Publication | Closed Access
vCUDA: GPU-Accelerated High-Performance Computing in Virtual Machines
233
Citations
27
References
2011
Year
EngineeringGpu BenchmarkingComputer ArchitectureCuda ApplicationsApi Call InterceptionGpu ComputingParallel ComputingComputer EngineeringVirtualization SupportComputer ScienceVcuda ArchitectureGpu ClusterGpu ArchitectureEdge ComputingCloud ComputingParallel ProgrammingVirtual MachinesSystem SoftwareGpu Virtualization
This paper describes vCUDA, a general-purpose graphics processing unit (GPGPU) computing solution for virtual machines (VMs). vCUDA allows applications executing within VMs to leverage hardware acceleration, which can be beneficial to the performance of a class of high-performance computing (HPC) applications. The key insights in our design include API call interception and redirection and a dedicated RPC system for VMs. With API interception and redirection, Compute Unified Device Architecture (CUDA) applications in VMs can access a graphics hardware device and achieve high computing performance in a transparent way. In the current study, vCUDA achieved a near-native performance with the dedicated RPC system. We carried out a detailed analysis of the performance of our framework. Using a number of unmodified official examples from CUDA SDK and third-party applications in the evaluation, we observed that CUDA applications running with vCUDA exhibited a very low performance penalty in comparison with the native environment, thereby demonstrating the viability of vCUDA architecture.
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