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tensor-compiler
taco
C++2017–2023
tensor-compiler / taco
taco
The Tensor Algebra Compiler (taco) computes sparse tensor expressions on CPUs and GPUs
3Distinct people
5Mentions
0Explicit recommenders
1.4KGitHub stars
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What it is
The Tensor Algebra Compiler (taco) computes sparse tensor expressions on CPUs and GPUs
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This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 12:54:37 PM UTC.
Mentions over time
HN mentions by year5 dated mentions
Observed mentions: 2017-10-31 18:29:06 UTC to 2023-06-16 04:41:48 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| 2017 | 2017-01-01 00:00:00 UTC | 2018-01-01 00:00:00 UTC | 4 | 0 | 4 |
| 2018 | 2018-01-01 00:00:00 UTC | 2019-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2019 | 2019-01-01 00:00:00 UTC | 2020-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2020 | 2020-01-01 00:00:00 UTC | 2021-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2021 | 2021-01-01 00:00:00 UTC | 2022-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2022 | 2022-01-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 1 | 0 | 1 |
What Hacker News says
5 sourcesROrohany·Jun 16, 2023
I agree! Much of this work was done as part of the overarching TACO project (https://github.com/tensor-compiler/taco), in an attempt to distribute sparse tensor computations (https://rohany.github.io/publications/sc2022-spdistal.pdf). MLIR recently (~mid 2022) began implementing the ideas from TACO into a "sparse tensor" dialect, so perhaps some of these ideas could make it into there. I'm working with MLIR these days, and if I could re-do the project now I would probably utilize and targetb the MLIR linalg infrastructure!
In The Distributed Tensor Algebra Compiler (2022)Larry chose to focus on the big data part, because it is intuitive. But I think you're absolutely correct, that it has applications in physics/chemistry (and machine learning too). We're actually talking to people in our theoretical physics department, who may want to use taco for their QCD computations. There's also a new issue on our tracker about adding complex number support for nuclear computations and quantum computing:
https://github.com/tensor-compiler/taco/issues/116.
The tensor contraction engine is great work, and focuses on dense tensor. We currently optimize for sparse tensors so TCE will do better than us for pure dense expressions. We want to bridge this gap next semester though.
The cyclops framework is also great. We discuss it in our related work, but we did not directly compare to it in our evaluation. The first versio
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n of it, like TCE, focused on dense tensors, and their main focus is on distributed computing, which we don't support yet (we do shared memory parallel execution at the moment). They have some followup work on sparse computations. The difference to our work is that they, if I read their paper correctly, transposes the data until they can call pre-existing matrix multiplication routines. This causes data movement overheads. Our work compiles expressions to work at the data at hand, without moving it.
Hi Hacker News! I’m one of the developers. This project was also featured in MIT News yesterday:
http://news.mit.edu/2017/faster-big-data-analysis-tensor-alg...
The code is available at:
https://github.com/tensor-compiler/taco/issues
I’m happy to discuss the project and to answer any questions :)
In The Tensor Algebra CompilerThe repository is here:
https://github.com/tensor-compiler/taco
In System for performing 'tensor algebra' offers 100-fold speedupsThe github repository is here:
https://github.com/tensor-compiler/taco
In System for performing 'tensor algebra' offers 100-fold speedups