TornadoVM
HVM
TornadoVM | HVM | |
---|---|---|
22 | 107 | |
1,120 | 7,168 | |
1.4% | 2.4% | |
9.9 | 6.7 | |
about 23 hours ago | 2 months ago | |
Java | Rust | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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.
TornadoVM
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Intel Gaudi 3 AI Accelerator
You don't need to use C++ to interface with CUDA or even write it.
A while ago NVIDIA and the GraalVM team demoed grCUDA which makes it easy to share memory with CUDA kernels and invoke them from any managed language that runs on GraalVM (which includes JIT compiled Python). Because it's integrated with the compiler the invocation overhead is low:
https://developer.nvidia.com/blog/grcuda-a-polyglot-language...
And TornadoVM lets you write kernels in JVM langs that are compiled through to CUDA:
https://www.tornadovm.org
There are similar technologies for other languages/runtimes too. So I don't think that will cause NVIDIA to lose ground.
- Java VectorAPI compatiblity with TornadoVM GPU programming framework
- Java GPU pre/post processing with ONNX RT and TornadoVM
- FLaNK Stack 05 Feb 2024
- FLaNK 25 December 2023
- GPU Acceleration for Python, JavaScript, Ruby from Java with Truffle
- TornadoVM v1.0 Released
- TornadoVM 1.0
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From CPU to GPU and FPGAs: Supercharging Java Applications with TornadoVM [video]
Presented by Juan Fumero, PhD & Research Fellow (The University of Manchester, UK) during the JVM Language Summit 2023 (Santa Clara CA).
More information on TornadoVM can be found at https://www.tornadovm.org/
Tags: #Java #JVMLS #GPU #FPGA #OpenJDK #GraalVM #AI
HVM
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SaberVM
Reminds me of HVM[0]
[0]https://github.com/HigherOrderCO/HVM
Really interesting to see how new lang concepts and refinements keep popping up this last decade, between Vale, Gleam, Hylo, Austral...
Linear types really opened up lots of ways to improve memory management and compilation improvements.
- GPU Survival Toolkit for the AI age: The bare minimum every developer must know
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A new F# compiler feature: graph-based type-checking
I have a tangential question that is related to this cool new feature.
Warning: the question I ask comes from a part of my brain that is currently melted due to heavy thinking.
Context: I write a fair amount of Clojure, and in Lisps the code itself is a tree. Just like this F# parallel graph type-checker. In Lisps, one would use Macros to perform compile-time computation to accomplish something like this, I think.
More context: Idris2 allows for first class type-driven development, where the types are passed around and used to formally specify program behavior, even down to the value of a particular definition.
Given that this F# feature enables parallel analysis, wouldn't it make sense to do all of our development in a Lisp-like Trie structure where the types are simply part of the program itself, like in Idris2?
Also related, is this similar to how HVM works with their "Interaction nets"?
https://github.com/HigherOrderCO/HVM
https://www.idris-lang.org/
https://clojure.org/
I'm afraid I don't even understand what the difference between code, data, and types are anymore... it used to make sense, but these new languages have dissolved those boundaries in my mind, and I am not sure how to build it back up again.
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A History of Functional Hardware
Impressive presentation but I find two things missing in particular:
* GRIN [1] - arguably a breakthrough in FP compilation; there are several implementation based on this
* HVM [2] - parallel optimal reduction. The results are very impressive.
[1] https://link.springer.com/chapter/10.1007/3-540-63237-9_19
[2] https://github.com/HigherOrderCO/HVM
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Is the abstraction of lazy-functional-purity doomed to leak?
Purity has nothing to do with memoization. Haskell's semantics never "rewrite under a lambda" (unlike, e.g. HVM). Calling (\_ -> e) () twice will (modulo optimizations) always perform the computation in e twice.
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Can one use lambda calculus as an IR?
The most recent exploration of this, that I'm aware of is HVM (another intermediate language / runtime), although this one is not actually based on the lambda calculus, but on the interaction calculus.
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The Rust I Wanted Had No Future
Then, actually unrelated but worth mentioning: HVM. Finally, something new on the functional front that isn't dependent types!
- The Halting Problem Is Decidable on a Set of Asymptotic Probability One (2006)
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Bachelor Thesis Topic
If you are into functional PL, how about https://github.com/HigherOrderCO/HVM? You could experiment if you could schedule that on a GPU?
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For those of you self taught,how did you cope with distractions while using a computer ?
In the interest of seeking ways of optimizing my code, I stumbled upon http://www.rntz.net/datafun/ as a means to do incremental computations of fixpoints while avoiding redundant work. And also the idea of automatic parallelism achieved by using Interaction Nets as a model of computation https://github.com/HigherOrderCO/HVM.
What are some alternatives?
Aparapi - The New Official Aparapi: a framework for executing native Java and Scala code on the GPU.
Kind - A next-gen functional language [Moved to: https://github.com/Kindelia/Kind2]
openapi4j - OpenAPI 3 parser, JSON schema and request validator.
rust-gpu - š Making Rust a first-class language and ecosystem for GPU shaders š§
GraalVMREPL - REPL (readāevalāprint loop) shell built on top of JavaFX and GraalVM stack, incorporating GraalJS, GraalPython, TruffleRuby and FastR
SICL - A fresh implementation of Common Lisp
kattlo-cli - Kattlo CLI Project
Sharp-Bilinear-Shaders - sharp bilinear shaders for RetroPie, Recalbox and Libretro for sharp pixels without pixel wobble and minimal blurring
junodb - JunoDB is PayPal's home-grown secure, consistent and highly available key-value store providing low, single digit millisecond, latency at any scale.
fslang-suggestions - The place to make suggestions, discuss and vote on F# language and core library features
jr - JR: streaming quality random data from the command line
atom - A DSL for embedded hard realtime applications.