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diku-dk
futhark
Haskell2017–2025
diku-dk / futhark

futhark

:boom::computer::boom: A data-parallel functional programming language

6Distinct people
7Mentions
0Explicit recommenders
2.8KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

:boom::computer::boom: A data-parallel functional programming language

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

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 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 year7 dated mentions

Observed mentions: 2017-09-26 21:10:13 UTC to 2025-07-10 07:05:32 UTC.

01232017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20172018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-01-01 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 2022-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20212022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025

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
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC101
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC000
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC000
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC101
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC101
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC303
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC000
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC101

What Hacker News says

7 sources
This is both a comprehensive guide, and an excellent reference! I use it often when writing SML for side projects. For those interested in parallel, functional programming, I recommend taking a look at Futhark, which leverages data parallelism to make very fast parallel programs. It is based on SML, and has similar syntax, but can automatically build programs that (among other targets) run on the GPU using CUDA or OpenCL. It is also worth checking out MPL, which extends the (already awesome) whole-program optimizing compiler MLton to add support for nested, fork-join parallelism. https://github.com/diku-dk/futhark https://github.com/MPLLang/mpl
In Programming in Standard ML (2011) [pdf]
I cannot overstate the importance of using a programming language targeting GPUs directly like Futhark (https://github.com/diku-dk/futhark). In this case, it is a functional, declarative language where you can focus on the why, not the how. Just like CPUs are incredibly complex, higher level abstractions are very important. If you were a pro GPU programmer and had 10 years, Futhark would be maybe 10x slower. But just like we do not program in assembly when making critically fast software, most non-simple things are easier written in this.
In Generic GPU Kernels

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