AMD Ryzen Threadripper 3960X 24-Core testing with a MSI Creator TRX40 (MS-7C59) v1.0 (1.12N1 BIOS) and Sapphire AMD Radeon RX 5500/5500M / Pro 5500M 4GB 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 2009286-PTS-TR3960XW65
TR 3960X WK
AMD Ryzen Threadripper 3960X 24-Core testing with a MSI Creator TRX40 (MS-7C59) v1.0 (1.12N1 BIOS) and Sapphire AMD Radeon RX 5500/5500M / Pro 5500M 4GB on Ubuntu 20.04 via the Phoronix Test Suite.
1:
Processor: AMD Ryzen Threadripper 3960X 24-Core @ 3.80GHz (24 Cores / 48 Threads), Motherboard: MSI Creator TRX40 (MS-7C59) v1.0 (1.12N1 BIOS), Chipset: AMD Starship/Matisse, Memory: 32GB, Disk: 1000GB Sabrent Rocket 4.0 1TB, Graphics: Sapphire AMD Radeon RX 5500/5500M / Pro 5500M 4GB (1900/875MHz), Audio: AMD Navi 10 HDMI Audio, Monitor: ASUS MG28U, Network: Aquantia AQC107 NBase-T/IEEE + Intel I211 + Intel Wi-Fi 6 AX200
OS: Ubuntu 20.04, Kernel: 5.9.0-rc5-14sep-patch (x86_64) 20200914, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 4.6 Mesa 20.0.8 (LLVM 10.0.0), Vulkan: 1.2.128, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 3840x2160
2:
Processor: AMD Ryzen Threadripper 3960X 24-Core @ 3.80GHz (24 Cores / 48 Threads), Motherboard: MSI Creator TRX40 (MS-7C59) v1.0 (1.12N1 BIOS), Chipset: AMD Starship/Matisse, Memory: 32GB, Disk: 1000GB Sabrent Rocket 4.0 1TB, Graphics: Sapphire AMD Radeon RX 5500/5500M / Pro 5500M 4GB (1900/875MHz), Audio: AMD Navi 10 HDMI Audio, Monitor: ASUS MG28U, Network: Aquantia AQC107 NBase-T/IEEE + Intel I211 + Intel Wi-Fi 6 AX200
OS: Ubuntu 20.04, Kernel: 5.9.0-rc5-14sep-patch (x86_64) 20200914, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 4.6 Mesa 20.0.8 (LLVM 10.0.0), Vulkan: 1.2.128, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 3840x2160
3:
Processor: AMD Ryzen Threadripper 3960X 24-Core @ 3.80GHz (24 Cores / 48 Threads), Motherboard: MSI Creator TRX40 (MS-7C59) v1.0 (1.12N1 BIOS), Chipset: AMD Starship/Matisse, Memory: 32GB, Disk: 1000GB Sabrent Rocket 4.0 1TB, Graphics: Sapphire AMD Radeon RX 5500/5500M / Pro 5500M 4GB (1900/875MHz), Audio: AMD Navi 10 HDMI Audio, Monitor: ASUS MG28U, Network: Aquantia AQC107 NBase-T/IEEE + Intel I211 + Intel Wi-Fi 6 AX200
OS: Ubuntu 20.04, Kernel: 5.9.0-rc5-14sep-patch (x86_64) 20200914, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 4.6 Mesa 20.0.8 (LLVM 10.0.0), Vulkan: 1.2.128, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 3840x2160
Hierarchical INTegration 1.0
Test: FLOAT
QUIPs > Higher Is Better
1 . 387229070.98 |=============================================================
2 . 387185459.43 |=============================================================
3 . 388597973.07 |=============================================================
Timed HMMer Search 3.3.1
Pfam Database Search
Seconds < Lower Is Better
1 . 131.08 |===================================================================
2 . 131.43 |===================================================================
3 . 131.51 |===================================================================
Timed MAFFT Alignment 7.471
Multiple Sequence Alignment - LSU RNA
Seconds < Lower Is Better
1 . 8.119 |===================================================================
2 . 8.243 |====================================================================
3 . 8.187 |====================================================================
Dolfyn 0.527
Computational Fluid Dynamics
Seconds < Lower Is Better
1 . 15.82 |====================================================================
2 . 15.86 |====================================================================
3 . 15.71 |===================================================================
Caffe 2020-02-13
Model: AlexNet - Acceleration: CPU - Iterations: 100
Milli-Seconds < Lower Is Better
1 . 63797 |====================================================================
2 . 63525 |====================================================================
3 . 63700 |====================================================================
Caffe 2020-02-13
Model: AlexNet - Acceleration: CPU - Iterations: 200
Milli-Seconds < Lower Is Better
1 . 127209 |===================================================================
2 . 127488 |===================================================================
3 . 127527 |===================================================================
Caffe 2020-02-13
Model: AlexNet - Acceleration: CPU - Iterations: 1000
Milli-Seconds < Lower Is Better
1 . 634925 |===================================================================
2 . 636843 |===================================================================
3 . 638848 |===================================================================
Caffe 2020-02-13
Model: GoogleNet - Acceleration: CPU - Iterations: 100
Milli-Seconds < Lower Is Better
1 . 158702 |===================================================================
2 . 158891 |===================================================================
3 . 159254 |===================================================================
Caffe 2020-02-13
Model: GoogleNet - Acceleration: CPU - Iterations: 200
Milli-Seconds < Lower Is Better
1 . 318121 |===================================================================
2 . 319129 |===================================================================
3 . 317413 |===================================================================
Caffe 2020-02-13
Model: GoogleNet - Acceleration: CPU - Iterations: 1000
Milli-Seconds < Lower Is Better
1 . 1585367 |==================================================================
2 . 1589890 |==================================================================
3 . 1586757 |==================================================================
NCNN 20200916
Target: CPU - Model: squeezenet
ms < Lower Is Better
1 . 16.40 |====================================================================
2 . 16.39 |====================================================================
3 . 16.43 |====================================================================
NCNN 20200916
Target: CPU - Model: mobilenet
ms < Lower Is Better
1 . 17.46 |====================================================================
2 . 17.24 |===================================================================
3 . 17.22 |===================================================================
NCNN 20200916
Target: CPU-v2-v2 - Model: mobilenet-v2
ms < Lower Is Better
1 . 7.28 |=====================================================================
2 . 7.24 |====================================================================
3 . 7.33 |=====================================================================
NCNN 20200916
Target: CPU-v3-v3 - Model: mobilenet-v3
ms < Lower Is Better
1 . 6.82 |=====================================================================
2 . 6.78 |====================================================================
3 . 6.86 |=====================================================================
NCNN 20200916
Target: CPU - Model: shufflenet-v2
ms < Lower Is Better
1 . 7.31 |=====================================================================
2 . 7.28 |====================================================================
3 . 7.34 |=====================================================================
NCNN 20200916
Target: CPU - Model: mnasnet
ms < Lower Is Better
1 . 6.58 |=====================================================================
2 . 6.53 |====================================================================
3 . 6.57 |=====================================================================
NCNN 20200916
Target: CPU - Model: efficientnet-b0
ms < Lower Is Better
1 . 8.79 |=====================================================================
2 . 8.64 |====================================================================
3 . 8.69 |====================================================================
NCNN 20200916
Target: CPU - Model: blazeface
ms < Lower Is Better
1 . 2.97 |=====================================================================
2 . 2.93 |====================================================================
3 . 2.94 |====================================================================
NCNN 20200916
Target: CPU - Model: googlenet
ms < Lower Is Better
1 . 17.76 |====================================================================
2 . 17.75 |====================================================================
3 . 17.78 |====================================================================
NCNN 20200916
Target: CPU - Model: vgg16
ms < Lower Is Better
1 . 41.10 |==================================================================
2 . 42.30 |====================================================================
3 . 41.33 |==================================================================
NCNN 20200916
Target: CPU - Model: resnet18
ms < Lower Is Better
1 . 13.89 |====================================================================
2 . 13.94 |====================================================================
3 . 13.96 |====================================================================
NCNN 20200916
Target: CPU - Model: alexnet
ms < Lower Is Better
1 . 11.49 |====================================================================
2 . 11.56 |====================================================================
3 . 11.53 |====================================================================
NCNN 20200916
Target: CPU - Model: resnet50
ms < Lower Is Better
1 . 23.37 |===================================================================
2 . 23.55 |====================================================================
3 . 23.53 |====================================================================
NCNN 20200916
Target: CPU - Model: yolov4-tiny
ms < Lower Is Better
1 . 27.88 |===================================================================
2 . 28.20 |====================================================================
3 . 28.07 |====================================================================
NCNN 20200916
Target: Vulkan GPU - Model: squeezenet
ms < Lower Is Better
1 . 6.22 |====================================================================
2 . 6.27 |=====================================================================
3 . 6.13 |===================================================================
NCNN 20200916
Target: Vulkan GPU - Model: mobilenet
ms < Lower Is Better
1 . 9.60 |================================================================
2 . 9.79 |=================================================================
3 . 10.22 |====================================================================
NCNN 20200916
Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2
ms < Lower Is Better
1 . 4.35 |=====================================================================
2 . 4.35 |=====================================================================
3 . 4.35 |=====================================================================
NCNN 20200916
Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3
ms < Lower Is Better
1 . 8.35 |====================================================================
2 . 8.23 |===================================================================
3 . 8.46 |=====================================================================
NCNN 20200916
Target: Vulkan GPU - Model: shufflenet-v2
ms < Lower Is Better
1 . 3.20 |=====================================================================
2 . 3.20 |=====================================================================
3 . 3.20 |=====================================================================
NCNN 20200916
Target: Vulkan GPU - Model: mnasnet
ms < Lower Is Better
1 . 4.44 |=====================================================================
2 . 4.44 |=====================================================================
3 . 4.44 |=====================================================================
NCNN 20200916
Target: Vulkan GPU - Model: efficientnet-b0
ms < Lower Is Better
1 . 11.93 |==================================================================
2 . 12.20 |====================================================================
3 . 12.25 |====================================================================
NCNN 20200916
Target: Vulkan GPU - Model: blazeface
ms < Lower Is Better
1 . 0.90 |=====================================================================
2 . 0.89 |====================================================================
3 . 0.89 |====================================================================
NCNN 20200916
Target: Vulkan GPU - Model: googlenet
ms < Lower Is Better
1 . 8.63 |=====================================================================
2 . 8.25 |==================================================================
3 . 8.41 |===================================================================
NCNN 20200916
Target: Vulkan GPU - Model: vgg16
ms < Lower Is Better
1 . 80.33 |====================================================================
2 . 80.68 |====================================================================
3 . 80.10 |====================================================================
NCNN 20200916
Target: Vulkan GPU - Model: resnet18
ms < Lower Is Better
1 . 3.83 |=====================================================================
2 . 3.82 |=====================================================================
3 . 3.81 |=====================================================================
NCNN 20200916
Target: Vulkan GPU - Model: alexnet
ms < Lower Is Better
1 . 28.12 |===================================================================
2 . 28.66 |====================================================================
3 . 28.36 |===================================================================
NCNN 20200916
Target: Vulkan GPU - Model: resnet50
ms < Lower Is Better
1 . 11.79 |===================================================================
2 . 11.85 |====================================================================
3 . 11.92 |====================================================================
NCNN 20200916
Target: Vulkan GPU - Model: yolov4-tiny
ms < Lower Is Better
1 . 21.70 |====================================================================
2 . 21.32 |===================================================================
3 . 21.05 |==================================================================
Mlpack Benchmark
Benchmark: scikit_ica
Seconds < Lower Is Better
1 . 53.53 |===================================================================
2 . 52.58 |==================================================================
3 . 54.33 |====================================================================
Mlpack Benchmark
Benchmark: scikit_qda
Seconds < Lower Is Better
1 . 44.98 |===================================================================
2 . 45.91 |====================================================================
3 . 45.89 |====================================================================
Mlpack Benchmark
Benchmark: scikit_svm
Seconds < Lower Is Better
1 . 19.75 |====================================================================
2 . 19.69 |====================================================================
3 . 19.67 |====================================================================
Mlpack Benchmark
Benchmark: scikit_linearridgeregression
Seconds < Lower Is Better
1 . 1.44 |=====================================================================
2 . 1.43 |=====================================================================
3 . 1.43 |=====================================================================
GROMACS 2020.3
Water Benchmark
Ns Per Day > Higher Is Better
1 . 2.529 |====================================================================
2 . 2.528 |====================================================================
3 . 2.527 |====================================================================
FFTE 7.0
N=256, 3D Complex FFT Routine
MFLOPS > Higher Is Better
1 . 83303.76 |================================================================
2 . 83979.88 |=================================================================
3 . 83465.84 |=================================================================
Apache CouchDB 3.1.1
Bulk Size: 100 - Inserts: 1000 - Rounds: 24
Seconds < Lower Is Better
1 . 108.15 |===================================================================
2 . 107.56 |===================================================================
3 . 108.11 |===================================================================
BYTE Unix Benchmark 3.6
Computational Test: Dhrystone 2
LPS > Higher Is Better
1 . 46013391.3 |===============================================================
2 . 45773092.9 |===============================================================
3 . 46091339.8 |===============================================================