high performance computing on graphics processing units: hgpu.org

Bit-reproducibility has many advantages in the context of high-performance computing. Besides simplifying and making more accurate the process of debugging and testing the code, it can allow the deploying of applications on heterogeneous systems, maintaining the consistency of the computations. In this work we analyze the basic operations performed by scientific applications and identify the possible sources of non-reproducibility. In particular, we consider the tasks of evaluating transcendental functions and performing non-associative reductions. We present a set of techniques to solve the problem of non-reproducibility and we propose improvements over existing algorithms to perform reproducible computations in a portable way, at the same time obtaining good performance and accuracy. By applying this techniques to more complex tasks we show that bit-reproducibility can be achieved on a broad range of scientific applications.