Towards Optimized Vector Instructions for High-Performance Functional Programming

Simple item page
dc.contributor.advisorNorris, Boyana
dc.contributor.authorAkter, Mamtaj
dc.date.accessioned2020-09-24T17:22:16Z
dc.date.available2020-09-24T17:22:16Z
dc.date.issued2020-09-24
dc.description.abstractThe Basic Linear Algebra Subprograms or BLAS provide the foundation for much of the software used in scientific computing. To date, BLAS has been implemented in C, Fortran, and directly in assembly. These languages allow the implementations to be well optimized by hand ensuring when a BLAS routine is called that it is as fast a possible. Functional programming languages, and in particular Haskell, do not allow the fine-grained control over memory, and their high-level features make it hard to optimize a single function to the level of C or assembly. However, Haskell has an advantage when optimizing combinations of container-based operations. Because of this we explore both implementing BLAS in Haskell and comparing the Glasgow Haskell Compiler’s ability to optimize scientific programs to that of a C compiler.en_US
dc.identifier.urihttps://hdl.handle.net/1794/25681
dc.language.isoen_US
dc.publisherUniversity of Oregon
dc.rightsAll Rights Reserved.
dc.subjectBasic Linear Algebra Subprogramsen_US
dc.subjectFunctional Programmingen_US
dc.subjectHigh-Performance Computingen_US
dc.subjectOptimizationen_US
dc.subjectScientific Computingen_US
dc.subjectVector Instructionsen_US
dc.titleTowards Optimized Vector Instructions for High-Performance Functional Programming
dc.typeElectronic Thesis or Dissertation
thesis.degree.disciplineDepartment of Computer and Information Science
thesis.degree.grantorUniversity of Oregon
thesis.degree.levelmasters
thesis.degree.nameM.S.

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Akter_oregon_0171N_12819.pdf
Size:
562.39 KB
Format:
Adobe Portable Document Format
Download

Collections

Theses and Dissertations
Computer Science Theses and Dissertations