https://github.com/hpac/lamp_benchmark

Benchmarks that evaluate whether high-level linear algebra languages solve the Linear Algebra Mapping Problem (LAMP).
https://github.com/hpac/lamp_benchmark

high-performance-computing lamp lamp-benchmark linear-algebra

Last synced: 6 months ago
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Benchmarks that evaluate whether high-level linear algebra languages solve the Linear Algebra Mapping Problem (LAMP).

• Host: GitHub
• URL: https://github.com/hpac/lamp_benchmark
• Owner: HPAC
• License: bsd-3-clause
• Created: 2019-11-19T13:33:05.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2023-01-22T00:38:23.000Z (over 2 years ago)
• Last Synced: 2024-07-30T19:24:04.997Z (11 months ago)
• Topics: high-performance-computing, lamp, lamp-benchmark, linear-algebra
• Language: Jupyter Notebook
• Homepage:
• Size: 1.45 MB
• Stars: 5
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# LAMP Benchmark

A series of benchmarks/tests across multiple high-level linear algebra oriented languages/libraries/frameworks (henceforth referred to as just "languages")

that assess the extent to which said languages translate high-level linear algebra expressions to high-performance code.

## Setup

For instructions on how to setup the benchmarks and install all languages used (and linking to Intel MKL), please consult the [Wiki](https://github.com/ChrisPsa/LAMP_benchmark/wiki) page.

## Related Publications

* [The Linear Algebra Mapping Problem. Current state of linear algebra languages and libraries](https://dl.acm.org/doi/10.1145/3549935)

* [Benchmarking the Linear Algebra Awareness of TensorFlow and PyTorch](https://ieeexplore.ieee.org/document/9835658)