Accelerator Design Language
Allo is a Python-embedded Accelerator Design Language (ADL) and compiler that facilitates the construction of large-scale, high-performance hardware accelerators in a modular and composable manner. Allo has several key features:
- Progressive hardware customizations: Allo decouples hardware customizations from algorithm specifications and treats each hardware customization as a primitive that performs a rewrite on the program. Allo not only decouples the loop-based transformations, but also extends the decoupling to memory, communication, and data types. All the transformations are built on top of MLIR that is easier to target different backends.
- Reusable parameterized kernel templates: Allo supports declaring type variables during kernel creation and instantiating the kernel when building the hardware executable, which is an important feature for building reusable hardware kernel libraries. Allo introduces a concise grammar for creating kernel templates, eliminating the need for users to possess complicated metaprogramming expertise.
- Composable schedules: Allo empowers users to construct kernels incrementally from the bottom up, adding customizations one at a time while validating the correctness of each submodule. Ultimately, multiple schedules are progressively integrated into a complete design using the
.compose()primitive. This approach, unachievable by prior top-down methods, significantly enhances productivity and debuggability.
Getting Started
Please check out the Allo documentation for installation instructions and tutorials. If you encounter any problems, please feel free to open an issue.
Publications
Please refer to our PLDI'24 paper for more details. If you use Allo in your research, please use the following bibtex entry to cite us:
@article{chen2024allo,
author = {Hongzheng Chen and Niansong Zhang and Shaojie Xiang and Zhichen Zeng and Mengjia Dai and Zhiru Zhang},
title = {Allo: A Programming Model for Composable Accelerator Design},
journal = {Proc. ACM Program. Lang.},
year = {2024},
month = {jun},
url = {https://doi.org/10.1145/3656401},
doi = {10.1145/3656401},
articleno = {171},
volume = {8},
number = {PLDI},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
issue_date = {June 2024},
}