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Automatic CPU-GPU Communication Management and Optimization

Summary: Automatic CPU-GPU Communication
Management and Optimization
Thomas B. Jablin Prakash Prabhu James A. Jablin
Nick P. Johnson Stephen R. Beard David I. August
Princeton University, Princeton, NJ Brown University, Providence, RI
{tjablin, pprabhu, npjohnso, sbeard, august}@cs.princeton.edu jjablin@cs.brown.edu
The performance benefits of GPU parallelism can be enormous,
but unlocking this performance potential is challenging. The ap-
plicability and performance of GPU parallelizations is limited by
the complexities of CPU-GPU communication. To address these
communications problems, this paper presents the first fully auto-
matic system for managing and optimizing CPU-GPU communca-
tion. This system, called the CPU-GPU Communication Man-
ager (CGCM), consists of a run-time library and a set of com-
piler transformations that work together to manage and optimize
CPU-GPU communication without depending on the strength of
static compile-time analyses or on programmer-supplied annota-
tions. CGCM eases manual GPU parallelizations and improves the
applicability and performance of automatic GPU parallelizations.


Source: August, David - Department of Computer Science, Princeton University


Collections: Computer Technologies and Information Sciences