Strider: Runtime Support for Optimizing Strided Data Accesses on Multi-Cores with Explicitly Managed Memories

Abstract

Abstract-Multi-core processors with explicitly-managed local memories provide advanced capabilities to optimize data caching and prefetching in software. Unfortunately, these capabilities are neither easily accessible to programmers, nor exploited to their maximum potential by current language, compiler, or runtime frameworks. We present Strider, a runtime framework for optimizing compilers on multi-core processors with softwaremanaged memories. Strider transparently optimizes grouping, decomposition, and scheduling of explicit software-managed accesses to multi-dimensional arrays in nested loops, given a highlevel specification of loops and their data access patterns. In particular, Strider contributes new methods to improve temporal locality, optimize the critical path of scheduling data transfers for multi-stride accesses in regular nested parallel loops, and distribute accesses between cores. The prototype of Strider on the IBM Cell processor performs competitively to hand-optimized code and better than contemporary language frameworks, in both non-trivial parallel applications and important application kernels.

How to Transfer Strided Data into Accelerator

“…Due to practicability, strided data is widely used in global memory access 28 and parallel pile systems. 35 However, data striding would damage access performance, so strided data access operations 34 and runtime support 36 are implemented and proposed to strided data access and transfer.…”