Keywords: SYCL, Domain-Specific Languages, Abstract Syntax Trees
TL;DR: The paper proposes an approach that translates domain-specific languages into abstract syntax trees and subsequently compiles them into SYCL.
Abstract: The escalating demand for computing resources, particularly in the realm of ar- 6
tificial intelligence (AI), necessitates efficient utilization of heterogeneous parallel 7
systems. This study focuses on compiling domain-specific languages, specifically 8
data-centric computation models, into SYCL for heterogeneous many-core systems. 9
SYCL, based on C++17, offers a unified programming model for various hardware 10
accelerators, promoting code reusability across different architectures. Leveraging 11
SYCL’s cross-hardware compatibility and performance optimization capabilities, 12
this project aims to enhance programming efficiency and performance on diverse 13
hardware backends. Through the translation of domain-specific languages into SYCL 14
(DPC++), developers can harness the simplicity and usability of domain-specific 15
languages while achieving high-performance parallel computing. This approach ad- 16
dresses the challenges of complex programming interfaces and poor program port- 17
ability across heterogeneous systems. By enabling domain-specific languages to run 18
in parallel on heterogeneous systems, this research contributes to advancing the de- 19
velopment of heterogeneous computing systems and providing programmers with 20
more flexible and efficient programming tools. The significance of this work lies 21
in its potential to facilitate broader application scenarios and higher execution effi- 22
ciency, ultimately promoting the widespread adoption of domain-specific languages 23
and driving innovation in parallel computing.
Submission Number: 6
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