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JuliaGPU
AMDGPU.jl
Julia2020–2022
JuliaGPU / AMDGPU.jl

AMDGPU.jl

AMD GPU (ROCm) programming in Julia

Systems & Infrastructure
Explore on GitHubRead Hacker News discussions
5Distinct people
8Mentions
0Explicit recommenders
348GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

AMD GPU (ROCm) programming in Julia

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

Mentioned in the same Hacker News threads. That is not proof they are substitutes.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 10:49:33 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month8 dated mentions

Observed mentions: 2020-09-21 21:04:33 UTC to 2022-07-06 19:21:20 UTC.

01232020-09-01 00:00:00 UTC to 2020-10-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsSep 20202020-10-01 00:00:00 UTC to 2020-11-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2020-11-01 00:00:00 UTC to 2020-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-12-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-01-01 00:00:00 UTC to 2021-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-02-01 00:00:00 UTC to 2021-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-03-01 00:00:00 UTC to 2021-04-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2021-04-01 00:00:00 UTC to 2021-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-05-01 00:00:00 UTC to 2021-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-06-01 00:00:00 UTC to 2021-07-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments2021-07-01 00:00:00 UTC to 2021-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-08-01 00:00:00 UTC to 2021-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsAug 20212021-09-01 00:00:00 UTC to 2021-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-10-01 00:00:00 UTC to 2021-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-11-01 00:00:00 UTC to 2021-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-12-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-01-01 00:00:00 UTC to 2022-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-02-01 00:00:00 UTC to 2022-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-03-01 00:00:00 UTC to 2022-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-04-01 00:00:00 UTC to 2022-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-05-01 00:00:00 UTC to 2022-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-06-01 00:00:00 UTC to 2022-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-07-01 00:00:00 UTC to 2022-08-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsJul 2022

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Sep 20202020-09-01 00:00:00 UTC2020-10-01 00:00:00 UTC101
Oct 20202020-10-01 00:00:00 UTC2020-11-01 00:00:00 UTC202
Nov 20202020-11-01 00:00:00 UTC2020-12-01 00:00:00 UTC000
Dec 20202020-12-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
Jan 20212021-01-01 00:00:00 UTC2021-02-01 00:00:00 UTC000
Feb 20212021-02-01 00:00:00 UTC2021-03-01 00:00:00 UTC000
Mar 20212021-03-01 00:00:00 UTC2021-04-01 00:00:00 UTC101
Apr 20212021-04-01 00:00:00 UTC2021-05-01 00:00:00 UTC000
May 20212021-05-01 00:00:00 UTC2021-06-01 00:00:00 UTC000
Jun 20212021-06-01 00:00:00 UTC2021-07-01 00:00:00 UTC303
Jul 20212021-07-01 00:00:00 UTC2021-08-01 00:00:00 UTC000
Aug 20212021-08-01 00:00:00 UTC2021-09-01 00:00:00 UTC000
Sep 20212021-09-01 00:00:00 UTC2021-10-01 00:00:00 UTC000
Oct 20212021-10-01 00:00:00 UTC2021-11-01 00:00:00 UTC000
Nov 20212021-11-01 00:00:00 UTC2021-12-01 00:00:00 UTC000
Dec 20212021-12-01 00:00:00 UTC2022-01-01 00:00:00 UTC000
Jan 20222022-01-01 00:00:00 UTC2022-02-01 00:00:00 UTC000
Feb 20222022-02-01 00:00:00 UTC2022-03-01 00:00:00 UTC000
Mar 20222022-03-01 00:00:00 UTC2022-04-01 00:00:00 UTC000
Apr 20222022-04-01 00:00:00 UTC2022-05-01 00:00:00 UTC000
May 20222022-05-01 00:00:00 UTC2022-06-01 00:00:00 UTC000
Jun 20222022-06-01 00:00:00 UTC2022-07-01 00:00:00 UTC000
Jul 20222022-07-01 00:00:00 UTC2022-08-01 00:00:00 UTC101

What Hacker News says

1 sources
jpsamaroo·Jul 6, 2022
This is exciting news! What's also exciting is that it's not just C++ that can run on this supercomputer; there is also good (currently unofficial) support for programming those GPUs from Julia, via the AMDGPU.jl library (note: I am the author/maintainer of this library). Some of our users have been able to run AMDGPU.jl's testsuite on the Crusher test system (which is an attached testing system with the same hardware configuration as Frontier), as well as their own domain-specific programs that use AMDGPU.jl. What's nice about programming GPUs in Julia is that you can write code once and execute it on multiple kinds of GPUs, with excellent performance. The KernelAbstractions.jl library makes this possible for compute kernels by acting as a frontend to AMDGPU.jl, CUDA.jl, and soon Metal.jl and oneAPI.jl, allowing a single piece of code to
Read the rest
be portable to AMD, NVIDIA, Intel, and Apple GPUs, and also CPUs. Similarly, the GPUArrays.jl library allows the same behavior for idiomatic array operations, and will automatically dispatch calls to BLAS, FFT, RNG, linear solver, and DNN vendor-provided libraries when appropriate. I'm personally looking forward to helping researchers get their Julia code up and running on Frontier so that we can push scientific computing to the max! Library link: <https://github.com/JuliaGPU/AMDGPU.jl>
In First true exascale supercomputer?

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