Robust Molecular Dynamics Simulations Using Coded FFT Algorithm
Yuk Wong, Yuqiu Zhang, Haewon Jeong, Pulkit Grover · 2019
As error/failure rates in supercomputers are projected to grow, computationally intensive scientific applications that lever-age large-scale parallelization will suffer from the increased error rate. In this work, we apply "coded computing" to protein folding simulations in an error-prone environment. We implemented the fast Fourier Poisson method for solving electrostatic equations at each time step of the simulation, and we utilize coded FFT algorithm to protect the compute-intensive FFT algorithm from soft errors. Through experiments on Amazon AWS, we showed that coded protein folding can be implemented with less than 10% overhead in total simulation time, and also showed that coded computing approach is faster than classical checkpointing method when the error rate is high.