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GPU virtualization
in openSUSE
Virtualization Team
Liang Yan
lyan@suse.com
GPU virtualization in openSUSE
1. GPU virtualization
Definition and Classification
Use scenario
2. Critical techniques
SRIOV vs MDEV
3. Demo
4. Current status and Todo
openSUSE
Outside Vendors
5. Q&A
GPU Virtualization
Huge market: Gartner Report:
2017: $ 145B
2018: $ 175B
2019: $ 206B
User Cases:
Auto driver: Tesla
Medical area:
Finance: wall street
Electronic Commerce: Delivery Transport, Recommend Sale
Language Translate/ AI:
GPU Virtualization
GPU Virtualization in Cloud, providing machine
learning service
Google Colaboratory
Paperspace Gradient
FloydHub Workspace
Lambda GPU Cloud
AWS Deep Learning AMIs
GCP Deep Learning VM Images
GPU Virtualization
GPU virtualization, Software Implementation
● Software Emulated
CPU “trap and emulate” GPU instruction,Slow, limited function
● API forwarding
Intercept API, Simple idea, but painful for API compatible
IO virtualization, GPU as a PCIe device today.
● GPU Passthrough
● Full GPU Virtualization
Para?
VirtIO-GPU
Run “native” graphics driver in VM, Full API, 3D
Achieve good performance and moderate multiplexing capability
● Split
Time Slices
framebuffer memory
● Isolate
Give a neat access between VM and Host Physical Device
IOMMU/Mdev and VFIO
DMA
Interrupt
● Schedule
Efficient and Robust
Pretty fix for AMD, hardware implementation
More flexible for NVIDIA, RR, BOND
GPU Virtualization
GPU Virtualization
Nvidia
Tesla Series: Volta Pascal Maxwell M6 M10 M60 P4 P6 P40 P100 V100
GRID: Kepler K1 K2 (VDI and application virtualization)
http://www.nvidia.com/object/grid-certified-servers.html
AMD
FirePro S7150 S7150x2
Radeon Pro V320 V340
Radeon Instinct MI6 MI8 MI25(Machine learning interface, CUDA compatible with HIP)
MI50/60 MI100
https://lists.freedesktop.org/archives/amd-gfx/2016-December/004075.html
Intel
     Haswell(3VMs)  Broadwell(7VMs) Skylake, Kaby Lake
2020, dedicated GPU
     https://github.com/intel/gvt-linux/wiki
SRIOV vs Mdev
GPU real Workload:
This is why GPU virtualization is doable
SRIOV vs Mdev
GPU real Workload:
This is why GPU virtualization is doable
10
MDEV 80~90%
no BSF, UUID
No IOMMU, MMIO trap
vGPU command needs address translation
Time Slice
Could split more vGPU
VFIO-Mdev Passthrough
SRIOV 97%
Bus/Slot/Function
IOMMU/VFIO
vGPU command runs directly
Time Slice
VF number is fixed
VFIO Passthrough
SR-IOV Mediated
MEDIATED DEVICE FRAMEWORK
Physical Interface sysfs Mdev Bus
Vendor Mdev
Vfio-mdev.ko
Vfio API compatible
TYPE1 IOMMU
i915.ko
nvidia.ko
Management
create
destroy
DEMO
SUSE
- Intel KVMGT technical ready
- Nvidia GRID technical ready
- AMD MxGPU technical ready
- GPU virtualization for Cloud
- GPU virtualization for CAAS
Outside
- Remote display
- IOMMU compatible
- Live Migration
- Scalability: Schedule Algorithm **
GPU for Container
FPGA/NPU/TPU Virtualization?
Status and Future
REFERENCE
VGPU ON KVM
An Introduction to PCI Device Assignment with VFIO - Alex Williamson,
Red Hat [Qemu-devel] [PATCH v7 0/4] Add Mediated device support
[libvirt] [RFC] libvirt vGPU QEMU integratio
https://yq.aliyun.com/articles/590909?spm=a2c4e.11153940.blogcont599189.23.f2016d7bXPo7TD
https://zhuanlan.zhihu.com/p/35489035
Question?
Thanks!
GPU virtualization in openSUSE

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GPUv virtualization in openSUSE: SRIOV vs MDEV

  • 1. GPU virtualization in openSUSE Virtualization Team Liang Yan lyan@suse.com
  • 2. GPU virtualization in openSUSE 1. GPU virtualization Definition and Classification Use scenario 2. Critical techniques SRIOV vs MDEV 3. Demo 4. Current status and Todo openSUSE Outside Vendors 5. Q&A
  • 3. GPU Virtualization Huge market: Gartner Report: 2017: $ 145B 2018: $ 175B 2019: $ 206B User Cases: Auto driver: Tesla Medical area: Finance: wall street Electronic Commerce: Delivery Transport, Recommend Sale Language Translate/ AI:
  • 4. GPU Virtualization GPU Virtualization in Cloud, providing machine learning service Google Colaboratory Paperspace Gradient FloydHub Workspace Lambda GPU Cloud AWS Deep Learning AMIs GCP Deep Learning VM Images
  • 5. GPU Virtualization GPU virtualization, Software Implementation ● Software Emulated CPU “trap and emulate” GPU instruction,Slow, limited function ● API forwarding Intercept API, Simple idea, but painful for API compatible IO virtualization, GPU as a PCIe device today. ● GPU Passthrough ● Full GPU Virtualization Para? VirtIO-GPU
  • 6. Run “native” graphics driver in VM, Full API, 3D Achieve good performance and moderate multiplexing capability ● Split Time Slices framebuffer memory ● Isolate Give a neat access between VM and Host Physical Device IOMMU/Mdev and VFIO DMA Interrupt ● Schedule Efficient and Robust Pretty fix for AMD, hardware implementation More flexible for NVIDIA, RR, BOND GPU Virtualization
  • 7. GPU Virtualization Nvidia Tesla Series: Volta Pascal Maxwell M6 M10 M60 P4 P6 P40 P100 V100 GRID: Kepler K1 K2 (VDI and application virtualization) http://www.nvidia.com/object/grid-certified-servers.html AMD FirePro S7150 S7150x2 Radeon Pro V320 V340 Radeon Instinct MI6 MI8 MI25(Machine learning interface, CUDA compatible with HIP) MI50/60 MI100 https://lists.freedesktop.org/archives/amd-gfx/2016-December/004075.html Intel      Haswell(3VMs)  Broadwell(7VMs) Skylake, Kaby Lake 2020, dedicated GPU      https://github.com/intel/gvt-linux/wiki
  • 8. SRIOV vs Mdev GPU real Workload: This is why GPU virtualization is doable
  • 9. SRIOV vs Mdev GPU real Workload: This is why GPU virtualization is doable
  • 10. 10 MDEV 80~90% no BSF, UUID No IOMMU, MMIO trap vGPU command needs address translation Time Slice Could split more vGPU VFIO-Mdev Passthrough SRIOV 97% Bus/Slot/Function IOMMU/VFIO vGPU command runs directly Time Slice VF number is fixed VFIO Passthrough SR-IOV Mediated
  • 11. MEDIATED DEVICE FRAMEWORK Physical Interface sysfs Mdev Bus Vendor Mdev Vfio-mdev.ko Vfio API compatible TYPE1 IOMMU i915.ko nvidia.ko Management create destroy
  • 12. DEMO
  • 13. SUSE - Intel KVMGT technical ready - Nvidia GRID technical ready - AMD MxGPU technical ready - GPU virtualization for Cloud - GPU virtualization for CAAS Outside - Remote display - IOMMU compatible - Live Migration - Scalability: Schedule Algorithm ** GPU for Container FPGA/NPU/TPU Virtualization? Status and Future
  • 14. REFERENCE VGPU ON KVM An Introduction to PCI Device Assignment with VFIO - Alex Williamson, Red Hat [Qemu-devel] [PATCH v7 0/4] Add Mediated device support [libvirt] [RFC] libvirt vGPU QEMU integratio https://yq.aliyun.com/articles/590909?spm=a2c4e.11153940.blogcont599189.23.f2016d7bXPo7TD https://zhuanlan.zhihu.com/p/35489035