Design and Implementation of an Extended Collectives Library for Unified Parallel C

• Published in: Journal of computer science and technology 2013, Vol.28 (1), p.72-89
• Main Authors: Teijeiro, Carlos, Taboada, Guillermo L., Touriño, Juan, Doallo, Ramón, Mouriño, José C., Mallón, Damián A., Wibecan, Brian
• Format: Article
• Language: English
• Subjects: Algorithms; Analysis; Artificial Intelligence; C (programming language); Computer programming; Computer Science; Data Structures and Information Theory; Distributed memory; Fourier transforms; High performance computing; Information Systems Applications (incl.Internet); Libraries; Mathematical analysis; Mathematical models; Parallel processing; Programming; Proposals; Regular Paper; Software; Software Engineering; Studies; Theory of Computation; Variables; 共享内存; 内存架构; 并行编程; 应用程序; 性能计算; 编程模型; 设计; 集体
• ISSN: 1000-9000; 1860-4749
• DOI: 10.1007/s11390-013-1313-9

Unified Parallel C （UPC） is a parallel extension of ANSI C based on the Partitioned Global Address Space （PGAS） programming model, which provides a shared memory view that simplifies code development while it can take advantage of the scalability of distributed memory architectures. Therefore, UPC allows programmers to write parallel applications on hybrid shared/distributed memory architectures, such as multi-core clusters, in a more productive way, accessing remote memory by means of different high-level language constructs, such as assignments to shared variables or collective primitives. However, the standard UPC collectives library includes a reduced set of eight basic primitives with quite limited functionality. This work presents the design and implementation of extended UPC collective functions that overcome the limitations of the standard collectives library, allowing, for example, the use of a specific source and destination thread or defining the amount of data transferred by each particular thread. This library fulfills the demands made by the UPC developers community and implements portable algorithms, independent of the specific UPC compiler/runtime being used. The use of a representative set of these extended collectives has been evaluated using two applications and four kernels as case studies. The results obtained confirm the suitability of the new library to provide easier programming without trading off performance, thus achieving high productivity in parallel programming to harness the performance of hybrid shared/distributed memory architectures in high performance computing.