Automatic Mapping of Array Operations to Specific Architectures

TY - GEN

T1 - Automatic Mapping of Array Operations to Specific Architectures

AU - Lund, Simon Andreas Frimann

AU - Kristensen, Mads Ruben Burgdorff

AU - Vinter, Brian

PY - 2017/1/27

Y1 - 2017/1/27

N2 - Array-oriented programming has been around for about thirty years and provides a fundamental abstraction for scientific computing. However, a wealth of popular programming languages in existence fail to provide convenient highlevel abstractions and exploit parallelism. One reason being that hardware is an ever-moving target.For this purpose, we introduce CAPE, a C-targeting Array Processing Engine, which manages the concerns of optimizing and parallelizing the execution of array operations. It is intended as a backend for new and existing languages and provides a portable runtime with a C-interface.The performance of the implementation is studied in relation to high-level implementations of a set of applications, kernels and synthetic benchmarks in Python/NumPy as well as lowlevel implementations in C/C++. We show the performance improvement over the high-productivity environment and how close the implementation is to handcrafted C/C++ code.

AB - Array-oriented programming has been around for about thirty years and provides a fundamental abstraction for scientific computing. However, a wealth of popular programming languages in existence fail to provide convenient highlevel abstractions and exploit parallelism. One reason being that hardware is an ever-moving target.For this purpose, we introduce CAPE, a C-targeting Array Processing Engine, which manages the concerns of optimizing and parallelizing the execution of array operations. It is intended as a backend for new and existing languages and provides a portable runtime with a C-interface.The performance of the implementation is studied in relation to high-level implementations of a set of applications, kernels and synthetic benchmarks in Python/NumPy as well as lowlevel implementations in C/C++. We show the performance improvement over the high-productivity environment and how close the implementation is to handcrafted C/C++ code.

U2 - 10.1109/WOLFHPC.2016.05

DO - 10.1109/WOLFHPC.2016.05

M3 - Article in proceedings

BT - 2016 Sixth International Workshop on Domain-Specific Languages and High-Level Frameworks for High Performance Computing

PB - IEEE

CY - Salt Lake City, USA

ER -