Supporting extended precision on graphics processors

Scientific computing applications often require support for non-traditional data types, for example, numbers with a pre-cision higher than 64-bit floats. As graphics processors, or GPUs, have emerged as a powerful accelerator for scientific computing, we design and implement a GPU-based extended precision library to enable applications with high precision requirement to run on the GPU. Our library contains arith-metic operators, mathematical functions, and data-parallel primitives, each of which can operate at either multi-term or multi-digit precision. The multi-term precision maintains an accuracy of up to 212 bits of signifcand whereas the multi-digit precision allows an accuracy of an arbitrary number of bits. Additionally, we have integrated the extended preci-sion algorithms to a GPU-based query processing engine to support efficient query processing with extended precision on GPUs. To demonstrate the usage of our library, we have im-plemented three applications: parallel summation in climate modeling, Newton’s method used in nonlinear physics, and high precision numerical integration in experimental math-ematics. The GPU-based implementation is up to an order of magnitude faster, and achieves the same accuracy as their optimized, quadcore CPU-based counterparts. 1