Name
Abstract | ||
|---|---|---|
As a general purpose scalable parallel programming model for coding highly parallel applications, CUDA from NVIDIA provides several key abstractions: a hierarchy of thread blocks, shared memory, and barrier synchronization. It has proven to be rather effective at programming multithreaded many-core GPUs that scale transparently to hundreds of cores; as a result, scientists all over the industry and academia are using CUDA to dramatically expedite on production and codes. GPU-based clusters are likely to play an essential role in future cloud computing centers, because some computation-intensive applications may require GPUs as well as CPUs. In this paper, we adopted the PCI pass-through technology and set up virtual machines in a virtual environment; thus, we were able to use the NVIDIA graphics card and the CUDA high performance computing as well. In this way, the virtual machine has not only the virtual CPU but also the real GPU for computing. The performance of the virtual machine is predicted to increase dramatically. This paper measured the difference of performance between physical and virtual machines using CUDA, and investigated how virtual machines would verify CPU numbers under the influence of CUDA performance. At length, we compared CUDA performance of two open source virtualization hypervisor environments, with or without using PCI pass-through. Through experimental results, we will be able to tell which environment is most efficient in a virtual environment with CUDA. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/s11227-013-1034-4 | The Journal of Supercomputing |
Keywords | Field | DocType |
CUDA,GPU virtualization,Cloud computing,PCI pass-through | Virtualization,Virtual machine,Supercomputer,Computer science,CUDA,Parallel computing,Hypervisor,Parallel programming model,Operating system,Cloud computing,CUDA Pinned memory | Journal |
Volume | Issue | ISSN |
68 | 1 | 0920-8542 |
Citations | PageRank | References |
9 | 0.48 | 18 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chao-Tung Yang | 1 | 1196 | 139.50 |
| Jung-Chun Liu | 2 | 233 | 33.10 |
| Hsien-Yi Wang | 3 | 27 | 3.22 |
| Ching-Hsien Hsu | 4 | 1121 | 125.53 |