An Efficient and Experimentally Tuned Software-Based Hardening Strategy for Matrix Multiplication on GPUs
Paolo Rech, Camile Maria Cunha Aguiar, Christopher D. Frost, Luigi Carro · IEEE Transactions on Nuclear Science · 2013
Neutron radiation experiment results on matrix multiplication on graphic processing units (GPUs) show that multiple errors are detected at the output in more than 50% of the cases. In the presence of multiple errors, the available hardening strategies may become ineffective or inefficient. Analyzing radiation-induced error distributions, we developed an optimized and experimentally tuned software-based hardening strategy for GPUs. With fault-injection simulations, we compare the performance and correcting capabilities of the proposed technique with the available ones.