Abstract: Optimizing programs to run efficiently on modern parallel hardware is hard but crucial for many applications. The predominantly used imperative languages — like C or OpenCL — force the programmer to intertwine the code describing functionality and optimizations. This results in a portability nightmare that is particularly problematic given the accelerating trend towards specialized hardware devices to further increase efficiency.Many emerging DSLs used in performance demanding domains such as deep learning or high-performance image processing attempt to simplify or even fully automate the optimization process. Using a high-level — often functional — language, programmers focus on describing functionality in a declarative way. In some systems such as Halide or TVM, a separate schedule specifies how the program should be optimized. Unfortunately, these schedules are not written in well-defined programming languages. Instead, they are implemented as a set of ad-hoc predefined APIs that the compiler writers have exposed.In this talk, we show how to employ functional programming techniques to solve this challenge with elegance. We present two functional languages that work together — each addressing a separate concern. RISE is a functional language for expressing computations using well known functional data-parallel patterns. ELEVATE is a functional language for describing optimization strategies. A high-level RISE program is transformed into a low-level form using optimization strategies written in ELEVATE. From the rewritten low-level program high-performance parallel code is automatically generated. In contrast to existing high-performance domain-specific systems with scheduling APIs, in our approach programmers are not restricted to a set of built-in operations and optimizations but freely define their own computational patterns in RISE and optimization strategies in ELEVATE in a composable and reusable way. We show how our holistic functional approach achieves competitive performance with the state-of-the-art imperative systems Halide and TVM.This talk is based on the functional ICFP 2020 pearl "Achieving High-Performance the Functional Way — A Functional Pearl on Expressing High-Performance Optimizations as Rewrite Strategies" but contains additional material connecting it to new and ongoing research.
Bio: Michel Steuwer (michel.steuwer.info) is a Lecturer in Compilers and Runtime Systems at the School of Informatics at the University of Edinburgh. His research aims to drastically simplify the programming of complex parallel hardware devices while achieving unprecedented performance and efficiency. He is pioneering research into performance portable programming languages and their compilation, allowing software to be written once in a high-level language and automatically be optimized for best performance on a diverse set of hardware devices. He has authored over 40 refereed papers and his work has been widely recognized by the academic community with best paper awards and high citation number of his papers.