TENSILE: A Tensor granularity dynamic GPU memory scheduling method toward multiple dynamic workloads system. (arXiv:2105.13336v5 [cs.DC] UPDATED)

Recently, deep learning has been an area of intense research. However, as a
kind of computing-intensive task, deep learning highly relies on the scale of
GPU memory, which is usually prohibitive and scarce. Although some extensive
works have been proposed for dynamic GPU memory management, they are hard to
apply to systems with multiple dynamic workloads, such as in-database machine
learning systems.

In this paper, we demonstrated TENSILE, a method of managing GPU memory in
tensor granularity to reduce the …

arxiv gpu memory scheduling tensor