AMD Ryzen 9 7950X 16-Core testing with a ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS) and AMD Radeon RX 6700 XT 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 2308012-PTS-VULKANBE49
vulkan benchmarks
AMD Ryzen 9 7950X 16-Core testing with a ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS) and AMD Radeon RX 6700 XT on Ubuntu 23.04 via the Phoronix Test Suite.
a:
Processor: AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads), Motherboard: ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS), Chipset: AMD Device 14d8, Memory: 32GB, Disk: Western Digital WD_BLACK SN850X 1000GB + 4001GB, Graphics: AMD Radeon RX 6700 XT (2855/1000MHz), Audio: AMD Navi 21/23, Monitor: ASUS MG28U, Network: Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411
OS: Ubuntu 23.04, Kernel: 6.4.6-060406-generic (x86_64), Desktop: GNOME Shell 44.2, Display Server: X Server 1.21.1.7 + Wayland, OpenGL: 4.6 Mesa 23.3~git2307260600.87109c~oibaf~l (git-87109c3 2023-07-26 lunar-oibaf-ppa) (LLVM 15.0.7 DRM 3.52), Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 3840x2160
b:
Processor: AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads), Motherboard: ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS), Chipset: AMD Device 14d8, Memory: 32GB, Disk: Western Digital WD_BLACK SN850X 1000GB + 4001GB, Graphics: AMD Radeon RX 6700 XT (2855/1000MHz), Audio: AMD Navi 21/23, Monitor: ASUS MG28U, Network: Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411
OS: Ubuntu 23.04, Kernel: 6.4.6-060406-generic (x86_64), Desktop: GNOME Shell 44.2, Display Server: X Server 1.21.1.7 + Wayland, OpenGL: 4.6 Mesa 23.3~git2307260600.87109c~oibaf~l (git-87109c3 2023-07-26 lunar-oibaf-ppa) (LLVM 15.0.7 DRM 3.52), Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 3840x2160
c:
Processor: AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads), Motherboard: ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS), Chipset: AMD Device 14d8, Memory: 32GB, Disk: Western Digital WD_BLACK SN850X 1000GB + 4001GB, Graphics: AMD Radeon RX 6700 XT (2855/1000MHz), Audio: AMD Navi 21/23, Monitor: ASUS MG28U, Network: Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411
OS: Ubuntu 23.04, Kernel: 6.4.6-060406-generic (x86_64), Desktop: GNOME Shell 44.2, Display Server: X Server 1.21.1.7 + Wayland, OpenGL: 4.6 Mesa 23.3~git2307260600.87109c~oibaf~l (git-87109c3 2023-07-26 lunar-oibaf-ppa) (LLVM 15.0.7 DRM 3.52), Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 3840x2160
vkpeak 20230730
fp32-scalar
GFLOPS > Higher Is Better
a . 13190.09 |=================================================================
b . 12807.06 |===============================================================
c . 12860.56 |===============================================================
vkpeak 20230730
fp32-vec4
GFLOPS > Higher Is Better
a . 12730.08 |=================================================================
b . 12808.59 |=================================================================
c . 12822.01 |=================================================================
vkpeak 20230730
fp16-scalar
GFLOPS > Higher Is Better
a . 13154.15 |=================================================================
b . 13145.19 |=================================================================
c . 13136.79 |=================================================================
vkpeak 20230730
fp16-vec4
GFLOPS > Higher Is Better
a . 23232.42 |=================================================================
b . 23390.44 |=================================================================
c . 23387.26 |=================================================================
vkpeak 20230730
fp64-scalar
GFLOPS > Higher Is Better
a . 841.40 |===================================================================
b . 839.20 |===================================================================
c . 839.01 |===================================================================
vkpeak 20230730
fp64-vec4
GFLOPS > Higher Is Better
a . 841.80 |===================================================================
b . 836.55 |===================================================================
c . 836.16 |===================================================================
vkpeak 20230730
int32-scalar
GIOPS > Higher Is Better
a . 2272.62 |==================================================================
b . 2269.25 |==================================================================
c . 2269.06 |==================================================================
vkpeak 20230730
int32-vec4
GIOPS > Higher Is Better
a . 2658.73 |==================================================================
b . 2640.08 |==================================================================
c . 2638.69 |==================================================================
vkpeak 20230730
int16-scalar
GIOPS > Higher Is Better
a . 13102.75 |=================================================================
b . 13070.81 |=================================================================
c . 13063.86 |=================================================================
vkpeak 20230730
int16-vec4
GIOPS > Higher Is Better
a . 23123.77 |================================================================
b . 23396.59 |=================================================================
c . 23385.44 |=================================================================
VkFFT 1.2.31
Test: FFT + iFFT R2C / C2R
Benchmark Score > Higher Is Better
a . 42105 |===================================================================
b . 42163 |===================================================================
c . 43021 |====================================================================
VkFFT 1.2.31
Test: FFT + iFFT C2C 1D batched in half precision
Benchmark Score > Higher Is Better
a . 91597 |====================================================================
b . 91812 |====================================================================
c . 91744 |====================================================================
VkFFT 1.2.31
Test: FFT + iFFT C2C Bluestein in single precision
Benchmark Score > Higher Is Better
a . 11340 |====================================================================
b . 11273 |====================================================================
c . 11311 |====================================================================
VkFFT 1.2.31
Test: FFT + iFFT C2C 1D batched in double precision
Benchmark Score > Higher Is Better
a . 20816 |====================================================================
b . 20822 |====================================================================
c . 20847 |====================================================================
VkFFT 1.2.31
Test: FFT + iFFT C2C 1D batched in single precision
Benchmark Score > Higher Is Better
a . 47887 |====================================================================
b . 47948 |====================================================================
c . 47971 |====================================================================
VkFFT 1.2.31
Test: FFT + iFFT C2C multidimensional in single precision
Benchmark Score > Higher Is Better
a . 33001 |====================================================================
b . 32751 |===================================================================
c . 32812 |====================================================================
VkFFT 1.2.31
Test: FFT + iFFT C2C Bluestein benchmark in double precision
Benchmark Score > Higher Is Better
a . 4717 |=====================================================================
b . 4695 |=====================================================================
c . 4670 |====================================================================
VkFFT 1.2.31
Test: FFT + iFFT C2C 1D batched in single precision, no reshuffling
Benchmark Score > Higher Is Better
a . 50504 |====================================================================
b . 50643 |====================================================================
c . 50596 |====================================================================
VkResample 1.0
Upscale: 2x - Precision: Single
ms < Lower Is Better
a . 11.69 |====================================================================
b . 11.69 |====================================================================
c . 11.69 |====================================================================
NCNN 20230517
Target: CPU - Model: mobilenet
ms < Lower Is Better
a . 8.05 |=====================================================================
b . 7.97 |====================================================================
c . 8.02 |=====================================================================
NCNN 20230517
Target: CPU-v2-v2 - Model: mobilenet-v2
ms < Lower Is Better
a . 3.16 |=====================================================================
b . 3.16 |=====================================================================
c . 3.18 |=====================================================================
NCNN 20230517
Target: CPU - Model: shufflenet-v2
ms < Lower Is Better
a . 3.34 |=====================================================================
b . 3.34 |=====================================================================
c . 3.35 |=====================================================================
NCNN 20230517
Target: CPU - Model: mnasnet
ms < Lower Is Better
a . 2.97 |=====================================================================
b . 2.97 |=====================================================================
c . 2.99 |=====================================================================
NCNN 20230517
Target: CPU - Model: efficientnet-b0
ms < Lower Is Better
a . 3.90 |=====================================================================
b . 3.85 |====================================================================
c . 3.88 |=====================================================================
NCNN 20230517
Target: CPU - Model: blazeface
ms < Lower Is Better
a . 1.38 |=====================================================================
b . 1.38 |=====================================================================
c . 1.39 |=====================================================================
NCNN 20230517
Target: CPU - Model: googlenet
ms < Lower Is Better
a . 7.94 |=====================================================================
b . 7.82 |====================================================================
c . 7.93 |=====================================================================
NCNN 20230517
Target: CPU - Model: vgg16
ms < Lower Is Better
a . 23.75 |====================================================================
b . 23.49 |===================================================================
c . 23.45 |===================================================================
NCNN 20230517
Target: CPU - Model: resnet18
ms < Lower Is Better
a . 5.29 |=====================================================================
b . 5.20 |====================================================================
c . 5.24 |====================================================================
NCNN 20230517
Target: CPU - Model: alexnet
ms < Lower Is Better
a . 4.41 |=====================================================================
b . 4.32 |====================================================================
c . 4.31 |===================================================================
NCNN 20230517
Target: CPU - Model: resnet50
ms < Lower Is Better
a . 10.20 |====================================================================
b . 10.01 |===================================================================
c . 10.11 |===================================================================
NCNN 20230517
Target: CPU - Model: yolov4-tiny
ms < Lower Is Better
a . 12.90 |====================================================================
b . 12.74 |===================================================================
c . 12.81 |====================================================================
NCNN 20230517
Target: CPU - Model: squeezenet_ssd
ms < Lower Is Better
a . 7.07 |=====================================================================
b . 7.06 |=====================================================================
c . 7.10 |=====================================================================
NCNN 20230517
Target: CPU - Model: regnety_400m
ms < Lower Is Better
a . 8.18 |====================================================================
b . 8.18 |====================================================================
c . 8.27 |=====================================================================
NCNN 20230517
Target: CPU - Model: vision_transformer
ms < Lower Is Better
a . 32.49 |====================================================================
b . 31.95 |===================================================================
c . 31.77 |==================================================================
NCNN 20230517
Target: CPU - Model: FastestDet
ms < Lower Is Better
a . 3.62 |=============================================================
b . 4.05 |====================================================================
c . 4.11 |=====================================================================
NCNN 20230517
Target: CPU-v3-v3 - Model: mobilenet-v3
ms < Lower Is Better
a . 3.18 |=====================================================================
c . 3.17 |=====================================================================
NCNN 20230517
Target: Vulkan GPU - Model: mobilenet
ms < Lower Is Better
a . 8.05 |=====================================================================
b . 8.04 |=====================================================================
c . 8.03 |=====================================================================
NCNN 20230517
Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2
ms < Lower Is Better
a . 3.17 |=====================================================================
b . 3.14 |====================================================================
c . 3.13 |====================================================================
NCNN 20230517
Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3
ms < Lower Is Better
a . 3.17 |====================================================================
c . 3.20 |=====================================================================
NCNN 20230517
Target: Vulkan GPU - Model: shufflenet-v2
ms < Lower Is Better
a . 3.35 |=====================================================================
b . 3.33 |=====================================================================
c . 3.32 |====================================================================
NCNN 20230517
Target: Vulkan GPU - Model: mnasnet
ms < Lower Is Better
a . 2.98 |=====================================================================
b . 2.95 |====================================================================
c . 2.96 |=====================================================================
NCNN 20230517
Target: Vulkan GPU - Model: efficientnet-b0
ms < Lower Is Better
a . 3.86 |=====================================================================
b . 3.82 |====================================================================
c . 3.83 |====================================================================
NCNN 20230517
Target: Vulkan GPU - Model: blazeface
ms < Lower Is Better
a . 1.38 |=====================================================================
b . 1.37 |=====================================================================
c . 1.37 |=====================================================================
NCNN 20230517
Target: Vulkan GPU - Model: googlenet
ms < Lower Is Better
a . 7.90 |=====================================================================
b . 7.85 |=====================================================================
c . 7.80 |====================================================================
NCNN 20230517
Target: Vulkan GPU - Model: vgg16
ms < Lower Is Better
a . 23.51 |====================================================================
b . 23.56 |====================================================================
c . 23.54 |====================================================================
NCNN 20230517
Target: Vulkan GPU - Model: resnet18
ms < Lower Is Better
a . 5.28 |=====================================================================
b . 5.23 |====================================================================
c . 5.21 |====================================================================
NCNN 20230517
Target: Vulkan GPU - Model: alexnet
ms < Lower Is Better
a . 4.31 |=====================================================================
b . 4.33 |=====================================================================
c . 4.33 |=====================================================================
NCNN 20230517
Target: Vulkan GPU - Model: resnet50
ms < Lower Is Better
a . 10.01 |====================================================================
b . 10.00 |====================================================================
c . 10.00 |====================================================================
NCNN 20230517
Target: Vulkan GPU - Model: yolov4-tiny
ms < Lower Is Better
a . 12.84 |====================================================================
b . 12.87 |====================================================================
c . 12.81 |====================================================================
NCNN 20230517
Target: Vulkan GPU - Model: squeezenet_ssd
ms < Lower Is Better
a . 7.09 |=====================================================================
b . 7.07 |=====================================================================
c . 7.06 |=====================================================================
NCNN 20230517
Target: Vulkan GPU - Model: regnety_400m
ms < Lower Is Better
a . 8.16 |=====================================================================
b . 8.21 |=====================================================================
c . 8.00 |===================================================================
NCNN 20230517
Target: Vulkan GPU - Model: vision_transformer
ms < Lower Is Better
a . 31.88 |====================================================================
b . 31.85 |====================================================================
c . 31.79 |====================================================================
NCNN 20230517
Target: Vulkan GPU - Model: FastestDet
ms < Lower Is Better
a . 4.10 |=====================================================================
b . 4.07 |====================================================================
c . 4.09 |=====================================================================
NCNN 20230517
Target: CPU-v3-v3-v3 - Model: mobilenet
ms < Lower Is Better
b . 8.01 |=====================================================================
c . 8.00 |=====================================================================
NCNN 20230517
Target: CPU-v3-v3-v3-v2-v2 - Model: mobilenet-v2
ms < Lower Is Better
b . 3.15 |=====================================================================
c . 3.14 |=====================================================================
NCNN 20230517
Target: CPU-v3-v3-v3-v3-v3 - Model: mobilenet-v3
ms < Lower Is Better
b . 3.16 |=====================================================================
c . 3.16 |=====================================================================
NCNN 20230517
Target: CPU-v3-v3-v3 - Model: shufflenet-v2
ms < Lower Is Better
b . 3.33 |=====================================================================
c . 3.34 |=====================================================================
NCNN 20230517
Target: CPU-v3-v3-v3 - Model: mnasnet
ms < Lower Is Better
b . 2.97 |=====================================================================
c . 2.97 |=====================================================================
NCNN 20230517
Target: CPU-v3-v3-v3 - Model: efficientnet-b0
ms < Lower Is Better
b . 3.82 |====================================================================
c . 3.89 |=====================================================================
NCNN 20230517
Target: CPU-v3-v3-v3 - Model: blazeface
ms < Lower Is Better
b . 1.37 |=====================================================================
c . 1.38 |=====================================================================
NCNN 20230517
Target: CPU-v3-v3-v3 - Model: googlenet
ms < Lower Is Better
b . 7.84 |=====================================================================
c . 7.88 |=====================================================================
NCNN 20230517
Target: CPU-v3-v3-v3 - Model: vgg16
ms < Lower Is Better
b . 23.50 |===================================================================
c . 23.99 |====================================================================
NCNN 20230517
Target: CPU-v3-v3-v3 - Model: resnet18
ms < Lower Is Better
b . 5.21 |====================================================================
c . 5.26 |=====================================================================
NCNN 20230517
Target: CPU-v3-v3-v3 - Model: alexnet
ms < Lower Is Better
b . 4.29 |=====================================================================
c . 4.28 |=====================================================================
NCNN 20230517
Target: CPU-v3-v3-v3 - Model: resnet50
ms < Lower Is Better
b . 10.01 |==================================================================
c . 10.33 |====================================================================
NCNN 20230517
Target: CPU-v3-v3-v3 - Model: yolov4-tiny
ms < Lower Is Better
b . 12.98 |====================================================================
c . 12.89 |====================================================================
NCNN 20230517
Target: CPU-v3-v3-v3 - Model: squeezenet_ssd
ms < Lower Is Better
b . 7.03 |=====================================================================
c . 7.04 |=====================================================================
NCNN 20230517
Target: CPU-v3-v3-v3 - Model: regnety_400m
ms < Lower Is Better
b . 8.05 |====================================================================
c . 8.14 |=====================================================================
NCNN 20230517
Target: CPU-v3-v3-v3 - Model: vision_transformer
ms < Lower Is Better
b . 31.65 |====================================================================
c . 31.78 |====================================================================
NCNN 20230517
Target: CPU-v3-v3-v3 - Model: FastestDet
ms < Lower Is Better
b . 4.07 |=====================================================================
c . 4.08 |=====================================================================
NCNN 20230517
Target: Vulkan GPU-v3-v3-v3 - Model: mobilenet
ms < Lower Is Better
b . 8.00 |=====================================================================
c . 7.95 |=====================================================================
NCNN 20230517
Target: Vulkan GPU-v3-v3-v3-v2-v2 - Model: mobilenet-v2
ms < Lower Is Better
b . 3.15 |=====================================================================
c . 3.15 |=====================================================================
NCNN 20230517
Target: Vulkan GPU-v3-v3-v3-v3-v3 - Model: mobilenet-v3
ms < Lower Is Better
b . 3.16 |=====================================================================
c . 3.17 |=====================================================================
NCNN 20230517
Target: Vulkan GPU-v3-v3-v3 - Model: shufflenet-v2
ms < Lower Is Better
b . 3.33 |=====================================================================
c . 3.33 |=====================================================================
NCNN 20230517
Target: Vulkan GPU-v3-v3-v3 - Model: mnasnet
ms < Lower Is Better
b . 2.96 |=====================================================================
c . 2.96 |=====================================================================
NCNN 20230517
Target: Vulkan GPU-v3-v3-v3 - Model: efficientnet-b0
ms < Lower Is Better
b . 3.85 |=====================================================================
c . 3.82 |====================================================================
NCNN 20230517
Target: Vulkan GPU-v3-v3-v3 - Model: blazeface
ms < Lower Is Better
b . 1.37 |=====================================================================
c . 1.36 |====================================================================
NCNN 20230517
Target: Vulkan GPU-v3-v3-v3 - Model: googlenet
ms < Lower Is Better
b . 7.97 |=====================================================================
c . 7.83 |====================================================================
NCNN 20230517
Target: Vulkan GPU-v3-v3-v3 - Model: vgg16
ms < Lower Is Better
b . 23.42 |====================================================================
c . 23.54 |====================================================================
NCNN 20230517
Target: Vulkan GPU-v3-v3-v3 - Model: resnet18
ms < Lower Is Better
b . 5.42 |=====================================================================
c . 5.23 |===================================================================
NCNN 20230517
Target: Vulkan GPU-v3-v3-v3 - Model: alexnet
ms < Lower Is Better
b . 4.42 |=====================================================================
c . 4.30 |===================================================================
NCNN 20230517
Target: Vulkan GPU-v3-v3-v3 - Model: resnet50
ms < Lower Is Better
b . 9.87 |===================================================================
c . 10.03 |====================================================================
NCNN 20230517
Target: Vulkan GPU-v3-v3-v3 - Model: yolov4-tiny
ms < Lower Is Better
b . 12.77 |====================================================================
c . 12.86 |====================================================================
NCNN 20230517
Target: Vulkan GPU-v3-v3-v3 - Model: squeezenet_ssd
ms < Lower Is Better
b . 7.14 |=====================================================================
c . 7.07 |====================================================================
NCNN 20230517
Target: Vulkan GPU-v3-v3-v3 - Model: regnety_400m
ms < Lower Is Better
b . 8.27 |=====================================================================
c . 7.98 |===================================================================
NCNN 20230517
Target: Vulkan GPU-v3-v3-v3 - Model: vision_transformer
ms < Lower Is Better
b . 31.71 |====================================================================
c . 31.66 |====================================================================
NCNN 20230517
Target: Vulkan GPU-v3-v3-v3 - Model: FastestDet
ms < Lower Is Better
b . 4.06 |=====================================================================
c . 3.69 |===============================================================