A Unified Runtime System for Heterogeneous Multi-core Architectures

Abstract

Approaching the theoretical performance of heterogeneous multicore architectures, equipped with specialized accelerators, is a challenging issue. Unlike regular CPUs that can transparently access the whole global memory address range, accelerators usually embed local memory on which they perform all their computations using a specific instruction set. While many research efforts have been devoted to offloading parts of a program over such coprocessors, the real challenge is to find a programming model providing a unified view of all available computing units.In this paper, we present an original runtime system providing a high-level, unified execution model allowing seamless execution of tasks over the underlying heterogeneous hardware. The runtime is based on a hierarchical memory management facility and on a codelet scheduler. We demonstrate the efficiency of our solution with a LU decomposition for both homogeneous (3.8 speedup on 4 cores) and heterogeneous machines (95 % efficiency). We also show that a “granularity aware” scheduling can improve execution time by 35 %.KeywordsMain MemoryExecution ModelRuntime SystemHeterogeneous ArchitectureEmbed MemoryThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.