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
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.
a:
Processor: AMD Ryzen Threadripper 3990X 64-Core @ 2.90GHz (64 Cores / 128 Threads), Motherboard: Gigabyte TRX40 AORUS PRO WIFI (F6 BIOS), Chipset: AMD Starship/Matisse, Memory: 128GB, Disk: Samsung SSD 970 EVO Plus 500GB, Graphics: AMD Radeon RX 5700 8GB (1750/875MHz), Audio: AMD Navi 10 HDMI Audio, Monitor: DELL P2415Q, Network: Intel I211 + Intel Wi-Fi 6 AX200
OS: Ubuntu 23.04, Kernel: 6.2.0-26-generic (x86_64), Desktop: GNOME Shell 44.0, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 23.0.2 (LLVM 15.0.7 DRM 3.49), Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 3840x2160
b:
Processor: AMD Ryzen Threadripper 3990X 64-Core @ 2.90GHz (64 Cores / 128 Threads), Motherboard: Gigabyte TRX40 AORUS PRO WIFI (F6 BIOS), Chipset: AMD Starship/Matisse, Memory: 128GB, Disk: Samsung SSD 970 EVO Plus 500GB, Graphics: AMD Radeon RX 5700 8GB (1750/875MHz), Audio: AMD Navi 10 HDMI Audio, Monitor: DELL P2415Q, Network: Intel I211 + Intel Wi-Fi 6 AX200
OS: Ubuntu 23.04, Kernel: 6.2.0-26-generic (x86_64), Desktop: GNOME Shell 44.0, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 23.0.2 (LLVM 15.0.7 DRM 3.49), Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 3840x2160
c:
Processor: AMD Ryzen Threadripper 3990X 64-Core @ 2.90GHz (64 Cores / 128 Threads), Motherboard: Gigabyte TRX40 AORUS PRO WIFI (F6 BIOS), Chipset: AMD Starship/Matisse, Memory: 128GB, Disk: Samsung SSD 970 EVO Plus 500GB, Graphics: AMD Radeon RX 5700 8GB (1750/875MHz), Audio: AMD Navi 10 HDMI Audio, Monitor: DELL P2415Q, Network: Intel I211 + Intel Wi-Fi 6 AX200
OS: Ubuntu 23.04, Kernel: 6.2.0-26-generic (x86_64), Desktop: GNOME Shell 44.0, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 23.0.2 (LLVM 15.0.7 DRM 3.49), Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 3840x2160
NCNN 20230517
Target: CPU - Model: mobilenet
ms < Lower Is Better
a . 25.21 |==================================================================
b . 25.78 |====================================================================
c . 25.96 |====================================================================
NCNN 20230517
Target: CPU-v2-v2 - Model: mobilenet-v2
ms < Lower Is Better
a . 13.83 |===========================================================
b . 14.49 |==============================================================
c . 16.01 |====================================================================
NCNN 20230517
Target: CPU-v3-v3 - Model: mobilenet-v3
ms < Lower Is Better
a . 12.73 |================================================================
b . 13.45 |===================================================================
c . 13.60 |====================================================================
NCNN 20230517
Target: CPU - Model: shufflenet-v2
ms < Lower Is Better
a . 14.08 |===================================================================
b . 14.38 |====================================================================
c . 14.12 |===================================================================
NCNN 20230517
Target: CPU - Model: mnasnet
ms < Lower Is Better
a . 13.13 |==========================================================
b . 12.90 |=========================================================
c . 15.27 |====================================================================
NCNN 20230517
Target: CPU - Model: efficientnet-b0
ms < Lower Is Better
a . 18.00 |==============================================================
b . 19.69 |====================================================================
c . 19.06 |==================================================================
NCNN 20230517
Target: CPU - Model: blazeface
ms < Lower Is Better
a . 5.89 |=========================================================
b . 7.12 |=====================================================================
c . 6.95 |===================================================================
NCNN 20230517
Target: CPU - Model: googlenet
ms < Lower Is Better
a . 30.87 |==================================================================
b . 31.55 |====================================================================
c . 31.64 |====================================================================
NCNN 20230517
Target: CPU - Model: vgg16
ms < Lower Is Better
a . 45.64 |=================================================================
b . 47.53 |====================================================================
c . 46.88 |===================================================================
NCNN 20230517
Target: CPU - Model: resnet18
ms < Lower Is Better
a . 19.07 |===================================================================
b . 19.40 |====================================================================
c . 18.91 |==================================================================
NCNN 20230517
Target: CPU - Model: alexnet
ms < Lower Is Better
a . 11.76 |=========================================================
b . 13.97 |====================================================================
c . 12.37 |============================================================
NCNN 20230517
Target: CPU - Model: resnet50
ms < Lower Is Better
a . 35.20 |=============================================================
b . 39.03 |====================================================================
c . 38.18 |===================================================================
NCNN 20230517
Target: CPU - Model: yolov4-tiny
ms < Lower Is Better
a . 37.72 |====================================================================
b . 37.38 |===================================================================
c . 37.14 |===================================================================
NCNN 20230517
Target: CPU - Model: squeezenet_ssd
ms < Lower Is Better
a . 22.30 |==================================================================
b . 22.27 |==================================================================
c . 22.89 |====================================================================
NCNN 20230517
Target: CPU - Model: regnety_400m
ms < Lower Is Better
a . 45.43 |================================================================
b . 48.03 |====================================================================
c . 47.02 |===================================================================
NCNN 20230517
Target: CPU - Model: vision_transformer
ms < Lower Is Better
a . 73.47 |==================================================================
b . 74.11 |==================================================================
c . 75.96 |====================================================================
NCNN 20230517
Target: CPU - Model: FastestDet
ms < Lower Is Better
a . 14.66 |==============================================================
b . 13.70 |==========================================================
c . 16.03 |====================================================================
NCNN 20230517
Target: Vulkan GPU - Model: mobilenet
ms < Lower Is Better
a . 24.66 |==================================================================
b . 25.25 |====================================================================
c . 25.37 |====================================================================
NCNN 20230517
Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2
ms < Lower Is Better
a . 15.71 |====================================================================
b . 14.78 |================================================================
c . 13.63 |===========================================================
NCNN 20230517
Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3
ms < Lower Is Better
a . 12.97 |===================================================================
b . 13.25 |====================================================================
c . 12.57 |=================================================================
NCNN 20230517
Target: Vulkan GPU - Model: shufflenet-v2
ms < Lower Is Better
a . 14.75 |====================================================================
b . 14.27 |==================================================================
c . 13.29 |=============================================================
NCNN 20230517
Target: Vulkan GPU - Model: mnasnet
ms < Lower Is Better
a . 14.18 |====================================================================
b . 13.72 |==================================================================
c . 12.93 |==============================================================
NCNN 20230517
Target: Vulkan GPU - Model: efficientnet-b0
ms < Lower Is Better
a . 18.42 |================================================================
b . 19.47 |====================================================================
c . 18.02 |===============================================================
NCNN 20230517
Target: Vulkan GPU - Model: blazeface
ms < Lower Is Better
a . 7.22 |=====================================================================
b . 7.09 |====================================================================
c . 6.08 |==========================================================
NCNN 20230517
Target: Vulkan GPU - Model: googlenet
ms < Lower Is Better
a . 31.43 |====================================================================
b . 31.24 |====================================================================
c . 31.46 |====================================================================
NCNN 20230517
Target: Vulkan GPU - Model: vgg16
ms < Lower Is Better
a . 47.52 |===================================================================
b . 48.13 |====================================================================
c . 47.50 |===================================================================
NCNN 20230517
Target: Vulkan GPU - Model: resnet18
ms < Lower Is Better
a . 19.20 |===================================================================
b . 19.42 |====================================================================
c . 19.04 |===================================================================
NCNN 20230517
Target: Vulkan GPU - Model: alexnet
ms < Lower Is Better
a . 15.22 |===================================================================
b . 15.34 |====================================================================
c . 13.07 |==========================================================
NCNN 20230517
Target: Vulkan GPU - Model: resnet50
ms < Lower Is Better
a . 38.91 |==================================================================
b . 39.84 |====================================================================
c . 38.43 |==================================================================
NCNN 20230517
Target: Vulkan GPU - Model: yolov4-tiny
ms < Lower Is Better
a . 36.72 |==================================================================
b . 37.79 |====================================================================
c . 37.36 |===================================================================
NCNN 20230517
Target: Vulkan GPU - Model: squeezenet_ssd
ms < Lower Is Better
a . 21.81 |===================================================================
b . 22.01 |====================================================================
c . 21.78 |===================================================================
NCNN 20230517
Target: Vulkan GPU - Model: regnety_400m
ms < Lower Is Better
a . 46.73 |====================================================================
b . 46.22 |===================================================================
c . 46.10 |===================================================================
NCNN 20230517
Target: Vulkan GPU - Model: vision_transformer
ms < Lower Is Better
a . 75.17 |====================================================================
b . 72.26 |=================================================================
c . 72.70 |==================================================================
NCNN 20230517
Target: Vulkan GPU - Model: FastestDet
ms < Lower Is Better
a . 14.25 |===================================================================
b . 14.53 |====================================================================
c . 13.88 |=================================================================
VkFFT 1.2.31
Test: FFT + iFFT R2C / C2R
Benchmark Score > Higher Is Better
a . 25525 |====================================================================
b . 25447 |====================================================================
c . 25451 |====================================================================
VkFFT 1.2.31
Test: FFT + iFFT C2C 1D batched in half precision
Benchmark Score > Higher Is Better
a . 100903 |===================================================================
b . 101063 |===================================================================
c . 100839 |===================================================================
VkFFT 1.2.31
Test: FFT + iFFT C2C Bluestein in single precision
Benchmark Score > Higher Is Better
a . 7268 |=====================================================================
b . 7258 |=====================================================================
c . 7259 |=====================================================================
VkFFT 1.2.31
Test: FFT + iFFT C2C 1D batched in double precision
Benchmark Score > Higher Is Better
a . 18431 |====================================================================
b . 18428 |====================================================================
c . 18426 |====================================================================
VkFFT 1.2.31
Test: FFT + iFFT C2C 1D batched in single precision
Benchmark Score > Higher Is Better
a . 58944 |====================================================================
b . 58947 |====================================================================
c . 58938 |====================================================================
VkFFT 1.2.31
Test: FFT + iFFT C2C multidimensional in single precision
Benchmark Score > Higher Is Better
a . 16993 |====================================================================
b . 16976 |====================================================================
c . 16967 |====================================================================
VkFFT 1.2.31
Test: FFT + iFFT C2C Bluestein benchmark in double precision
Benchmark Score > Higher Is Better
a . 3066 |=====================================================================
b . 3064 |=====================================================================
c . 3064 |=====================================================================
VkFFT 1.2.31
Test: FFT + iFFT C2C 1D batched in single precision, no reshuffling
Benchmark Score > Higher Is Better
a . 64140 |====================================================================
b . 64139 |====================================================================
c . 64131 |====================================================================
vkpeak 20230730
fp32-scalar
GFLOPS > Higher Is Better
a . 7836.61 |==================================================================
b . 7856.19 |==================================================================
c . 7866.83 |==================================================================
vkpeak 20230730
fp32-vec4
GFLOPS > Higher Is Better
a . 7781.34 |==================================================================
b . 7808.56 |==================================================================
c . 7808.48 |==================================================================
vkpeak 20230730
fp16-scalar
GFLOPS > Higher Is Better
a . 7853.66 |==================================================================
b . 7860.29 |==================================================================
c . 7866.33 |==================================================================
vkpeak 20230730
fp16-vec4
GFLOPS > Higher Is Better
a . 12516.94 |=================================================================
b . 12550.91 |=================================================================
c . 12559.31 |=================================================================
vkpeak 20230730
fp64-scalar
GFLOPS > Higher Is Better
a . 493.36 |===================================================================
b . 493.01 |===================================================================
c . 493.51 |===================================================================
vkpeak 20230730
fp64-vec4
GFLOPS > Higher Is Better
a . 493.28 |===================================================================
b . 492.96 |===================================================================
c . 493.57 |===================================================================
vkpeak 20230730
int32-scalar
GIOPS > Higher Is Better
a . 1214.41 |==================================================================
b . 1213.48 |==================================================================
c . 1214.40 |==================================================================
vkpeak 20230730
int32-vec4
GIOPS > Higher Is Better
a . 1574.82 |==================================================================
b . 1574.60 |==================================================================
c . 1575.91 |==================================================================
vkpeak 20230730
int16-scalar
GIOPS > Higher Is Better
a . 7856.21 |==================================================================
b . 7852.03 |==================================================================
c . 7857.01 |==================================================================
vkpeak 20230730
int16-vec4
GIOPS > Higher Is Better
a . 12531.35 |=================================================================
b . 12550.38 |=================================================================
c . 12563.14 |=================================================================
VkResample 1.0
Upscale: 2x - Precision: Single
ms < Lower Is Better
a . 12.77 |====================================================================
b . 12.77 |====================================================================
c . 12.78 |====================================================================