COMPASS Talk by Martin Burtscher (Texas State University): Automatic Hierarchical Parallelization of Linear Recurrences

COMPASS: Computing Platforms Seminar Series

CAB E 72 

Friday, 6 July 2018, 15:00-16:00

Speaker: Martin Burtscher (Texas State University) 

Title: Automatic Hierarchical Parallelization of Linear Recurrences

Abstract:

Many important computations from various fields are instances of linear recurrences. Prominent examples include prefix sums in parallel processing and recursive filters in digital signal processing. Later result values depend on earlier result values in recurrences, making it a challenge to compute them in parallel. We present a brand-new work-, space-, and communication-efficient algorithm to compute linear recurrences that is based on Fibonacci numbers, amenable to automatic parallelization, and suitable for GPUs. We implemented our approach in a small compiler that translates recurrences expressed in signature notation into CUDA code. Moreover, we discuss the domain-specific optimizations performed by our compiler to produce state-of-the-art implementations of linear recurrences. Compared to the fastest prior GPU codes, all of which only support certain types of recurrences, our automatically parallelized code performs on par or better in most cases. In fact, for standard prefix sums and single-stage IIR filters, it reaches the throughput of memory copy for large inputs, which cannot be surpassed. On higher-order prefix sums, it performs nearly as well as the fastest handwritten code. On tuple-based prefix sums and 1D recursive filters, it outperforms the fastest preexisting implementations.

Shirt Bio:

Martin Burtscher is a Professor in the Department of Computer Science at Texas State University. He received the BS/MS degree from ETH Zurich and the PhD degree from the University of Colorado at Boulder. Martin's current research focuses on parallelization of complex programs for GPUs as well as on automatic synthesis of data-compression algorithms. He has co-authored over 100 peer-reviewed scientific publications. Martin is a distinguished member of the ACM and a senior member of the IEEE.