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Towards Multi-tenant GPGPU : Event-driven Programming Model for System-wide Scheduling on Shared GPUs
| Content Provider | Semantic Scholar |
|---|---|
| Author | Suzuki, Yusuke |
| Copyright Year | 2016 |
| Abstract | Graphics processing units (GPUs) are attractive to the generalpurpose computing (GPGPU) beyond the graphics purpose. Sharing GPUs among such GPGPU applications is a key requirement especially for cloud platforms whose resources are utilized by various cloud users. However, consolidating recent GPU applications, referred to as GPU eaters, on a GPU poses a new challenge. Such advanced applications are designed based on the assumption that only one GPU application runs on a GPU at a time. In this paper, we present GLoop, a GPGPU framework that allows multiple GPU eaters to share a GPU. GLoop offers an event-driven programming model that generates scheduling points in GPU kernels. It achieves resource isolation among GPU applications and schedules applications by suspending/resuming GPU kernels only if necessary to reduce the number of kernel launches. The preliminary experiments demonstrate that GLoop model is applicable to a GPU eater. The results also show that GLoop enables two GPGPU applications to run concurrently on a shared GPU by interleaving GPU kernel execution. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://www.cs.utexas.edu/~mars2016/workshop-program/MaRS_2016_paper_6.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
