Improving numerical reproducibility and stability in large-scale numerical simulations on GPUs

The advent of general purpose graphics processing units (GPGPU's) brings about a whole new platform for running numerically intensive applications at high speeds. Their multi-core architectures enable large degrees of parallelism via a massively multi-threaded environment. Molecular dynamics (MD) simulations are particularly well-suited for GPU's because their computations are easily parallelizable. Significant performance improvements are observed when single precision floating-point arithmetic is used. However, this performance comes at the cost of accuracy: it is widely acknowledged that constant-energy (NVE) MD simulations accumulate errors as the simulation proceeds due to the inherent errors associated with integrators used for propagating the coordinates. A consequence of this numerical integration is the drift of potential energy as the simulation proceeds. Double precision arithmetic partially corrects this drifting, but is significantly slower than single precision,...

• Type: Journal
• Year: 2010
• Where: IPPS
• Authors: Michela Taufer, Omar Padron, Philip Saponaro, Sandeep Patel
• Keywords: Distributed And Parallel Computing, IPPS 2010, MD Simulations, Simulations, Single Precision