sponsored byACMIEEE The International Conference for High Performance 
Computing, Networking, Storage and Analysis
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SCHEDULE: NOV 15-20, 2015

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Improving Application Concurrency on GPUs by Managing Implicit and Explicit Synchronizations

SESSION: Regular & ACM Student Research Competition Poster Reception

EVENT TYPE: Posters, Receptions, ACM Student Research Competition

EVENT TAG(S): HPC Beginner Friendly, ACM Student Research Competition Poster

TIME: 5:15PM - 7:00PM

SESSION CHAIR(S): Michela Becchi, Manish Parashar, Dorian C. Arnold

AUTHOR(S):Michael C. Butler

ROOM:Level 4 - Lobby


GPUs have progressively become part of shared computing environments, such as HPC servers and clusters. Commonly used GPU software stacks (e.g., CUDA and OpenCL), however, are designed for the dedicated use of GPUs by a single application, possibly leading to resource underutilization. In recent years, several node-level runtime components have been proposed to allow the efficient sharing of GPUs among concurrent applications; however, they are limited by synchronizations embedded in the applications or implicitly introduced by the GPU software stack.
In this work, we analyze the effect of explicit and implicit synchronizations on application concurrency and GPU utilization, design runtime mechanisms to bypass these synchronizations, and integrate these mechanisms into a GPU virtualization runtime named Sync-Free GPU (SF-GPU). The resultant runtime removes unnecessary blockages caused by multitenancy, ensuring any two applications running on the same device experience limited to no interference. Finally, we evaluate the impact of our proposed mechanisms.

Chair/Author Details:

Michela Becchi, Manish Parashar, Dorian C. Arnold (Chair) - University of Missouri|Rutgers University|University of New Mexico|

Michael C. Butler - University of Missouri

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