Enabling CUDA acceleration within virtual machines using rCUDA
|Research Area:||High Performance Clusters||Year:||2011|
|Type of Publication:||Article||Keywords:||Virtual machine;rCUDA|
|Journal:||Proceedings of HiPC 2011|
Clusters;CUDA;High performance computing;Virtualizations;
The hardware and software advances of Graphics Processing Units (GPUs) have favored the develop- ment of GPGPU (General-Purpose Computation on GPUs) and its adoption in many scientific, engineering, and industrial areas. Thus, GPUs are increasingly being introduced in high-performance computing systems as well as in datacenters. On the other hand, virtualization technologies are also receiving rising interest in these domains, because of their many benefits on acquisition and maintenance savings. There are currently several works on GPU virtualization. However, there is no standard solution allowing access to GPGPU capabilities from virtual machine environments like, e.g., VMware, Xen, VirtualBox, or KVM. Such lack of a standard solution is delaying the integration of GPGPU into these domains.