Analyzing the soft error resilience of linear solvers on multicore multiprocessors

As chip transistor densities continue to increase, soft errors (bit flips) are becoming a significant concern in networked multiprocessors with multicore nodes. Large cache structures in multicore processors are especially susceptible to soft errors as they occupy a significant portion of the chip area. In this paper, we consider the impacts of soft errors in caches on the resilience and energy efficiency of sparse linear solvers. In particular, we focus on two widely used sparse iterative solvers, namely Conjugate Gradient (CG) and Generalized Minimum Residuals (GMRES). We propose two adaptive schemes, (i) a Write Eviction Hybrid ECC (WEH-ECC) scheme for the L1 cache and (ii) a Prefetcher Based Adaptive ECC (PBA-ECC) scheme for the L2 cache, and evaluate the energy and reliability trade-offs they bring in the context of GMRES and CG solvers. Our evaluations indicate that WEH-ECC reduces the CG and GMRES soft error vulnerability by a factor of 18 to 220 in L1 cache, relative to an unprotected L1 cache, and energy consumption by 16%, relative to a cache with strong protection. The PBA-ECC scheme reduces the CG and GMRES soft error vulnerability by a factor of 9 × 103 to 8.6 × 109, relative to an unprotected L2 cache, and reduces the energy consumption by 8.5%, relative to a cache with strong ECC protection. Our energy overheads over unprotected L1 and L2 caches are 5% and 14% respectively.