Graphics processing units (GPUs) have become an attractive platform for general-purpose computing (
GPGPU
) in various domains. Making GPUs a time-multiplexing resource is a key to consolidating
GPGPU
applications (apps) in multi-tenant cloud platforms. However, advanced
GPGPU
apps pose a new challenge for consolidation. Such highly functional
GPGPU
apps, referred to as
GPU eaters, can easily monopolize a shared GPU and starve collocated
GPGPU
apps. This paper presents
GLoop, which is a software runtime that enables us to consolidate
GPGPU
apps including GPU eaters. GLoop offers an
event-driven programming model, which allows GLoop-based apps to inherit the GPU eaters' high functionality while proportionally scheduling them on a shared GPU in an isolated manner. We implemented a prototype of GLoop and ported eight GPU eaters on it. The experimental results demonstrate that our prototype successfully schedules the consolidated
GPGPU
apps on the basis of its scheduling policy and isolates resources among them.
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