Multi-Stage Programming for GPUs in Modern C++ using PACXX

Writing and optimizing programs for high performance on systems with GPUs remains a challenging task even for expert programmers. One promising optimization technique is to evaluate parts of the program upfront on the CPU and embed the computed results in the GPU code allowing for more aggressive compiler optimizations. This technique is known as multi-stage programming and has proven to allow for significant performance benefits. Unfortunately, to achieve such optimizations in current GPU programming models like OpenCL, programmers are forced to manipulate the GPU source code as plain strings, which is error-prone and type-unsafe. In this paper we describe PACXX a GPU programming approach using modern C++ standards, with the convenient features like type deduction, lambda expressions, and algorithms from the standard template library (STL). Using PACXX, a GPU program is written as a single C++ program, rather than two distinct host and kernel programs. We extend PACXX with an easy-to-use and typesafe API for multi-stage programming avoiding the pitfalls of string manipulation. Using just-in-time compilation techniques, PACXX generates efficient GPU code at runtime. Our evaluation shows that using PACXX allows for writing multi-stage code easier and safer than currently possible. Using two detailed application studies we show that multi-stage programming can significantly outperform equivalent non-staged programs. Furthermore, we show that PACXX generates code with performance comparable to industrial-strength OpenCL compilers.