Using Data-Level Parallelism to Accelerate Instruction-Level Redundancy

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