ArrayFire VS HPX

Compare ArrayFire vs HPX and see what are their differences.


The C++ Standard Library for Parallelism and Concurrency (by STEllAR-GROUP)
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ArrayFire HPX
6 15
4,280 2,303
0.9% 0.9%
0.0 9.8
about 1 month ago 4 days ago
C++ C++
BSD 3-clause "New" or "Revised" License Boost Software License 1.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.


Posts with mentions or reviews of ArrayFire. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-27.
  • Learn WebGPU
    9 projects | | 27 Apr 2023
    Loads of people have stated why easy GPU interfaces are difficult to create, but we solve many difficult things all the time.

    Ultimately I think CPUs are just satisfactory for the vast vast majority of workloads. Servers rarely come with any GPUs to speak of. The ecosystem around GPUs is unattractive. CPUs have SIMD instructions that can help. There are so many reasons not to use GPUs. By the time anyone seriously considers using GPUs they're, in my imagination, typically seriously starved for performance, and looking to control as much of the execution details as possible. GPU programmers don't want an automagic solution.

    So I think the demand for easy GPU interfaces is just very weak, and therefore no effort has taken off. The amount of work needed to make it as easy to use as CPUs is massive, and the only reason anyone would even attempt to take this on is to lock you in to expensive hardware (see CUDA).

    For a practical suggestion, have you taken a look at ? It can run on both CUDA and OpenCL, and it has C++, Rust and Python bindings.

  • [D] Deep Learning Framework for C++.
    7 projects | /r/MachineLearning | 12 Jun 2022
    Low-overhead — not our goal, but Flashlight is on par with or outperforming most other ML/DL frameworks with its ArrayFire reference tensor implementation, especially on nonstandard setups where framework overhead matters
  • [D] Neural Networks using a generic GPU framework
    2 projects | /r/MachineLearning | 4 Jan 2022
    Looking for frameworks with Julia + OpenCL I found array fire. It seems quite good, bonus points for rust bindings. I will keep looking for more, Julia completely fell off my radar.


Posts with mentions or reviews of HPX. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-07.

What are some alternatives?

When comparing ArrayFire and HPX you can also consider the following projects:

Thrust - [ARCHIVED] The C++ parallel algorithms library. See

Boost.Compute - A C++ GPU Computing Library for OpenCL

Taskflow - A General-purpose Parallel and Heterogeneous Task Programming System

VexCL - VexCL is a C++ vector expression template library for OpenCL/CUDA/OpenMP


Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration

RaftLib - The RaftLib C++ library, streaming/dataflow concurrency via C++ iostream-like operators

moderngpu - Patterns and behaviors for GPU computing

libcds - A C++ library of Concurrent Data Structures