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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mrCUDA: Low-Overhead Middleware for Transparently Migrating CUDA Execution from Remote to Local GPUs

SESSION: Regular & ACM Student Research Competition Poster Reception

EVENT TYPE: Posters, Receptions, ACM Student Research Competition

EVENT TAG(S): HPC Beginner Friendly, Regular Poster

TIME: 5:15PM - 7:00PM

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

AUTHOR(S):Pak Markthub, Akihiro Nomura, Satoshi Matsuoka

ROOM:Level 4 - Lobby


rCUDA is a state-of-the-art remote CUDA execution middleware that enables CUDA
applications running on one node to transparently use GPUs on other nodes. With
this capability, applications can use nodes that do not have enough unoccupied
GPUs by using rCUDA to borrow idle GPUs from some other nodes. However, those
applications may suffer from rCUDA's overhead; especially for applications that
frequently call CUDA kernels or have to transfer a lot of data, rCUDA's
overhead can be detrimentally large. We propose mrCUDA, a middleware for
transparently live-migrating CUDA execution from remote to local GPUs, and show
that mrCUDA's overhead is negligibly small compared with rCUDA's overhead.
Hence, mrCUDA enables applications to run on nodes that does not have enough
unoccupied GPUs (by using rCUDA) and later migrate the work to local GPUs
(thus, get rid of rCUDA's overhead) when available.

Chair/Author Details:

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

Pak Markthub - Tokyo Institute of Technology

Akihiro Nomura - Tokyo Institute of Technology

Satoshi Matsuoka - Tokyo Institute of Technology

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