Ebook: An Object-Oriented Interface to The Sparse Polyhedral Library
- Genre: Computers // Programming: Compilers
- Year: 2021
- Publisher: IEEE
- City: Madrid
- Language: English
- pdf
Published in Proceedings of 2021 IEEE 45th Annual Computers, Software, and Applications Conference.
Abstract:
Many important applications including machine learning, molecular dynamics, and computational fluid dynamics, use sparse data. Processing sparse data leads to non-affine loop bounds and frustrates the use of the polyhedral model for code transformation. The Sparse Polyhedral Framework (SPF) addresses limitations of the Polyhedral model by supporting non-affine constraints in sets and relations using uninterpreted functions. This work contributes an object-oriented API that wraps the SPF intermediate representation (IR) and integrates the Inspector/Executor Generation Library and Omega+ for precise set and relation manipulation and code generation. The result is a well-specified definition of a full computation using the SPF IR. The API provides a single entry point for tools to interact with the SPF, generate and manipulate polyhedral data flow graphs, and transform sparse applications.
Abstract:
Many important applications including machine learning, molecular dynamics, and computational fluid dynamics, use sparse data. Processing sparse data leads to non-affine loop bounds and frustrates the use of the polyhedral model for code transformation. The Sparse Polyhedral Framework (SPF) addresses limitations of the Polyhedral model by supporting non-affine constraints in sets and relations using uninterpreted functions. This work contributes an object-oriented API that wraps the SPF intermediate representation (IR) and integrates the Inspector/Executor Generation Library and Omega+ for precise set and relation manipulation and code generation. The result is a well-specified definition of a full computation using the SPF IR. The API provides a single entry point for tools to interact with the SPF, generate and manipulate polyhedral data flow graphs, and transform sparse applications.
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