Intel Core i9-9900K testing with a ASRock Z390M Pro4 (P4.20 BIOS) and Intel UHD 630 3GB 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 2101135-HA-9900KTUES77
9900K Tues
Intel Core i9-9900K testing with a ASRock Z390M Pro4 (P4.20 BIOS) and Intel UHD 630 3GB on Ubuntu 20.04 via the Phoronix Test Suite.
1:
Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASRock Z390M Pro4 (P4.20 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16GB, Disk: 240GB Corsair Force MP510, Graphics: Intel UHD 630 3GB (1200MHz), Audio: Realtek ALC892, Monitor: G237HL, Network: Intel I219-V
OS: Ubuntu 20.04, Kernel: 5.9.0-050900rc1daily20200819-generic (x86_64) 20200818, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 4.6 Mesa 20.0.4, OpenCL: OpenCL 2.1, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080
2:
Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASRock Z390M Pro4 (P4.20 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16GB, Disk: 240GB Corsair Force MP510, Graphics: Intel UHD 630 3GB (1200MHz), Audio: Realtek ALC892, Monitor: G237HL, Network: Intel I219-V
OS: Ubuntu 20.04, Kernel: 5.9.0-050900rc1daily20200819-generic (x86_64) 20200818, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 4.6 Mesa 20.0.4, OpenCL: OpenCL 2.1, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080
3:
Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASRock Z390M Pro4 (P4.20 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16GB, Disk: 240GB Corsair Force MP510, Graphics: Intel UHD 630 3GB (1200MHz), Audio: Realtek ALC892, Monitor: G237HL, Network: Intel I219-V
OS: Ubuntu 20.04, Kernel: 5.9.0-050900rc1daily20200819-generic (x86_64) 20200818, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 4.6 Mesa 20.0.4, OpenCL: OpenCL 2.1, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080
Quantum ESPRESSO 6.7
Input: AUSURF112
Seconds < Lower Is Better
1 . 1452.78 |================================================================
2 . 1498.09 |==================================================================
3 . 1497.60 |==================================================================
dav1d 0.8.1
Video Input: Summer Nature 1080p
FPS > Higher Is Better
1 . 622.70 |===================================================================
2 . 612.56 |==================================================================
3 . 620.58 |===================================================================
Mobile Neural Network 1.1.1
Model: SqueezeNetV1.0
ms < Lower Is Better
1 . 4.930 |===================================================================
2 . 4.954 |===================================================================
3 . 5.010 |====================================================================
Mobile Neural Network 1.1.1
Model: inception-v3
ms < Lower Is Better
1 . 32.03 |====================================================================
2 . 31.61 |===================================================================
3 . 31.65 |===================================================================
Mobile Neural Network 1.1.1
Model: mobilenet-v1-1.0
ms < Lower Is Better
1 . 2.654 |====================================================================
2 . 2.643 |====================================================================
3 . 2.622 |===================================================================
dav1d 0.8.1
Video Input: Chimera 1080p
FPS > Higher Is Better
1 . 680.94 |==================================================================
2 . 688.38 |===================================================================
3 . 686.40 |===================================================================
OpenFOAM 8
Input: Motorbike 30M
Seconds < Lower Is Better
1 . 238.60 |===================================================================
2 . 236.21 |==================================================================
3 . 236.72 |==================================================================
TNN 0.2.3
Target: CPU - Model: MobileNet v2
ms < Lower Is Better
1 . 285.12 |==================================================================
2 . 287.71 |===================================================================
3 . 285.73 |===================================================================
Kripke 1.2.4
Throughput FoM > Higher Is Better
1 . 32520703 |================================================================
2 . 32779697 |=================================================================
3 . 32682987 |=================================================================
Algebraic Multi-Grid Benchmark 1.2
Figure Of Merit > Higher Is Better
1 . 236840200 |================================================================
2 . 238320900 |================================================================
3 . 237803500 |================================================================
LAMMPS Molecular Dynamics Simulator 29Oct2020
Model: Rhodopsin Protein
ns/day > Higher Is Better
1 . 6.895 |====================================================================
2 . 6.896 |====================================================================
3 . 6.854 |====================================================================
Mobile Neural Network 1.1.1
Model: resnet-v2-50
ms < Lower Is Better
1 . 27.68 |====================================================================
2 . 27.56 |====================================================================
3 . 27.61 |====================================================================
LAMMPS Molecular Dynamics Simulator 29Oct2020
Model: 20k Atoms
ns/day > Higher Is Better
1 . 6.179 |====================================================================
2 . 6.168 |====================================================================
3 . 6.160 |====================================================================
dav1d 0.8.1
Video Input: Summer Nature 4K
FPS > Higher Is Better
1 . 171.06 |===================================================================
2 . 171.45 |===================================================================
3 . 171.33 |===================================================================
OpenFOAM 8
Input: Motorbike 60M
Seconds < Lower Is Better
1 . 1180.72 |==================================================================
2 . 1181.00 |==================================================================
3 . 1179.54 |==================================================================
LULESH 2.0.3
z/s > Higher Is Better
1 . 4965.30 |==================================================================
2 . 4963.61 |==================================================================
3 . 4967.85 |==================================================================
TNN 0.2.3
Target: CPU - Model: SqueezeNet v1.1
ms < Lower Is Better
1 . 268.07 |===================================================================
2 . 268.18 |===================================================================
3 . 268.26 |===================================================================
dav1d 0.8.1
Video Input: Chimera 1080p 10-bit
FPS > Higher Is Better
1 . 119.19 |===================================================================
2 . 119.22 |===================================================================
3 . 119.23 |===================================================================
CP2K Molecular Dynamics 8.1
Fayalite-FIST Data
Seconds < Lower Is Better
1 . 1046.29 |==================================================================
3 . 1046.02 |==================================================================
Mobile Neural Network 1.1.1
Model: MobileNetV2_224
ms < Lower Is Better
1 . 2.758 |==================================================================
2 . 2.840 |====================================================================
3 . 2.753 |==================================================================