high performance computing on graphics processing units: hgpu.org

The current interface provided by the C++17 parallel algorithms poses some limitations with respect to parallel data access and heterogeneous systems, such as personal computers and server nodes with GPUs, smartphones, and embedded System on a Chip chipsets. In this paper, we present a summary of why we believe the Ranges TS solves these problems, and also improves both programmability and performance on heterogeneous platforms. The complete paper has been submitted to WG21 for consideration, and here we present a summary of the changes proposed alongside new performance results. To the best of our knowledge, this is the first paper presented to WG21 that unifies the Ranges TS with the parallel algorithms introduced in C++17. Although there are various points of intersection, we will focus on the composability of functions, and the benefit that this brings to accelerator devices via kernel fusion.