vulkan-benchmarks

AMD Ryzen 9 7950X 16-Core testing with a ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS) and NVIDIA GeForce RTX 4090 24GB 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 2308060-PTS-VULKANBE29
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NVIDIA GPU Compute 4 Tests
Vulkan Compute 4 Tests

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Identifier
Performance Per
Dollar
Date
Run
  Test
  Duration
a
August 01 2023
  3 Hours, 11 Minutes
b
August 01 2023
  1 Hour, 30 Minutes
c
August 01 2023
  1 Hour, 32 Minutes
d
August 01 2023
  3 Hours, 45 Minutes
e
August 01 2023
  3 Hours, 16 Minutes
f
August 02 2023
  1 Hour, 53 Minutes
g
August 02 2023
  2 Hours, 9 Minutes
h
August 02 2023
  47 Minutes
i
August 02 2023
  1 Hour, 50 Minutes
4080
August 02 2023
  2 Hours, 4 Minutes
4080 rep
August 02 2023
  2 Hours, 7 Minutes
4080 xxx
August 02 2023
  2 Hours, 8 Minutes
4080 zzz
August 02 2023
  2 Hours, 9 Minutes
3090
August 03 2023
  2 Hours, 44 Minutes
3090 rep
August 03 2023
  2 Hours, 54 Minutes
3070
August 03 2023
  4 Hours, 56 Minutes
RTX 3070 Ti
August 04 2023
  1 Day, 7 Hours, 27 Minutes
4090
August 06 2023
  2 Hours, 52 Minutes
4090 rep
August 06 2023
  2 Hours, 54 Minutes
nv 4090
August 06 2023
  2 Hours, 52 Minutes
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  3 Hours, 57 Minutes

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vulkan-benchmarks AMD Ryzen 9 7950X 16-Core testing with a ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS) and NVIDIA GeForce RTX 4090 24GB on Ubuntu 23.04 via the Phoronix Test Suite. ,,"a","b","c","d","e","f","g","h","i","4080","4080 rep","4080 xxx","4080 zzz","3090","3090 rep","3070","RTX 3070 Ti","4090","4090 rep","nv 4090" Processor,,AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads),AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads),AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads),AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads),AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads),AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads),AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads),AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads),AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads),AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads),AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads),AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads),AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads),AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads),AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads),AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads),AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads),AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads),AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads),AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads) Motherboard,,ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS),ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS),ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS),ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS),ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS),ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS),ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS),ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS),ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS),ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS),ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS),ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS),ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS),ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS),ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS),ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS),ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS),ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS),ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS),ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS) Chipset,,AMD Device 14d8,AMD Device 14d8,AMD Device 14d8,AMD Device 14d8,AMD Device 14d8,AMD Device 14d8,AMD Device 14d8,AMD Device 14d8,AMD Device 14d8,AMD Device 14d8,AMD Device 14d8,AMD Device 14d8,AMD Device 14d8,AMD Device 14d8,AMD Device 14d8,AMD Device 14d8,AMD Device 14d8,AMD Device 14d8,AMD Device 14d8,AMD Device 14d8 Memory,,32GB,32GB,32GB,32GB,32GB,32GB,32GB,32GB,32GB,32GB,32GB,32GB,32GB,32GB,32GB,32GB,32GB,32GB,32GB,32GB Disk,,Western Digital WD_BLACK SN850X 1000GB + 4001GB,Western Digital WD_BLACK SN850X 1000GB + 4001GB,Western Digital WD_BLACK SN850X 1000GB + 4001GB,Western Digital WD_BLACK SN850X 1000GB + 4001GB,Western Digital WD_BLACK SN850X 1000GB + 4001GB,Western Digital WD_BLACK SN850X 1000GB + 4001GB,Western Digital WD_BLACK SN850X 1000GB + 4001GB,Western Digital WD_BLACK SN850X 1000GB + 4001GB,Western Digital WD_BLACK SN850X 1000GB + 4001GB,Western Digital WD_BLACK SN850X 1000GB + 4001GB,Western Digital WD_BLACK SN850X 1000GB + 4001GB,Western Digital WD_BLACK SN850X 1000GB + 4001GB,Western Digital WD_BLACK SN850X 1000GB + 4001GB,Western Digital WD_BLACK SN850X 1000GB + 4001GB,Western Digital WD_BLACK SN850X 1000GB + 4001GB,Western Digital WD_BLACK SN850X 1000GB + 4001GB,Western Digital WD_BLACK SN850X 1000GB + 4001GB,Western Digital WD_BLACK SN850X 1000GB + 4001GB,Western Digital WD_BLACK SN850X 1000GB + 4001GB,Western Digital WD_BLACK SN850X 1000GB + 4001GB Graphics,,AMD Radeon RX 6700 XT (2855/1000MHz),AMD Radeon RX 6700 XT (2855/1000MHz),AMD Radeon RX 6700 XT (2855/1000MHz),MSI NVIDIA GeForce RTX 4060 8GB,MSI NVIDIA GeForce RTX 4060 8GB,eVGA NVIDIA GeForce RTX 3060 12GB,eVGA NVIDIA GeForce RTX 3060 12GB,eVGA NVIDIA GeForce RTX 3060 12GB,NVIDIA GeForce RTX 3060 Ti 8GB,NVIDIA GeForce RTX 4080 16GB,NVIDIA GeForce RTX 4080 16GB,NVIDIA GeForce RTX 4080 16GB,NVIDIA GeForce RTX 4080 16GB,NVIDIA GeForce RTX 3090 24GB,NVIDIA GeForce RTX 3090 24GB,NVIDIA GeForce RTX 3070 8GB,NVIDIA GeForce RTX 3070 Ti 8GB,NVIDIA GeForce RTX 4090 24GB,NVIDIA GeForce RTX 4090 24GB,NVIDIA GeForce RTX 4090 24GB Audio,,AMD Navi 21/23,AMD Navi 21/23,AMD Navi 21/23,NVIDIA Device 22be,NVIDIA Device 22be,NVIDIA GA106 HD Audio,NVIDIA GA106 HD Audio,NVIDIA GA106 HD Audio,NVIDIA GA104 HD Audio,NVIDIA Device 22bb,NVIDIA Device 22bb,NVIDIA Device 22bb,NVIDIA Device 22bb,NVIDIA GA102 HD Audio,NVIDIA GA102 HD Audio,NVIDIA GA104 HD Audio,NVIDIA GA104 HD Audio,NVIDIA AD102 HD Audio,NVIDIA AD102 HD Audio,NVIDIA AD102 HD Audio Monitor,,ASUS MG28U,ASUS MG28U,ASUS MG28U,ASUS MG28U,ASUS MG28U,ASUS MG28U,ASUS MG28U,ASUS MG28U,ASUS MG28U,ASUS MG28U,ASUS MG28U,ASUS MG28U,ASUS MG28U,ASUS MG28U,ASUS MG28U,ASUS MG28U,ASUS MG28U,ASUS MG28U,ASUS MG28U,ASUS MG28U Network,,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411,Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411 OS,,Ubuntu 23.04,Ubuntu 23.04,Ubuntu 23.04,Ubuntu 23.04,Ubuntu 23.04,Ubuntu 23.04,Ubuntu 23.04,Ubuntu 23.04,Ubuntu 23.04,Ubuntu 23.04,Ubuntu 23.04,Ubuntu 23.04,Ubuntu 23.04,Ubuntu 23.04,Ubuntu 23.04,Ubuntu 23.04,Ubuntu 23.04,Ubuntu 23.04,Ubuntu 23.04,Ubuntu 23.04 Kernel,,6.4.6-060406-generic (x86_64),6.4.6-060406-generic (x86_64),6.4.6-060406-generic (x86_64),6.4.6-060406-generic (x86_64),6.4.6-060406-generic (x86_64),6.4.6-060406-generic (x86_64),6.4.6-060406-generic (x86_64),6.4.6-060406-generic (x86_64),6.4.6-060406-generic (x86_64),6.4.6-060406-generic (x86_64),6.4.6-060406-generic (x86_64),6.4.6-060406-generic (x86_64),6.4.6-060406-generic (x86_64),6.4.6-060406-generic (x86_64),6.4.6-060406-generic (x86_64),6.4.6-060406-generic (x86_64),6.4.6-060406-generic (x86_64),6.4.6-060406-generic (x86_64),6.4.6-060406-generic (x86_64),6.4.6-060406-generic (x86_64) Desktop,,GNOME Shell 44.2,GNOME Shell 44.2,GNOME Shell 44.2,GNOME Shell 44.2,GNOME Shell 44.2,GNOME Shell 44.2,GNOME Shell 44.2,GNOME Shell 44.2,GNOME Shell 44.2,GNOME Shell 44.2,GNOME Shell 44.2,GNOME Shell 44.2,GNOME Shell 44.2,GNOME Shell 44.2,GNOME Shell 44.2,GNOME Shell 44.2,GNOME Shell 44.2,GNOME Shell 44.2,GNOME Shell 44.2,GNOME Shell 44.2 Display Server,,X Server 1.21.1.7 + Wayland,X Server 1.21.1.7 + Wayland,X Server 1.21.1.7 + Wayland,X Server 1.21.1.7,X Server 1.21.1.7,X Server 1.21.1.7,X Server 1.21.1.7,X Server 1.21.1.7,X Server 1.21.1.7,X Server 1.21.1.7,X Server 1.21.1.7,X Server 1.21.1.7,X Server 1.21.1.7,X Server 1.21.1.7,X Server 1.21.1.7,X Server 1.21.1.7,X Server 1.21.1.7,X Server 1.21.1.7,X Server 1.21.1.7,X Server 1.21.1.7 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),4.6 Mesa 23.3~git2307260600.87109c~oibaf~l (git-87109c3 2023-07-26 lunar-oibaf-ppa) (LLVM 15.0.7 DRM 3.52),4.6 Mesa 23.3~git2307260600.87109c~oibaf~l (git-87109c3 2023-07-26 lunar-oibaf-ppa) (LLVM 15.0.7 DRM 3.52),4.6.0,4.6.0,4.6.0,4.6.0,4.6.0,4.6.0,4.6.0,4.6.0,4.6.0,4.6.0,4.6.0,4.6.0,4.6.0,4.6.0,4.6.0,4.6.0,4.6.0 Compiler,,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0 File-System,,ext4,ext4,ext4,ext4,ext4,ext4,ext4,ext4,ext4,ext4,ext4,ext4,ext4,ext4,ext4,ext4,ext4,ext4,ext4,ext4 Screen Resolution,,3840x2160,3840x2160,3840x2160,3840x2160,3840x2160,3840x2160,3840x2160,3840x2160,2560x1440,3840x2160,3840x2160,3840x2160,3840x2160,3840x2160,3840x2160,2560x1440,2560x1440,3840x2160,3840x2160,3840x2160 Display Driver,,,,,NVIDIA 535.86.05,NVIDIA 535.86.05,NVIDIA 535.86.05,NVIDIA 535.86.05,NVIDIA 535.86.05,NVIDIA 535.86.05,NVIDIA 535.86.05,NVIDIA 535.86.05,NVIDIA 535.86.05,NVIDIA 535.86.05,NVIDIA 535.86.05,NVIDIA 535.86.05,NVIDIA 535.86.05,NVIDIA 535.86.05,NVIDIA 535.86.05,NVIDIA 535.86.05,NVIDIA 535.86.05 ,,"a","b","c","d","e","f","g","h","i","4080","4080 rep","4080 xxx","4080 zzz","3090","3090 rep","3070","RTX 3070 Ti","4090","4090 rep","nv 4090" "vkpeak - fp16-vec4 (GFLOPS)",HIB,23232.42,23390.44,23387.26,16864.47,16865.29,13440.97,13438.47,13490.24,,,,,,41149.1,41188.02,,,,, "vkpeak - int32-scalar (GIOPS)",HIB,2272.62,2269.25,2269.06,8520.02,8505.20,6827.92,6824.29,6800.6,,,,,,20909.02,20767.64,,,,, "vkpeak - int16-vec4 (GIOPS)",HIB,23123.77,23396.59,23385.44,7352.85,7336.25,5959.75,5956.38,5978.38,,,,,,16886.66,16881.47,,,,, "vkpeak - int32-vec4 (GIOPS)",HIB,2658.73,2640.08,2638.69,8465.82,8465.71,6800.17,6795.39,6772.98,,,,,,20820.09,20517.68,,,,, "vkpeak - int16-scalar (GIOPS)",HIB,13102.75,13070.81,13063.86,5676.02,5675.99,4480.59,4479.22,4495.98,,,,,,13710.88,13608.57,,,,, "vkpeak - fp16-scalar (GFLOPS)",HIB,13154.15,13145.19,13136.79,8412.33,8397.80,6812.52,6811.35,6838.32,,,,,,20845.09,20953.3,,,,, "vkpeak - fp32-vec4 (GFLOPS)",HIB,12730.08,12808.59,12822.01,11251.17,11231.72,9006.57,9003.12,9036.17,,,,,,27797.8,27807.58,,,,, "vkpeak - fp32-scalar (GFLOPS)",HIB,13190.09,12807.06,12860.56,8531.96,8515.58,6837.94,6832.74,6810.73,,,,,,21269.72,20925.3,,,,, "vkpeak - fp64-scalar (GFLOPS)",HIB,841.40,839.2,839.01,267.43,267.41,214.17,213.96,213.37,,,,,,653.13,653.63,,,,, "vkpeak - fp64-vec4 (GFLOPS)",HIB,841.80,836.55,836.16,267.74,267.25,214.23,213.95,210.96,,,,,,653.15,,,,,, "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: mobilenet-v3 (ms)",LIB,,,,,,,,,,,,,,3.16,,5.97,3.52,3.36,3.44,4.81 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: FastestDet (ms)",LIB,,,,,,,,,,,,,,4.08,4.1,4.48,4.25,2.82,3.91,4.01 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: vision_transformer (ms)",LIB,,,,,,,,,,,,,,32.16,32.13,69.48,38.32,38.82,38.69,38.58 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: regnety_400m (ms)",LIB,,,,,,,,,,,,,,8.2,8.19,18.24,9.10,10.05,8.45,8.37 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: squeezenet_ssd (ms)",LIB,,,,,,,,,,,,,,7.05,7.07,15.46,8.31,7.4,9.34,7.72 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: yolov4-tiny (ms)",LIB,,,,,,,,,,,,,,12.86,12.89,26.33,15.56,15.69,16.6,15.67 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: resnet50 (ms)",LIB,,,,,,,,,,,,,,10.03,10.04,23.54,12.52,12.98,11.24,13.46 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: alexnet (ms)",LIB,,,,,,,,,,,,,,4.3,4.3,10.69,5.41,4.94,5.16,6.54 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: resnet18 (ms)",LIB,,,,,,,,,,,,,,5.2,5.2,13.34,6.69,7.78,5.84,5.97 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: vgg16 (ms)",LIB,,,,,,,,,,,,,,23.5,23.47,51.28,28.53,27.31,29.35,29.4 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: googlenet (ms)",LIB,,,,,,,,,,,,,,7.83,7.82,18.66,9.58,8.91,10.18,8.85 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: blazeface (ms)",LIB,,,,,,,,,,,,,,1.39,1.38,3.57,1.51,1.45,1.38,2.91 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: efficientnet-b0 (ms)",LIB,,,,,,,,,,,,,,3.86,3.85,9.53,4.55,4.14,4.44,5.88 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: mnasnet (ms)",LIB,,,,,,,,,,,,,,2.97,2.98,8.15,3.25,3.19,3.28,3.1 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: shufflenet-v2 (ms)",LIB,,,,,,,,,,,,,,3.36,3.36,6.3,3.92,3.47,5.18,3.37 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3-v2-v2 - Model: mobilenet-v2 (ms)",LIB,,,,,,,,,,,,,,3.15,3.17,5.49,3.69,5.25,3.6,3.27 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: mobilenet (ms)",LIB,,,,,,,,,,,,,,8.01,8.05,18.54,9.98,8.46,8.83,10.15 "VkFFT - Test: FFT + iFFT C2C Bluestein benchmark in double precision (Benchmark Score)",HIB,4717,4695,4670,2346,2343,1814,1818,,2417,5579,5583,5587,5584,4282,4289,,,8039,8119,8132 "VkResample - Upscale: 2x - Precision: Double (ms)",LIB,,,,500.014,500.016,500.01,500.011,,500.006,288.201,288.166,288.039,288.028,371.699,371.422,24.745,24.805,172.883,173.043,172.887 "NCNN - Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3 (ms)",LIB,3.17,,3.2,3.17,3.18,3.14,,,4.87,,,,3.28,3.19,3.16,6.6,3.64,3.28,3.3,3.36 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: FastestDet (ms)",LIB,,,,,,,,,,4.19,4.17,3.75,4.61,3.83,4.07,6.71,4.32,4.45,4.11,2.64 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: vision_transformer (ms)",LIB,,,,,,,,,,35.6,33.93,33.9,35.36,31.94,31.97,70.29,38.27,38.62,39.03,38.46 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: regnety_400m (ms)",LIB,,,,,,,,,,8.67,8.35,8.25,8.37,8.33,8.07,17.61,9.05,9.87,10.69,10.03 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: squeezenet_ssd (ms)",LIB,,,,,,,,,,7.71,7.62,7.27,8.06,7.05,7.08,18.83,8.65,9.81,9.46,7.02 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: yolov4-tiny (ms)",LIB,,,,,,,,,,13.93,13.73,13.52,15.26,12.97,12.9,28.73,15.00,15.95,15.4,15.55 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: resnet50 (ms)",LIB,,,,,,,,,,11.48,11.07,11.22,12.5,10.07,9.98,23.44,12.42,12.4,11.51,13.13 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: alexnet (ms)",LIB,,,,,,,,,,4.98,4.64,4.71,4.7,4.32,4.3,11.89,5.34,4.67,5.25,4.69 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: resnet18 (ms)",LIB,,,,,,,,,,5.92,5.67,5.65,5.74,5.21,5.2,11.3,6.40,7.52,5.9,7.38 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: vgg16 (ms)",LIB,,,,,,,,,,25.67,25.56,25.33,26.09,23.51,23.38,49.7,28.53,27.44,29.17,28.14 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: googlenet (ms)",LIB,,,,,,,,,,8.79,8.42,8.26,8.55,7.84,7.86,16.97,9.90,9.05,10.39,8.35 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: blazeface (ms)",LIB,,,,,,,,,,1.44,1.42,1.31,1.41,1.38,1.37,2.99,1.34,1.42,1.41,1.26 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: efficientnet-b0 (ms)",LIB,,,,,,,,,,4.04,4.01,3.97,4.05,3.88,3.85,9.81,4.37,4.15,4.41,4.1 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: mnasnet (ms)",LIB,,,,,,,,,,3.1,3.06,2.98,3.08,2.94,2.97,6.06,3.10,4.93,4.99,3.07 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: shufflenet-v2 (ms)",LIB,,,,,,,,,,3.48,3.44,3.34,3.44,3.32,3.34,5.59,3.89,3.52,3.48,3.5 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: mobilenet-v3 (ms)",LIB,,,,,,,,,,3.26,3.31,3.05,3.26,3.13,3.18,5.99,3.44,3.62,3.34,3.17 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3-v3-v3-v3-v2-v2 - Model: mobilenet-v2 (ms)",LIB,,,,,,,,,,3.29,3.27,3.14,3.28,3.12,3.17,5.46,3.66,3.48,3.36,3.42 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: mobilenet (ms)",LIB,,,,,,,,,,8.43,8.38,8.31,9.19,8.03,8.05,17.09,9.52,9.16,9.02,8.93 "VkFFT - Test: FFT + iFFT C2C 1D batched in double precision (Benchmark Score)",HIB,20816,20822,20847,12143,12168,10561,10548,10572,14780,34974,35038,35071,35058,30945,31122,,,55214,55383,54950 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3-v3-v3 - Model: mobilenet-v3 (ms)",LIB,,,,,,,3.16,,3.26,,3.24,3.26,3.24,3.16,,6.56,3.62,3.3,3.33,3.26 "VkFFT - Test: FFT + iFFT C2C Bluestein in single precision (Benchmark Score)",HIB,11340,11273,11311,10719,10560,7571,7574,7622,10061,17121,17287,17343,17185,14406,14449,,,20373,20404,20601 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3 - Model: yolov4-tiny (ms)",LIB,,,,,,,13.14,,13.77,13.86,13.55,13.62,13.61,13.1,12.86,29.8,15.21,15.55,15.45,17.3 "NCNN - Target: CPU-v3-v3 - Model: mobilenet-v3 (ms)",LIB,3.18,,3.17,3.17,,,3.14,,3.26,3.24,3.26,3.27,3.24,3.18,3.19,7.52,3.61,3.53,3.31,3.47 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3 - Model: FastestDet (ms)",LIB,,,,,,,3.92,,3.83,4.28,4.14,4.17,4.2,4.03,4.08,6.93,4.41,4.03,3.96,2.81 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3 - Model: vision_transformer (ms)",LIB,,,,,,,33.32,,38.01,34.91,34.1,34.23,34.1,33.22,32.09,71.08,37.88,38.38,38.17,39.18 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3 - Model: regnety_400m (ms)",LIB,,,,,,,8.38,,8.46,8.61,8.24,8.52,8.49,7.99,8.34,17.88,9.19,8.1,8.64,10.09 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3 - Model: squeezenet_ssd (ms)",LIB,,,,,,,7.14,,7.21,7.66,7.55,7.67,7.62,7.04,7.09,15.4,8.28,7.57,9.16,9.21 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3 - Model: resnet50 (ms)",LIB,,,,,,,10.33,,13.1,11.4,10.8,10.91,10.91,10.38,10.04,23.59,12.73,11.53,12.17,13.63 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3 - Model: alexnet (ms)",LIB,,,,,,,4.35,,5.1,4.61,4.72,4.67,4.68,4.31,4.31,10.08,5.53,4.72,5.33,5.14 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3 - Model: resnet18 (ms)",LIB,,,,,,,5.28,,5.88,5.61,5.61,5.67,5.6,5.19,5.22,12.14,6.57,5.78,6.05,8.16 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3 - Model: vgg16 (ms)",LIB,,,,,,,24.04,,27.43,25.48,25.05,25.4,25.16,23.55,23.52,55.48,28.63,29.05,29.12,27.89 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3 - Model: googlenet (ms)",LIB,,,,,,,7.96,,10.47,8.4,8.49,8.43,8.42,7.86,7.89,18.6,9.84,10.87,10.38,8.61 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3 - Model: blazeface (ms)",LIB,,,,,,,1.38,,1.41,1.43,1.41,1.42,1.42,1.36,1.39,1.77,1.49,1.16,1.46,1.18 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3 - Model: efficientnet-b0 (ms)",LIB,,,,,,,3.84,,4.19,4.06,3.98,4.02,4.01,3.83,3.87,8.41,4.60,4.24,4.04,4.12 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3 - Model: mnasnet (ms)",LIB,,,,,,,2.97,,3.07,3.06,3.03,3.05,3.08,2.96,2.99,4.59,3.34,3.1,3.13,3.16 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3 - Model: shufflenet-v2 (ms)",LIB,,,,,,,3.34,,3.43,3.46,3.39,3.43,3.43,3.33,3.37,8,3.75,5.09,5.27,3.51 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3-v2-v2 - Model: mobilenet-v2 (ms)",LIB,,,,,,,3.17,,3.29,3.28,3.27,3.27,3.28,3.15,3.19,8.35,3.66,3.32,3.34,5.1 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3-v3 - Model: mobilenet (ms)",LIB,,,,,,,8.5,,10.02,8.84,8.4,8.46,8.46,8.11,8.04,18.39,9.62,8.96,8.37,9.41 "NCNN - Target: Vulkan GPU - Model: FastestDet (ms)",LIB,4.1,4.07,4.09,4.11,4.08,4.24,4.07,,5.14,4.2,4.21,4.2,4.79,4.11,4.08,8.41,4.26,4.39,4.59,3.93 "NCNN - Target: Vulkan GPU - Model: vision_transformer (ms)",LIB,31.88,31.85,31.79,32.12,31.93,32.92,32.42,,36.42,35.56,35.07,34.19,34.32,31.94,31.91,70.76,38.03,38.76,37.59,39.04 "NCNN - Target: Vulkan GPU - Model: regnety_400m (ms)",LIB,8.16,8.21,8,8.17,8.10,8.34,8.36,,9.88,8.39,8.56,8.56,8.58,8.38,8.02,16.22,9.07,8.64,8.48,9.81 "NCNN - Target: Vulkan GPU - Model: squeezenet_ssd (ms)",LIB,7.09,7.07,7.06,7.08,7.05,7.08,7.1,,7.46,7.58,7.64,7.62,7.63,7.16,7.06,15.82,8.47,7.83,8.22,9.11 "NCNN - Target: Vulkan GPU - Model: yolov4-tiny (ms)",LIB,12.84,12.87,12.81,12.85,12.87,13.17,13.64,,15.16,13.79,13.67,13.65,13.8,12.88,12.83,28.59,15.54,13.97,15.72,15.26 "NCNN - Target: Vulkan GPU - Model: resnet50 (ms)",LIB,10.01,10,10,10.10,10.10,10.26,10.34,,12.96,10.81,10.84,10.94,11.07,10.1,10.06,23.48,12.60,14.13,13.08,12.45 "NCNN - Target: Vulkan GPU - Model: alexnet (ms)",LIB,4.31,4.33,4.33,4.31,4.31,4.64,4.87,,6.53,4.62,4.65,4.68,4.68,4.35,4.31,10.88,5.25,4.64,6.79,5.2 "NCNN - Target: Vulkan GPU - Model: resnet18 (ms)",LIB,5.28,5.23,5.21,5.23,5.22,5.48,6.22,,5.82,5.67,5.61,5.62,5.59,5.27,5.2,12.68,6.28,5.69,6.01,7.44 "NCNN - Target: Vulkan GPU - Model: vgg16 (ms)",LIB,23.51,23.56,23.54,23.56,23.60,24.55,24.2,,27.83,25,25.04,25.01,25.82,23.55,23.48,48.29,29.06,28.82,27.04,29.29 "NCNN - Target: Vulkan GPU - Model: googlenet (ms)",LIB,7.90,7.85,7.8,7.85,7.85,8.15,8.96,,8.75,8.42,8.4,8.42,8.41,7.87,7.82,19.49,9.87,10.62,10.65,8.7 "NCNN - Target: Vulkan GPU - Model: blazeface (ms)",LIB,1.38,1.37,1.37,1.38,1.38,1.38,1.41,,1.4,1.41,1.41,1.42,1.42,1.39,1.37,3.98,1.60,1.39,1.4,1.4 "NCNN - Target: Vulkan GPU - Model: efficientnet-b0 (ms)",LIB,3.86,3.82,3.83,3.87,3.84,3.86,3.86,,5.88,4.01,4.05,4.04,4.04,3.88,3.86,8.99,4.53,4.34,4.09,4.1 "NCNN - Target: Vulkan GPU - Model: mnasnet (ms)",LIB,2.98,2.95,2.96,2.97,2.96,2.97,2.98,,3.2,3.07,3.08,3.07,3.06,2.99,2.97,5.09,3.40,3.18,3.15,4.7 "NCNN - Target: Vulkan GPU - Model: shufflenet-v2 (ms)",LIB,3.35,3.33,3.32,3.35,3.33,3.4,3.35,,3.49,3.43,3.44,3.5,3.46,3.39,3.36,7.07,3.98,3.45,3.49,3.51 "NCNN - Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2 (ms)",LIB,3.17,3.14,3.13,3.16,3.14,3.13,3.18,,3.29,3.26,3.29,3.26,3.29,3.18,3.17,7.81,3.56,3.3,3.31,3.43 "NCNN - Target: Vulkan GPU - Model: mobilenet (ms)",LIB,8.05,8.04,8.03,8.02,8.04,8.27,8.17,,10.4,8.44,8.57,8.37,8.47,8.07,8.03,21.11,9.35,10.55,10.23,8.45 "NCNN - Target: CPU - Model: FastestDet (ms)",LIB,3.62,4.05,4.11,4.08,,4.22,2.57,,2.66,4.42,4.34,4.17,4.16,4.21,4.08,8.65,3.94,5.48,5.27,4.51 "NCNN - Target: CPU - Model: blazeface (ms)",LIB,1.38,1.38,1.39,1.38,,1.37,1.38,,1.4,1.4,1.42,1.42,1.4,1.38,1.38,2.98,1.60,1.27,1.45,1.33 "NCNN - Target: Vulkan GPU-v3-v3-v3-v3-v3 - Model: mobilenet-v3 (ms)",LIB,,3.16,3.17,,,3.15,3.15,,3.26,3.27,3.27,3.33,3.2,,3.15,8.06,3.65,3.12,4.9,2.61 "NCNN - Target: CPU-v3-v3-v3-v3-v3 - Model: mobilenet-v3 (ms)",LIB,,3.16,3.16,,,3.15,3.16,,3.29,3.28,,3.31,3.27,3.15,3.15,5.38,3.76,3.25,3.53,3.35 "NCNN - Target: CPU - Model: vision_transformer (ms)",LIB,32.49,31.95,31.77,32.43,,33.56,32.73,,37.8,35.07,35.28,34.27,34.1,33.01,31.8,75.34,37.91,38.25,37.05,38.9 "NCNN - Target: CPU - Model: regnety_400m (ms)",LIB,8.18,8.18,8.27,8.23,,8.08,8.3,,9.94,8.24,8.67,8.45,8.37,8.25,8.24,18,8.83,8.13,8.78,10.17 "NCNN - Target: CPU - Model: squeezenet_ssd (ms)",LIB,7.07,7.06,7.1,7.09,,7.23,7.13,,8.96,7.73,7.86,7.62,7.55,7.52,7.12,13.2,8.13,7.86,7.31,9.11 "NCNN - Target: CPU - Model: yolov4-tiny (ms)",LIB,12.90,12.74,12.81,12.95,,13.32,17.23,,14.65,13.85,14.03,13.6,13.63,14.26,12.77,27.66,15.20,13.68,15.38,15.4 "NCNN - Target: CPU - Model: resnet50 (ms)",LIB,10.20,10.01,10.11,10.00,,11.05,10.72,,12.09,11.16,11.76,10.82,11.1,10.3,9.95,21.5,12.73,14.1,12.73,11.41 "NCNN - Target: CPU - Model: alexnet (ms)",LIB,4.41,4.32,4.31,4.30,,4.36,4.32,,5.3,4.75,4.67,4.68,4.69,4.3,4.31,9.62,5.49,5.14,5.14,5.18 "NCNN - Target: CPU - Model: resnet18 (ms)",LIB,5.29,5.2,5.24,5.23,,5.69,5.55,,5.6,5.69,5.68,5.56,5.63,5.21,5.29,14.03,6.08,6,6.77,7.82 "NCNN - Target: CPU - Model: vgg16 (ms)",LIB,23.75,23.49,23.45,23.51,,24.19,23.78,,30.96,25.37,26.11,25.03,25.4,23.43,23.43,56.64,28.36,27.75,28.19,29.54 "NCNN - Target: CPU - Model: googlenet (ms)",LIB,7.94,7.82,7.93,7.85,,7.92,7.98,,10.3,8.42,8.52,8.38,8.4,7.86,7.9,18.25,9.69,10.27,9.53,8.93 "NCNN - Target: CPU - Model: efficientnet-b0 (ms)",LIB,3.90,3.85,3.88,3.85,,3.87,3.91,,4.05,3.99,4.09,4.04,3.99,3.87,3.86,9.23,4.72,4.23,4.03,4.37 "NCNN - Target: CPU - Model: mnasnet (ms)",LIB,2.97,2.97,2.99,2.98,,2.97,3,,2.74,3.05,3.06,3.06,3.04,2.99,2.97,6.88,3.26,3.12,3.18,4.77 "NCNN - Target: CPU - Model: shufflenet-v2 (ms)",LIB,3.34,3.34,3.35,3.35,,3.55,3.59,,5.03,3.41,3.43,3.45,3.42,3.34,3.35,6.82,3.77,3.55,3.47,3.45 "NCNN - Target: CPU-v2-v2 - Model: mobilenet-v2 (ms)",LIB,3.16,3.16,3.18,3.17,,3.15,3.16,,3.52,3.28,3.28,3.28,3.25,3.17,3.17,9.67,3.76,3.3,3.3,3.6 "NCNN - Target: CPU - Model: mobilenet (ms)",LIB,8.05,7.97,8.02,8.10,,8.45,22.74,,8.37,8.73,8.41,8.37,8.38,8.6,8.01,17.81,9.43,10.08,8.43,8.15 "NCNN - Target: CPU-v3-v3-v3 - Model: FastestDet (ms)",LIB,,4.07,4.08,,,3.85,3.97,,5.69,4.2,4.18,4.19,4.04,4.04,4.11,9.18,4.33,2.93,4.16,4.06 "NCNN - Target: CPU-v3-v3-v3 - Model: vision_transformer (ms)",LIB,,31.65,31.78,,,33.47,33.39,,36.55,34.2,34.27,34.37,34.47,31.89,31.93,81.77,37.86,38.79,39.12,38.99 "NCNN - Target: CPU-v3-v3-v3 - Model: regnety_400m (ms)",LIB,,8.05,8.14,,,8.34,8.07,,8.21,8.33,8.57,8.75,8.47,7.95,8.09,19.66,9.02,8.13,17.15,9.55 "NCNN - Target: CPU-v3-v3-v3 - Model: squeezenet_ssd (ms)",LIB,,7.03,7.04,,,6.97,7.26,,8.16,7.64,7.59,7.64,7.35,7.04,7.09,17.75,8.39,9.32,9.3,9.37 "NCNN - Target: CPU-v3-v3-v3 - Model: yolov4-tiny (ms)",LIB,,12.98,12.89,,,13.07,13.08,,15.11,13.81,13.55,13.69,13.83,12.87,12.82,29.34,15.42,15.3,15.34,15.62 "NCNN - Target: CPU-v3-v3-v3 - Model: resnet50 (ms)",LIB,,10.01,10.33,,,11.05,11.25,,14.05,11.11,10.79,10.91,11.21,10.05,10.07,24.07,12.11,11.39,13.82,13.68 "NCNN - Target: CPU-v3-v3-v3 - Model: alexnet (ms)",LIB,,4.29,4.28,,,4.83,4.71,,5.01,4.66,4.65,4.65,4.67,4.31,4.3,11,5.55,4.94,5.27,4.67 "NCNN - Target: CPU-v3-v3-v3 - Model: resnet18 (ms)",LIB,,5.21,5.26,,,6.13,5.48,,5.86,5.7,5.63,5.66,5.71,5.19,5.2,11.14,6.18,5.81,7.75,7.61 "NCNN - Target: CPU-v3-v3-v3 - Model: vgg16 (ms)",LIB,,23.5,23.99,,,24.45,24.92,,29.12,25.1,24.91,25,25.45,23.5,23.54,49.75,28.40,28.55,27.25,27.04 "NCNN - Target: CPU-v3-v3-v3 - Model: googlenet (ms)",LIB,,7.84,7.88,,,8.07,9.15,,10.17,8.45,8.52,8.5,8.55,7.83,7.85,17,9.65,9.97,9.29,9.02 "NCNN - Target: CPU-v3-v3-v3 - Model: blazeface (ms)",LIB,,1.37,1.38,,,1.43,1.37,,1.28,1.44,1.42,1.42,1.41,1.36,1.37,3.03,1.79,1.17,1.34,1.16 "NCNN - Target: CPU-v3-v3-v3 - Model: efficientnet-b0 (ms)",LIB,,3.82,3.89,,,4.04,4.14,,4.68,4.02,4.02,4.06,4.03,3.83,3.85,9.01,4.78,4.09,4.34,4.04 "NCNN - Target: CPU-v3-v3-v3 - Model: mnasnet (ms)",LIB,,2.97,2.97,,,3.12,3.05,,3.39,3.08,3.09,3.07,3.06,2.95,2.96,6.87,3.11,3.19,3.23,4.61 "NCNN - Target: CPU-v3-v3-v3 - Model: shufflenet-v2 (ms)",LIB,,3.33,3.34,,,3.4,3.38,,3.52,3.46,3.43,3.47,3.43,3.32,3.33,8.13,4.09,5.18,3.59,3.46 "NCNN - Target: CPU-v3-v3-v3-v2-v2 - Model: mobilenet-v2 (ms)",LIB,,3.15,3.14,,,3.16,3.15,,3.3,3.31,3.27,3.3,3.28,3.14,3.17,9.19,3.41,3.46,3.45,3.39 "NCNN - Target: CPU-v3-v3-v3 - Model: mobilenet (ms)",LIB,,8.01,8,,,8.56,8.98,,10.08,8.43,8.48,8.44,8.4,8.06,8.03,17.82,9.62,8.96,8.74,8.91 "NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: regnety_400m (ms)",LIB,,8.27,7.98,,,8.5,7.99,,7.99,8.45,8.44,8.58,8.1,8.01,8.25,17.23,8.89,9.6,10.34,7.73 "NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: FastestDet (ms)",LIB,,4.06,3.69,,,4.2,3.97,,4.43,4.2,4.09,4.31,4.12,4.04,4.1,8.63,4.26,3.94,4.16,5.92 "NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: vision_transformer (ms)",LIB,,31.71,31.66,,,33.36,32.38,,38.33,34.13,34.29,35.4,34.05,31.86,32.11,73.51,38.29,39.01,38.73,38.58 "NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: squeezenet_ssd (ms)",LIB,,7.14,7.07,,,7.09,7.19,,8.33,7.66,7.63,7.7,7.51,7.04,7.08,16.15,8.29,7.93,7.81,7.72 "NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: yolov4-tiny (ms)",LIB,,12.77,12.86,,,14.34,12.89,,15.43,13.79,13.68,13.95,13.62,12.88,12.84,29.49,15.44,15.44,16.39,16.61 "NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: resnet50 (ms)",LIB,,9.87,10.03,,,10.25,10.18,,11.15,10.95,10.84,11.5,11.09,9.97,10.01,23.11,12.35,14.58,13.57,13.13 "NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: alexnet (ms)",LIB,,4.42,4.3,,,4.35,4.35,,4.99,4.69,4.69,5.21,4.65,4.3,4.3,9.86,5.67,6.11,6.58,6.11 "NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: resnet18 (ms)",LIB,,5.42,5.23,,,5.3,5.3,,5.85,5.65,5.69,5.89,5.59,5.23,5.24,13.38,6.23,5.97,5.81,5.84 "NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: vgg16 (ms)",LIB,,23.42,23.54,,,24.12,23.82,,29.07,25.04,25.04,26.08,25.26,23.5,23.43,55.42,28.40,28.21,27.59,27.77 "NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: googlenet (ms)",LIB,,7.97,7.83,,,7.94,7.94,,10.19,8.49,8.58,8.99,8.37,7.82,7.85,20.72,9.86,8.87,8.9,10.01 "NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: blazeface (ms)",LIB,,1.37,1.36,,,1.37,1.37,,1.25,1.42,1.45,1.42,1.39,1.36,1.38,3.18,1.71,1.33,1.41,1.07 "NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: efficientnet-b0 (ms)",LIB,,3.85,3.82,,,3.85,3.85,,4.21,4.05,4.04,4.22,3.95,3.85,3.85,7.81,4.73,4.18,6.28,5.26 "NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: mnasnet (ms)",LIB,,2.96,2.96,,,2.96,2.95,,2.99,3.09,3.07,3.13,3.01,2.97,2.97,6.02,3.37,3,3.1,2.54 "NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: shufflenet-v2 (ms)",LIB,,3.33,3.33,,,3.33,3.33,,3.36,3.44,3.44,3.51,3.37,3.34,3.36,4.89,3.95,3.34,3.4,3.17 "NCNN - Target: Vulkan GPU-v3-v3-v3-v2-v2 - Model: mobilenet-v2 (ms)",LIB,,3.15,3.15,,,3.16,3.14,,3.28,3.29,3.3,3.4,3.23,3.16,3.17,7.24,3.66,4.99,3.31,4.45 "NCNN - Target: Vulkan GPU-v3-v3-v3 - Model: mobilenet (ms)",LIB,,8,7.95,,,8.65,8.04,,9.05,8.43,8.46,8.88,8.38,8,8.01,16.34,9.62,8.81,9.54,10.54 "VkFFT - Test: FFT + iFFT C2C 1D batched in single precision (Benchmark Score)",HIB,47887,47948,47971,42645,42651,56476,56455,56431,69738,104556,104491,104528,104543,141357,141437,,,153896,153939,152170 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: FastestDet (ms)",LIB,,,,,,,,,,,,,,,4.07,7.23,4.14,4.62,4.59,5.86 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: vision_transformer (ms)",LIB,,,,,,,,,,,,,,,31.94,70.53,38.50,39.35,38.65,37.13 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: regnety_400m (ms)",LIB,,,,,,,,,,,,,,,8.06,17.02,9.14,10.11,8.7,8.34 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: squeezenet_ssd (ms)",LIB,,,,,,,,,,,,,,,7.07,15.32,7.45,7.43,9.44,8.26 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: yolov4-tiny (ms)",LIB,,,,,,,,,,,,,,,12.92,29.38,14.64,16.05,15.41,16.3 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: resnet50 (ms)",LIB,,,,,,,,,,,,,,,10.27,22.15,13.15,13,10.96,13.25 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: alexnet (ms)",LIB,,,,,,,,,,,,,,,4.31,11.43,6.25,5.14,5.34,6.32 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: resnet18 (ms)",LIB,,,,,,,,,,,,,,,5.27,12.13,5.94,6.96,5.87,5.58 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: vgg16 (ms)",LIB,,,,,,,,,,,,,,,23.72,53.48,27.86,27.32,29.85,27.25 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: googlenet (ms)",LIB,,,,,,,,,,,,,,,7.86,18.8,9.97,8.55,10.47,10.14 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: blazeface (ms)",LIB,,,,,,,,,,,,,,,1.38,2.69,1.40,1.35,1.42,1.4 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: efficientnet-b0 (ms)",LIB,,,,,,,,,,,,,,,3.84,6.63,4.17,4.63,4.1,5.82 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: mnasnet (ms)",LIB,,,,,,,,,,,,,,,2.96,8.55,3.12,3.23,3.12,3.1 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: shufflenet-v2 (ms)",LIB,,,,,,,,,,,,,,,3.32,5.89,3.48,3.56,5.23,3.43 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: mobilenet-v3 (ms)",LIB,,,,,,,,,,,,,,,3.19,7.34,3.24,3.36,3.35,4.96 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v2-v2 - Model: mobilenet-v2 (ms)",LIB,,,,,,,,,,,,,,,3.15,5.92,3.83,4.75,3.38,3.29 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3-v3 - Model: mobilenet (ms)",LIB,,,,,,,,,,,,,,,8.03,17.06,10.02,10.56,8.22,10.64 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v3-v3 - Model: mobilenet-v3 (ms)",LIB,,,,,,,,,,,3.28,3.08,3.06,,3.17,6.43,3.70,3.33,3.3,4.97 "VkFFT - Test: FFT + iFFT C2C 1D batched in single precision, no reshuffling (Benchmark Score)",HIB,50504,50643,50596,43365,43365,57110,57094,,71163,106210,106205,106099,105926,143969,143956,,,152656,155936,155148 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3 - Model: FastestDet (ms)",LIB,,,,,,,,,,,4.2,3.8,3.82,4.1,4.07,7.12,4.18,2.85,3.12,3.93 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3 - Model: vision_transformer (ms)",LIB,,,,,,,,,,,34.22,34.14,34.47,32.1,31.85,65.41,38.04,38.76,38.79,38.95 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3 - Model: regnety_400m (ms)",LIB,,,,,,,,,,,8.72,8.38,8.34,8.22,8.03,18.25,8.42,10.09,10.23,8.25 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3 - Model: squeezenet_ssd (ms)",LIB,,,,,,,,,,,7.67,7.27,7.25,7.12,7.09,14.27,7.57,9.51,9.38,7.48 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3 - Model: yolov4-tiny (ms)",LIB,,,,,,,,,,,13.71,13.63,13.42,12.82,12.81,28.41,14.57,15.85,13.88,17.67 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3 - Model: resnet50 (ms)",LIB,,,,,,,,,,,10.86,11.26,11.1,10.03,10.06,22.19,12.81,11.72,12.47,13.29 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3 - Model: alexnet (ms)",LIB,,,,,,,,,,,4.68,4.69,4.66,4.33,4.31,10.59,6.17,4.99,5.45,6.62 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3 - Model: resnet18 (ms)",LIB,,,,,,,,,,,5.64,5.78,5.77,5.2,5.3,12.64,6.22,7.74,8.14,6.07 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3 - Model: vgg16 (ms)",LIB,,,,,,,,,,,25.01,25.44,25.26,23.58,23.4,50.32,27.98,30.16,30.74,27.61 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3 - Model: googlenet (ms)",LIB,,,,,,,,,,,8.52,8.32,8.29,7.9,7.91,19.2,9.68,8.38,8.97,10.75 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3 - Model: blazeface (ms)",LIB,,,,,,,,,,,1.43,1.32,1.31,1.39,1.38,2.53,2.48,1.3,1.42,1.42 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3 - Model: efficientnet-b0 (ms)",LIB,,,,,,,,,,,4.07,4.01,3.95,3.88,3.85,9.19,4.74,4.47,4.35,5.94 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3 - Model: mnasnet (ms)",LIB,,,,,,,,,,,3.09,3,2.96,2.98,2.97,6.07,3.24,5.19,5.11,3.12 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3 - Model: shufflenet-v2 (ms)",LIB,,,,,,,,,,,3.47,3.4,3.36,3.36,3.33,7.81,4.02,3.48,3.42,3.32 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3-v2-v2 - Model: mobilenet-v2 (ms)",LIB,,,,,,,,,,,3.3,3.2,3.16,3.16,3.16,7.22,3.91,3.36,3.44,3.29 "NCNN - Target: CPU-v3-v3-v3-v3-v3-v3 - Model: mobilenet (ms)",LIB,,,,,,,,,,,8.45,8.34,8.25,8.07,8.06,16.52,10.03,9.04,10.61,12.12 "VkFFT - Test: FFT + iFFT C2C 1D batched in half precision (Benchmark Score)",HIB,91597,91812,91744,85181,85191,104146,104171,104298,132270,211076,211058,210713,210991,255207,265171,,,290342,287651,292768 "VkFFT - Test: FFT + iFFT C2C multidimensional in single precision (Benchmark Score)",HIB,33001,32751,32812,36328,37090,26238,26541,,34686,65869,70068,67887,70040,51005,54814,,,81406,80999,82875 "VkFFT - Test: FFT + iFFT R2C / C2R (Benchmark Score)",HIB,42105,42163,43021,35399,35304,26593,26638,26524,33727,66473,68279,69068,67689,55347,54432,,,84351,81329,84887 "VkResample - Upscale: 2x - Precision: Single (ms)",LIB,11.686,11.69,11.688,32.855,32.850,26.738,26.769,,20.93,13.136,13.136,13.137,13.126,10.399,10.428,22.064,27.183,9.284,8.962,8.967