High Performance Dense Linear System Solver with Resilience to Multiple Soft Errors

In the multi-peta-flop era for supercomputers, the number of computing cores is growing exponentially. However, as integrated circuit technology scales below 65 nm, the critical charge required to flip a gate or a memory cell has been dangerously reduced, causing higher cosmic-radiations-induced soft error rate. Soft error threatens computing system by producing silently data corruption which is hard to detect and correct. Current research of soft errors resilience for dense linear solver offers limited capability when facing large scale computing systems, and suffers from both soft error and round-off error due to floating point arithmetic. This work proposes a fault tolerant algorithm that can recover the solution of a dense linear system Ax = b from multiple spatial and temporal soft errors. Experimental results on the Kraken Supercomputer confirm scalable performance of the proposed fault tolerance functionality and negligible overhead in solution recovery.