# merrymercy/awesome-tensor-compilers

A list of awesome compiler projects and papers for tensor computation and deep learning.

Repository: https://github.com/merrymercy/awesome-tensor-compilers
Canonical: https://ross.abutalabs.com/products/awesome-tensor-compilers
License Family: other
Topics: compiler, tensor, deep-learning, machine-learning, high-performance-computing, code-generation, programming-language
Last push: 2024-10-19T14:35:00+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2267, "days_push": 683, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2773, forks 329 (observed 2026-08-28T04:07:19.107133+00:00)

## What it is
A curated awesome-list of open-source compiler projects and academic papers for tensor computation and deep learning, covering TVM, MLIR, XLA, Halide, Triton, and more. It organizes resources by topic including IR design, auto-tuning, hardware optimization, and quantization.

## Use cases
- find deep learning compiler projects
- research papers on tensor compiler IR design
- learn about auto-tuning and auto-scheduling for ML kernels
- compare open source ML compilers like TVM and XLA
- find GPU and NPU optimization papers
- get started with tensor computation compilers

## When to choose
- you need a survey of the tensor compiler landscape
- you are researching ML compiler design or auto-scheduling
- you want a starting point to discover compiler projects and papers

## When to avoid
- you need an actual compiler toolchain rather than a reference list
- you want maintained software with a license and releases rather than curated links

## Facets
- artifact type: learning-resource
- maturity: active
- function: compiler, developer-tools, documentation
- domain: machine-learning, compilers, deep-learning, awesome-lists, gpu-computing
- platform: cross-platform
- tags: awesome-list, tensor-compilers, curated-list, research-papers, code-generation

## Member repositories
- merrymercy/awesome-tensor-compilers (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:19.107133+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T08:16:36.282080+00:00, confidence not recorded.
  - readme: https://github.com/merrymercy/awesome-tensor-compilers (fetched 2026-08-28T04:07:19.107133+00:00, sha a0c631f274ff)
- Data as of 2026-08-30T08:39:29.467469+00:00.