Exploiting Vector Instructions with Generalized Stream Fusion.
Ideally, a program written as a composition of concise, self-contained components should perform as well as the equivalent hand-written version where the functionality of what was many components has been manually combined into a monolithic implementation. That is, programmers should not have to sac...
| Publicado en: | Communications of the ACM Vol. 60; no. 5; pp. 83 - 92 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Association for Computing Machinery
May2017
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=122701128&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 122701128 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00010782 ACM jtl: Communications of the ACM issn: 00010782 maglogo: N pubinfo: dt: May2017 vid: 60 iid: 5 pid: 68 pub: Association for Computing Machinery artinfo: ui: 122701128 10.1145/3060597 ppf: 83 ppct: 9 formats: tig: atl: Exploiting Vector Instructions with Generalized Stream Fusion. aug: au: Mainland, Geoffrey Leshchinskiy, Roman Peyton Jones, Simon affil: Department of Computer Science, Drexel University, Philadelphia, PA Microsoft Research Ltd Cambridge, England su: Haskell (Computer program language) Computer programming Array processing Unicode (Computer character set) Vector processing (Computer science) SIMD (Computer architecture) sug: subj: Haskell (Computer program language) Computer programming Array processing Unicode (Computer character set) Vector processing (Computer science) SIMD (Computer architecture) ab: Ideally, a program written as a composition of concise, self-contained components should perform as well as the equivalent hand-written version where the functionality of what was many components has been manually combined into a monolithic implementation. That is, programmers should not have to sacrifice code clarity or good software engineering practices to obtain performance--we want compositionality without a performance penalty. This work shows how to attain this goal for high-level Haskell in the domain of sequence-processing functions, which includes applications such as array processing. Prior work on stream fusion3 shows how to automatically transform some high-level sequence-processing functions into efficient implementations. It has been used to great effect in Haskell libraries for manipulating byte arrays, Unicode text, and unboxed vectors. However some operations, like vector append, do not perform well within the stream fusion framework. Others, like SIMD computation using the SSE and AVX instructions available on modern x86 chips, do not seem to fit in the stream fusion framework at all. We describe generalized stream fusion, which solves these issues through a careful choice of stream representation. Benchmarks show that high-level Haskell code written using our compiler and libraries can produce code that is faster than both compiler- and hand-vectorized C. pubtype: Periodical doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2017 holdings: @attributes: islocal: N |
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