Wait-free Programming for General Purpose Computations on Graphics Processors

The fact that graphics processors (GPUs) are today’s most powerful computational hardware for the dollar has motivated researchers to utilize the ubiquitous and powerful GPUs for general-purpose computing. Recent GPUs feature the single-program multiple-data (SPMD) multicore architecture instead of the single-instruction multiple-data (SIMD). However, unlike CPUs, GPUs devote their transistors mainly to data processing rather than data caching and flow control, and consequently most of the powerful GPUs with many cores do not support any synchronization mechanisms between their cores. This prevents GPUs from being deployed more widely for general-purpose computing. This paper aims at bridging the gap between the lack of synchronization mechanisms in recent GPU architectures and the need of synchronization mechanisms in parallel applications. Based on the intrinsic features of recent GPU architectures, we construct strong synchronization objects like wait-free and t-resilient read-modify-write objects for a general model of recent GPU architectures without strong hardware synchronization primitives like test-and-set and compare-and-swap. Accesses to the wait-free objects have time complexity O(N), whether N is the number of processes. Our result demonstrates that it is possible to construct wait-free synchronization mechanisms for GPUs without the need of strong synchronization primitives in hardware and that wait-free programming is possible for GPUs.