Towards Composable GPU Programming
Michael Haidl, Michel Steuwer, Hendrik Dirks, Tim Humernbrum, Sergei Petrovich Gorlatch · 2017
In this paper, we advocate a composable approach to programming systems with Graphics Processing Units (GPU): programs are developed as compositions of generic, reusable patterns. Current GPU programming approaches either rely on low-level, monolithic code without patterns (CUDA and OpenCL), which achieves high performance at the cost of cumbersome and error-prone programming, or they improve the programmability by using pattern-based abstractions (e.g., Thrust) but pay a performance penalty due to inefficient implementations of pattern composition.