Title :
Using data-level parallelism to accelerate instruction-level redundancy
Author :
Hu, Yu ; Chen, Zhongliang ; Xiaowei Li
Author_Institution :
Key Laboratory of Computer System and Architecture, Institute of Computing Technology, CAS, Beijing, 100190, China
Abstract :
Instruction-level redundancy is an effective scheme to reduce the susceptibility of microprocessors to soft errors, offering high error detection and recovery capability; however, it usually incurs significant performance degradation due to resource racing. Motivated by the fact that narrow-width operands are commonly seen in applications, we exploit data-level parallelism to accelerate instruction-level redundancy. For the instructions within sphere of replication (SoR) of data-level redundancy, normal and redundant versions of the narrow-width operand of the instruction are folded into one register to share the same functional unit during execution hence alleviating resource racing. The other instructions are all protected by instruction-level redundancy. We run SPECint2000 benchmarks on a modified version of SimpleScalar simulator, and synthesize the extra hardware to evaluate area overhead of the proposed pipeline. Experimental results show that our acceleration scheme outperforms conventional instruction-level redundancy by 13% in IPC. Besides, the extra area overhead is negligible.
Keywords :
Data-level redundancy; Instruction-level redundancy; Narrow-width value; Sphere of replication;
Conference_Titel :
World Automation Congress (WAC), 2012
Conference_Location :
Puerto Vallarta, Mexico
Print_ISBN :
978-1-4673-4497-5