The Celerity High-level API: C++20 for Accelerator Clusters

Providing convenient APIs and notations for data parallelism which remain accessible for programmers while still providing good performance has been a long-term goal of researchers as well as language and library designers. C++20 introduces ranges and views, as well as the composition of operations...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:International journal of parallel programming Jg. 50; H. 3-4; S. 341 - 359
Hauptverfasser: Thoman, Peter, Tischler, Florian, Salzmann, Philip, Fahringer, Thomas
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.08.2022
Springer Nature B.V
Schlagworte:
Clusters
Computer Science
Design
Design optimization
Distributed memory
Graphics processing units
Libraries
Processor Architectures
Software Engineering/Programming and Operating Systems
Special Issue on High-Level Parallel Programming and Applications 2021
Theory of Computation
SYCL
API design
C++20
GPU computing
Compile-time expressions
ISSN:0885-7458, 1573-7640
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Providing convenient APIs and notations for data parallelism which remain accessible for programmers while still providing good performance has been a long-term goal of researchers as well as language and library designers. C++20 introduces ranges and views, as well as the composition of operations on them using a concise syntax, but the efficient implementation of these library features is restricted to CPUs. We present the Celerity High-level API, which makes similarly concise mechanisms applicable to GPUs and accelerators, and even distributed memory clusters of GPUs. Crucially, we achieve this very high level of abstraction without a significant negative impact on performance compared to a lower-level implementation, and without introducing any non-standard toolchain components or compilers, by implementing a C++ library infrastructure on top of the Celerity system. This is made possible by two central API design and implementation strategies, which form the core of our contribution. Firstly, gathering as much information as possible at compile-time and using metaprogramming techniques to automatically fuse several distinctly formulated processing steps into a single accelerator kernel invocation. And secondly, leveraging C++20 “Concepts” in order to avoid type erasure, allowing for highly efficient code generation. We have evaluated our approach quantitatively in a comparison to lower-level manual implementations of several benchmarks, demonstrating its low overhead. Additionally, we investigated the individual performance impact of our specific optimizations and design choices, illustrating the advantages afforded by a Concepts-based approach.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0885-7458
1573-7640
DOI:10.1007/s10766-022-00731-8