KVM testing on Debian 11 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 2211265-NE-20221127025
2022-11-27-0323
KVM testing on Debian 11 via the Phoronix Test Suite.
Common KVM:
Processor: Common KVM (40 Cores), Motherboard: QEMU Standard PC (i440FX + PIIX 1996) (rel-1.15.0-0-g2dd4b9b3f840-prebuilt.qemu.org BIOS), Chipset: Intel 440FX 82441FX PMC, Memory: 60GB, Disk: 64GB QEMU HDD, Graphics: bochs-drmdrmfb, Monitor: QEMU Monitor, Network: Red Hat Virtio device
OS: Debian 11, Kernel: 5.10.0-19-amd64 (x86_64), Vulkan: 1.0.2, Compiler: GCC 10.2.1 20210110, File-System: ext4, Screen Resolution: 1024x768, System Layer: KVM
oneDNN 2.7
Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
Common KVM . 8095.32 |=========================================================
oneDNN 2.7
Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
Common KVM . 18112.5 |=========================================================
oneDNN 2.7
Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Common KVM . 8183.33 |=========================================================
oneDNN 2.7
Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Common KVM . 17832.1 |=========================================================
oneDNN 2.7
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Common KVM . 8173.88 |=========================================================
oneDNN 2.7
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Common KVM . 17503.0 |=========================================================
oneDNN 2.7
Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Common KVM . 57.31 |===========================================================
oneDNN 2.7
Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Common KVM . 137.54 |==========================================================
oneDNN 2.7
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Common KVM . 1190.10 |=========================================================
oneDNN 2.7
Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Common KVM . 29.38 |===========================================================
oneDNN 2.7
Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Common KVM . 86.73 |===========================================================
oneDNN 2.7
Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Common KVM . 49.73 |===========================================================
oneDNN 2.7
Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Common KVM . 14.40 |===========================================================
FFTW 3.3.6
Build: Float + SSE - Size: 2D FFT Size 4096
Mflops > Higher Is Better
Common KVM . 10466.6 |=========================================================
FFTW 3.3.6
Build: Float + SSE - Size: 1D FFT Size 4096
Mflops > Higher Is Better
Common KVM . 17520 |===========================================================
FFTW 3.3.6
Build: Float + SSE - Size: 1D FFT Size 32
Mflops > Higher Is Better
Common KVM . 9666.9 |==========================================================
FFTW 3.3.6
Build: Stock - Size: 2D FFT Size 4096
Mflops > Higher Is Better
Common KVM . 3389.6 |==========================================================
FFTW 3.3.6
Build: Stock - Size: 1D FFT Size 4096
Mflops > Higher Is Better
Common KVM . 4550.5 |==========================================================
FFTW 3.3.6
Build: Stock - Size: 2D FFT Size 32
Mflops > Higher Is Better
Common KVM . 5564.9 |==========================================================
FFTW 3.3.6
Build: Stock - Size: 1D FFT Size 32
Mflops > Higher Is Better
Common KVM . 5500.0 |==========================================================
Dolfyn 0.527
Computational Fluid Dynamics
Seconds < Lower Is Better
Common KVM . 29.38 |===========================================================
NAMD 2.14
ATPase Simulation - 327,506 Atoms
days/ns < Lower Is Better
Common KVM . 1.68134 |=========================================================
Rodinia 3.1
Test: OpenMP CFD Solver
Seconds < Lower Is Better
Common KVM . 19.08 |===========================================================
Rodinia 3.1
Test: OpenMP Leukocyte
Seconds < Lower Is Better
Common KVM . 176.67 |==========================================================
Rodinia 3.1
Test: OpenMP LavaMD
Seconds < Lower Is Better
Common KVM . 217.36 |==========================================================
miniBUDE 20210901
Implementation: OpenMP - Input Deck: BM2
Billion Interactions/s > Higher Is Better
Common KVM . 6.711 |===========================================================
miniBUDE 20210901
Implementation: OpenMP - Input Deck: BM2
GFInst/s > Higher Is Better
Common KVM . 167.78 |==========================================================
oneDNN 2.7
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
oneDNN 2.7
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Common KVM . 22.38 |===========================================================
oneDNN 2.7
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Common KVM . 6.85221 |=========================================================
oneDNN 2.7
Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
oneDNN 2.7
Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
oneDNN 2.7
Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
oneDNN 2.7
Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Common KVM . 104.41 |==========================================================
oneDNN 2.7
Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Common KVM . 45.86 |===========================================================
oneDNN 2.7
Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
oneDNN 2.7
Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
oneDNN 2.7
Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Common KVM . 18.12 |===========================================================
FFTW 3.3.6
Build: Float + SSE - Size: 2D FFT Size 32
Mflops > Higher Is Better
Common KVM . 17990 |===========================================================
Rodinia 3.1
Test: OpenMP Streamcluster
Seconds < Lower Is Better
Common KVM . 20.50 |===========================================================
CloverLeaf
Lagrangian-Eulerian Hydrodynamics
Seconds < Lower Is Better
Common KVM . 84.26 |===========================================================
miniBUDE 20210901
Implementation: OpenMP - Input Deck: BM1
Billion Interactions/s > Higher Is Better
Common KVM . 5.348 |===========================================================
miniBUDE 20210901
Implementation: OpenMP - Input Deck: BM1
GFInst/s > Higher Is Better
Common KVM . 133.70 |==========================================================