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Specx: a C++ task-based runtime system for heterogeneous distributed architectures.

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Title: Specx: a C++ task-based runtime system for heterogeneous distributed architectures.
Authors: Cardosi, Paul, Bramas, Bérenger
Source: PeerJ Computer Science; Jul2025, p1-34, 34p
Subject Terms: HETEROGENEOUS distributed computing, HIGH performance computing, CENTRAL processing units, PARALLEL algorithms, C++, DISTRIBUTED computing, GRAPHICS processing units, PARALLEL programming
Abstract: Parallelization is needed everywhere, from laptops and mobile phones to supercomputers. Among parallel programming models, task-based programming has demonstrated a powerful potential and is widely used in high-performance scientific computing. Not only does it allow efficient parallelization across distributed heterogeneous computing nodes, but it also allows for elegant source code structuring by describing hardware-independent algorithms. In this article, we present Specx, a task-based runtime system written in modern C++. Specx supports distributed heterogeneous computing by simultaneously exploiting central processing units (CPUs) and graphics processing units (GPUs) (CUDA/HIP) and incorporating communication into the task graph. We describe the specificities of Specx and demonstrate its potential by running parallel applications. [ABSTRACT FROM AUTHOR]
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Database: Complementary Index
Description
Abstract:Parallelization is needed everywhere, from laptops and mobile phones to supercomputers. Among parallel programming models, task-based programming has demonstrated a powerful potential and is widely used in high-performance scientific computing. Not only does it allow efficient parallelization across distributed heterogeneous computing nodes, but it also allows for elegant source code structuring by describing hardware-independent algorithms. In this article, we present Specx, a task-based runtime system written in modern C++. Specx supports distributed heterogeneous computing by simultaneously exploiting central processing units (CPUs) and graphics processing units (GPUs) (CUDA/HIP) and incorporating communication into the task graph. We describe the specificities of Specx and demonstrate its potential by running parallel applications. [ABSTRACT FROM AUTHOR]
ISSN:23765992
DOI:10.7717/peerj-cs.2966