Local and remote GPUs perform similar with EDR 100G InfiniBand

C Reaño, F Silla, G Shainer, S Schultz - … of the Industrial Track of the …, 2015 - dl.acm.org
C Reaño, F Silla, G Shainer, S Schultz
Proceedings of the Industrial Track of the 16th International Middleware …, 2015dl.acm.org
The use of graphics processing units (GPUs) to accelerate some portions of applications is
widespread nowadays. To avoid the usual inconveniences associated with these
accelerators (high acquisition cost, high energy consumption, and low utilization), one
possible solution is sharing them among several nodes in the cluster. Several years ago,
remote GPU virtualization middleware systems appeared to implement this solution.
Although these systems tackled the aforementioned inconveniences, their performance was …
The use of graphics processing units (GPUs) to accelerate some portions of applications is widespread nowadays. To avoid the usual inconveniences associated with these accelerators (high acquisition cost, high energy consumption, and low utilization), one possible solution is sharing them among several nodes in the cluster. Several years ago, remote GPU virtualization middleware systems appeared to implement this solution. Although these systems tackled the aforementioned inconveniences, their performance was usually impaired by the low bandwidth attained by the underlying network. However, the recent advances in InfiniBand fabrics have changed this trend. In this paper we analyze how the high bandwidth provided by the new EDR 100G InfiniBand fabric allows remote GPU virtualization middleware systems not only to perform very similar to local GPUs, but also to improve overall performance for some applications.
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