accelerate
futhark
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accelerate | futhark | |
---|---|---|
9 | 52 | |
886 | 2,291 | |
0.5% | 2.2% | |
5.3 | 9.8 | |
16 days ago | 3 days ago | |
Haskell | Haskell | |
GNU General Public License v3.0 or later | ISC License |
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.
accelerate
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Should I use newer ghc?
Someone has opened a PR for accelerate here https://github.com/AccelerateHS/accelerate/pull/525 (sadly seems not actively maintained at the moment, but that can always change if people care enough). I agree for an executable you should freeze your dependencies and compiler version, and using 8.10 is fine. Although there are tons of improvements in 9.2+
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Haskell deep learning tutorials [Blog]
Backprop is a neat library. However, I guess its use case is if you actually don't want to go for anything standard like Torch or TF (perhaps for research?) For instance, if I were to use something like Accelerate for GPU acceleration, or some other computation-oriented library, then I would mix it with Backprop. Previously, I have benefited from Backprop in a ConvNet tutorial and I liked it.
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I made a petition to get the accelerate project for Haskell some funding.
Wait, really? Here's a conversation I had with him: https://github.com/AccelerateHS/accelerate/discussions/528
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Who is researching array languages these days?
I know Accelerate is being developed at Utrecht University in the Netherlands. You can look at publications by Trevor McDonell to get a taste of what they are doing.
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Next Decade in Languages: User Code on the GPU
I’m personally a big fan of http://www.acceleratehs.org / https://github.com/AccelerateHS/accelerate-llvm
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Introduction to Doctests in Haskell
Looking for a few projects that make use of it, I found accelerate, hawk, polysemy and pretty-simple, so I'll be interested to poke around in their code and see how they have things set up.
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Monthly Hask Anything (March 2022)
There's accelerate for GPU computing and hmatrix for bindings to BLAS and LAPACK.
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Idris2+WebGL, part #12: Linear algebra with linear types... not great
I'm toying with the idea of replacing vector values with vector generators, where e.g. v1 + v2 is not evaluated to a new vector, but to a vector program. This is similar to the approaches of Accelerate and TensorFlow. On the flip side, I don't think I could get rid of the overhead, and I expect much smaller computation loads than aforementioned libraries, so overheads could be very significant. The added benefit of using vector generators is that the generator could not only be evaluated, but also be turned into a Latex formula.
futhark
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What downsides exist to Futhark? Seems almost too good to be true?
Why Futhark? (futhark-lang.org)
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GPU Programming: When, Why and How?
There is no on-going work to support Metal apart from the work done by Miles. There's an old issue about it: https://github.com/diku-dk/futhark/issues/853#issuecomment-5...
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Is Parallel Programming Hard, and, If So, What Can You Do About It? v2023.06.11a
Functional programming can be a great way to handle parallel programming in a sane way. See the Futhark language [1], for example, that accepts high-level constructs like map and convert them to the appropriate machine code, either on the CPU or the GPU.
[1] https://futhark-lang.org/
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Is there a programming language that will blow my mind?
Futhark - use a functional language to program the gpu
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Does This Language Exist?
You might want to look into Futhark, although it's mainly designed for writing GPU code.
- Learn WebGPU
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Two-tier programming language
Futhark https://futhark-lang.org/
- Best book on writing an optimizing compiler (inlining, types, abstract interpretation)?
- Functional GPU programming: what are alternatives or generalizations of the idea of "number of cycles must be known at compile time"?
- APL: An Array Oriented Programming Language (2018)
What are some alternatives?
dhall - Maintainable configuration files
arrayfire-rust - Rust wrapper for ArrayFire
accelerate-bignum - Fixed-length large integer arithmetic for Accelerate
dex-lang - Research language for array processing in the Haskell/ML family
accelerate-cuda - DEPRECATED: Accelerate backend for NVIDIA GPUs
Halide - a language for fast, portable data-parallel computation
hyper-haskell-server - The strongly hyped Haskell interpreter.
julia - The Julia Programming Language
accelerate-fft - FFT library for Haskell based on the embedded array language Accelerate
BQN - An APL-like programming language. Self-hosted!
feldspar-compiler - This is the compiler for the Feldspar Language.
kompute - General purpose GPU compute framework built on Vulkan to support 1000s of cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous and optimized for advanced GPU data processing usecases. Backed by the Linux Foundation.