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Computer Science > Programming Languages

arXiv:2505.08906 (cs)
[Submitted on 13 May 2025]

Title:Comparing Parallel Functional Array Languages: Programming and
Performance

Authors:David van Balen, Tiziano De Matteis, Clemens Grelck, Troels
Henriksen, Aaron W. Hsu, Gabriele K. Keller, Thomas Koopman, Trevor
L. McDonell, Cosmin Oancea, Sven-Bodo Scholz, Artjoms Sinkarovs, Tom
Smeding, Phil Trinder, Ivo Gabe de Wolff, Alexandros Nikolaos Ziogas
View a PDF of the paper titled Comparing Parallel Functional Array
Languages: Programming and Performance, by David van Balen and 13
other authors
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    Abstract:Parallel functional array languages are an emerging
    class of programming languages that promise to combine low-effort
    parallel programming with good performance and performance
    portability. We systematically compare the designs and
    implementations of five different functional array languages:
    Accelerate, APL, DaCe, Futhark, and SaC. We demonstrate the
    expressiveness of functional array programming by means of four
    challenging benchmarks, namely N-body simulation, MultiGrid,
    Quickhull, and Flash Attention. These benchmarks represent a
    range of application domains and parallel computational models.
    We argue that the functional array code is much shorter and more
    comprehensible than the hand-optimized baseline implementations
    because it omits architecture-specific aspects. Instead, the
    language implementations generate both multicore and GPU
    executables from a single source code base. Hence, we further
    argue that functional array code could more easily be ported to,
    and optimized for, new parallel architectures than conventional
    implementations of numerical kernels. We demonstrate this
    potential by reporting the performance of the five parallel
    functional array languages on a total of 39 instances of the four
    benchmarks on both a 32-core AMD EPYC 7313 multicore system and
    on an NVIDIA A30 GPU. We explore in-depth why each language
    performs well or not so well on each benchmark and architecture.
    We argue that the results demonstrate that mature functional
    array languages have the potential to deliver performance
    competitive with the best available conventional techniques.

Subjects: Programming Languages (cs.PL); Distributed, Parallel, and
          Cluster Computing (cs.DC); Performance (cs.PF)
Cite as:  arXiv:2505.08906 [cs.PL]
          (or arXiv:2505.08906v1 [cs.PL] for this version)
          https://doi.org/10.48550/arXiv.2505.08906
          Focus to learn more
          arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Cosmin Oancea [view email]
[v1] Tue, 13 May 2025 18:54:36 UTC (1,285 KB)
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