Difference between revisions of "GPGPU-FedCloud"
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*VM snapshot with memory is not supported | *VM snapshot with memory is not supported | ||
= Cloud Management Frameworks = | |||
Some initiatives but not completed | Some initiatives but not completed |
Revision as of 14:46, 30 April 2015
Status of accelerated computing in Clouds
Need modification/support at all levels
- Chipset : HW virtualization support (otherwise some limitation)
- OS level: correct kernel configuration for the accelerators
- Hypervisor: configuration pass-through, vGPU
- CMFs: VM start, scheduler
- FedCloud facilities: accounting, information discovery
- Application: VM images with correct drivers for specific chipsets
Accelerators
GPGPU (General-Purpose computing on Graphical Processing Units)
NVIDIA GPU/Tesla/GRID, AMD Radeon/FirePro, Intel HD Graphics,...
Virtualization using VGA pass-through, vGPU (GPU partitioning) - NVIDIA GRID accelerators
Intel Many Integrated Core Architecture
Xeon Phi Coprocessor
Virtualization using PCI pass-through
Specialized PCIe cards with accelerators
DSP (Digital Signal Processors)
FPGA (Field Programmable Gate Array)
Not commonly used in cloud environment
Hypervisors
QEMU/KVM
Supports only pass-through virtualization model
vGPU support is under development
Citrix XenServer 6, VMware ESXi 5.1
Support both pass-through and vGPU virtualization models
Limitations:
- vGPU support require certified server HW
- Live VM migration is not supported
- VM snapshot with memory is not supported
Cloud Management Frameworks
Some initiatives but not completed
- HeterogeneousGpuAcceleratorSupport in OpenStack (https://wiki.openstack.org/wiki/HeterogeneousGpuAcceleratorSupport)
- GPU and vGPU support for CloudStack Guest VMs (https://cwiki.apache.org/confluence/display/CLOUDSTACK/GPU+and+vGPU+support+for+CloudStack+Guest+VMs)
Work to be done:
- Define VM types/flavors with attributes for GPGPU
- Modify VM start to allow passthrough or allocate vGPU
- Modify scheduler to allocate VMs with GPGPU correctly