Domain-Specific Language Abstractions for Compression

Little attention has been given to language support for block-based compression algorithms, despite their high implementation complexity. Current implementations have to deal with both the intricacies of the algorithm itself, as well as the low-level optimizations necessary for generating fast code....

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Published in:DCC (Los Alamitos, Calif.) p. 364
Main Authors: Ray, Jessica, Brahmakshatriya, Ajav, Wang, Richard, Kamil, Shoaib, Reuther, Albert, Sze, Vivienne, Amarasinghe, Saman
Format: Conference Proceeding
Language:English
Published: IEEE 01.03.2021
Subjects:
Complexity theory
Compression algorithms
Data compression
High level languages
Optimization
Optimizing compilers
Partitioning algorithms
ISSN:2375-0359
Online Access:Get full text
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Abstract Little attention has been given to language support for block-based compression algorithms, despite their high implementation complexity. Current implementations have to deal with both the intricacies of the algorithm itself, as well as the low-level optimizations necessary for generating fast code. However, many block-based compression algorithms share a common structure in terms of their data representations, data partitioning operations, and data traversals. In this work, we propose a set of high-level language abstractions that can succinctly capture this structure. These abstractions provide the building blocks for the development of a domain-specific language and an associated optimizing compiler. With compression-specific language support, researchers can focus on algorithm development rather than the low-level implementation details.
AbstractList Little attention has been given to language support for block-based compression algorithms, despite their high implementation complexity. Current implementations have to deal with both the intricacies of the algorithm itself, as well as the low-level optimizations necessary for generating fast code. However, many block-based compression algorithms share a common structure in terms of their data representations, data partitioning operations, and data traversals. In this work, we propose a set of high-level language abstractions that can succinctly capture this structure. These abstractions provide the building blocks for the development of a domain-specific language and an associated optimizing compiler. With compression-specific language support, researchers can focus on algorithm development rather than the low-level implementation details.
Author Ray, Jessica
Wang, Richard
Amarasinghe, Saman
Kamil, Shoaib
Sze, Vivienne
Reuther, Albert
Brahmakshatriya, Ajav
Author_xml – sequence: 1
  givenname: Jessica
  surname: Ray
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  organization: MIT CSAIL
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  givenname: Ajav
  surname: Brahmakshatriya
  fullname: Brahmakshatriya, Ajav
  email: ajaybr@mit.edu
  organization: MIT CSAIL
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  givenname: Richard
  surname: Wang
  fullname: Wang, Richard
  email: rwang99@mit.edu
  organization: MIT CSAIL
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  givenname: Shoaib
  surname: Kamil
  fullname: Kamil, Shoaib
  email: kamil@adobe.com
  organization: Adobe Research
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  givenname: Albert
  surname: Reuther
  fullname: Reuther, Albert
  email: reuther@ll.mit.edu
  organization: MIT Lincoln Laboratory
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  givenname: Vivienne
  surname: Sze
  fullname: Sze, Vivienne
  email: sze@mit.edu
  organization: MIT CSAIL
– sequence: 7
  givenname: Saman
  surname: Amarasinghe
  fullname: Amarasinghe, Saman
  email: samana@mit.edu
  organization: MIT CSAIL
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Snippet Little attention has been given to language support for block-based compression algorithms, despite their high implementation complexity. Current...
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StartPage 364
SubjectTerms Complexity theory
Compression algorithms
Data compression
High level languages
Optimization
Optimizing compilers
Partitioning algorithms
Title Domain-Specific Language Abstractions for Compression
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