Model, design, and explore tensor algebra accelerators.
AccelForge is a framework for modeling, designing, and exploring tensor algebra accelerators. It uses HWComponents as a backend for component cost modeling.
Learn more at the website or on GitHub.
⚡ Features
- Flexible Full-Stack Modeling of a wide variety of devices, circuits, architectures, workloads, and mappings. We integrate with HWComponents, with easily-modifiable models for component costs (area, energy, leak power, and throughput).
- Fast and optimal mapping of workloads onto architectures, yielding the best-possible performance and energy efficiency.
- Fusion-aware mapping that optimizes fusion for cascades of Einsums, enabling end-to-end optimization of entire workloads.
- Heterogenous Architectures that can include multiple types of compute units.
- Strong input validation via Pydantic, with clear error reports for invalid specifications.
- Pythonic Interfaces that enable easy automation and integration with other tools.
📦 Install
pip install accelforge
🧪 Examples
See examples/ for architectures and workloads, and notebooks/ for tutorials.
📚 Cite
If you use AccelForge in your work, please see Citing AccelForge for the relevant papers.
1 maintainer
Metadata
1 maintainer
Release files for accelforge 1.0.467
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| accelforge-1.0.467.tar.gz | 1.1 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| accelforge-1.0.467-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 2.4 MB
Release files / accelforge-1.0.467.tar.gz
| Download URL | accelforge-1.0.467.tar.gz |
|---|---|
| Size | 1.1 MB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Transparency logRelease files / accelforge-1.0.467-py3-none-any.whl
| Download URL | accelforge-1.0.467-py3-none-any.whl |
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| Size | 1.3 MB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
|
Provenance
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PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
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