Title :
Argus-G: Comprehensive, Low-Cost Error Detection for GPGPU Cores
Author :
Nathan, Ralph ; Sorin, Daniel J.
Author_Institution :
Duke Univ., Durham, NC, USA
Abstract :
We have developed and evaluated Argus-G, an error detection scheme for general purpose GPU (GPGPU) cores. Argus-G is a natural extension of the Argus error detection scheme for CPU cores, and we demonstrate how to modify Argus such that it is compatible with GPGPU cores. Using an RTL prototype, we experimentally show that Argus-G can detect the vast majority of injected errors at relatively low performance, area, and power costs.
Keywords :
error detection; graphics processing units; Argus-G; CPU cores; GPGPU cores; general purpose GPU cores; low-cost error detection; Benchmark testing; Conferences; Graphics processing units; Hardware; Hardware design languages; Instruction sets; Registers; Graphics processors; fault tolerance;
Journal_Title :
Computer Architecture Letters
DOI :
10.1109/LCA.2014.2298391