 1.2.31 - Test: FFT + iFFT C2C 1D batched in single precision",
Higher Results Are Better
"a",58945,58941,58945
"b",58954,58944,58944
"c",58937,58936,58940
"VkFFT 1.2.31 - Test: FFT + iFFT C2C multidimensional in single precision",
Higher Results Are Better
"a",17090,16917,16971
"b",16952,16989,16987
"c",16981,16949,16972
"VkFFT 1.2.31 - Test: FFT + iFFT C2C Bluestein benchmark in double precision",
Higher Results Are Better
"a",3075,3062,3062
"b",3066,3063,3063
"c",3067,3063,3062
"VkFFT 1.2.31 - Test: FFT + iFFT C2C 1D batched in single precision, no reshuffling",
Higher Results Are Better
"a",64142,64150,64128
"b",64150,64132,64136
"c",64116,64138,64140
"vkpeak 20230730 - fp32-scalar",
Higher Results Are Better
"a",7837.73,7836.51,7835.58
"b",7858.33,7854.8,7855.43
"c",7870.56,7865.83,7864.1
"vkpeak 20230730 - fp32-vec4",
Higher Results Are Better
"a",7796.47,7773.6,7773.94
"b",7822.87,7802.16,7800.65
"c",7825.09,7800.78,7799.57
"vkpeak 20230730 - fp16-scalar",
Higher Results Are Better
"a",7856.23,7851.62,7853.14
"b",7861.8,7859.54,7859.54
"c",7869.95,7865.16,7863.89
"vkpeak 20230730 - fp16-vec4",
Higher Results Are Better
"a",12520.84,12514.7,12515.28
"b",12550.07,12549.48,12553.19
"c",12561.81,12557.9,12558.22
"vkpeak 20230730 - fp64-scalar",
Higher Results Are Better
"a",493.52,493.38,493.19
"b",492.98,492.99,493.06
"c",493.63,493.5,493.39
"vkpeak 20230730 - fp64-vec4",
Higher Results Are Better
"a",493.49,493.23,493.13
"b",493.02,492.9,492.96
"c",493.76,493.55,493.4
"vkpeak 20230730 - int32-scalar",
Higher Results Are Better
"a",1214.89,1214.39,1213.96
"b",1213.52,1213.38,1213.54
"c",1214.99,1214.3,1213.91
"vkpeak 20230730 - int32-vec4",
Higher Results Are Better
"a",1575.1,1574.85,1574.5
"b",1574.59,1574.69,1574.51
"c",1576.31,1575.81,1575.6
"vkpeak 20230730 - int16-scalar",
Higher Results Are Better
"a",7856.14,7857.01,7855.49
"b",7852.44,7851.01,7852.64
"c",7858.9,7855.76,7856.38
"vkpeak 20230730 - int16-vec4",
Higher Results Are Better
"a",12532.26,12531.51,12530.28
"b",12550.29,12549.1,12551.76
"c",12565.85,12560.5,12563.08
"VkResample 1.0 - Upscale: 2x - Precision: Single",
Lower Results Are Better
"a",12.772,12.769,12.769
"b",12.774,12.771,12.769
"c",12.774,12.776,12.774