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dslsAndSearchForLinearAlgebraPerformanceOptimization

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dslsAndSearchForLinearAlgebraPerformanceOptimization

DSLs and Search for Linear Algebra PerfronianceOptimizationbyThomas NelsonB.s. University of Texas, 2007M.S. University of Colorado, 2010A thesis subm

dslsAndSearchForLinearAlgebraPerformanceOptimizationmitted to theFaculty of the Graduate School of theUniversity of Colorado in partial fulfillment of the requirements for the degree of Doctor of Philos

ophyDepartment of Computuer Science2015This thesis entitled:DSLs and Search for Linear Algebra Perfromance Optimization written by Thomas Nelsonhas be dslsAndSearchForLinearAlgebraPerformanceOptimization

en approved for the Department of Computuer ScienceProf. Elizabeth JessupProf. Jeremy SiekProf. Xiao-Chnan V.Prof. Jed BrownProf. Pavol CernyDateThe f

dslsAndSearchForLinearAlgebraPerformanceOptimization

inal copy of this thesis has l>oen examined by the signatories, and we find that both the content, and the form meet acceptable presentation standards

DSLs and Search for Linear Algebra PerfronianceOptimizationbyThomas NelsonB.s. University of Texas, 2007M.S. University of Colorado, 2010A thesis subm

dslsAndSearchForLinearAlgebraPerformanceOptimizationebra Pcrfromancc OptimizationThesis directed by Prof. Elizabeth JessupLinear algebra

scientific applications. These numerical problems have a mathematical structure that allows for complex transformations of rhe code. This thesis prese dslsAndSearchForLinearAlgebraPerformanceOptimization

nts search strategics for two Domain-Specific Languages (DSLs) focusing on high performance numerical computing domains. The first D.Sl. is Build to O

dslsAndSearchForLinearAlgebraPerformanceOptimization

rder Bl.AS (B I O), a language for matrix compulation. Scientific programmers often turn to vendor-tuned Basic Linear Algebra Subprograms (Bl.AS) to o

DSLs and Search for Linear Algebra PerfronianceOptimizationbyThomas NelsonB.s. University of Texas, 2007M.S. University of Colorado, 2010A thesis subm

dslsAndSearchForLinearAlgebraPerformanceOptimizationoptimal performance. The entire sequence needs to be optimized in concert. Instead of vendor-tuned BLAS, a programmer could start with source code in

Fortran or c mid use a state-of-the-art optimizing compiler. However, experiments in this thesis show that optimizing compilers often attain only one- dslsAndSearchForLinearAlgebraPerformanceOptimization

quarter of the performance of hand -optimized code. 1 present. a scalable search algorithm for BTO that reliably achieves high performance by choosing

dslsAndSearchForLinearAlgebraPerformanceOptimization

the best, combination of loop fusion, array contraction, ami multithreading for data parallelism.The second DSL is t he Optimizing Compiler with Tens

DSLs and Search for Linear Algebra PerfronianceOptimizationbyThomas NelsonB.s. University of Texas, 2007M.S. University of Colorado, 2010A thesis subm

dslsAndSearchForLinearAlgebraPerformanceOptimizationreuse. The best-performing implementation is heavily dependent on the tensor dimensionality and the target architecture. This optimization problem is

especially challenging when the computation requires many iterations with tensors of small dimensions. I created a high level search representation an dslsAndSearchForLinearAlgebraPerformanceOptimization

d input language as part of a tookhain to solve these problems. In this thesis. OCTOPI maps such tensor computations to GPUs, starting with a high lev

dslsAndSearchForLinearAlgebraPerformanceOptimization

el tensor input language and producing efficient CUD A code as output. This approach combines tensor-specific mathematical transformations with a GPU

DSLs and Search for Linear Algebra PerfronianceOptimizationbyThomas NelsonB.s. University of Texas, 2007M.S. University of Colorado, 2010A thesis subm

dslsAndSearchForLinearAlgebraPerformanceOptimizationode, and a comparison with OpenACC shows the importance of autotuning and otheroptimizations for achieving efficient results.DedicationTo Katie. Thank

yon for sharing this adventure with me.VAcknowledgementsFirst I want to thank Katie, for canying me through graduate school with her love and support dslsAndSearchForLinearAlgebraPerformanceOptimization

. She kept me on task, helped every way she knew how, and kept me smiling. I also want to thank my parents for encouraging me throughout school, my br

dslsAndSearchForLinearAlgebraPerformanceOptimization

other Joe for listening to me ramble on about programming and the meaning of life, ami my whole family for believing that 1 could do this.1 want to th

DSLs and Search for Linear Algebra PerfronianceOptimizationbyThomas NelsonB.s. University of Texas, 2007M.S. University of Colorado, 2010A thesis subm

dslsAndSearchForLinearAlgebraPerformanceOptimization. Paul Hovland, Prasanna Balaprakesh, and Mary Hall, for teaching me how to do research and giving valuable feedlMwk and insight throughout the PhD pr

ocess. Thank yon to Xiao-Chuan Cai, Jed Brown, ami Pavol Cerny, forlaiingon my thesis committee and reading this document. dslsAndSearchForLinearAlgebraPerformanceOptimization

DSLs and Search for Linear Algebra PerfronianceOptimizationbyThomas NelsonB.s. University of Texas, 2007M.S. University of Colorado, 2010A thesis subm

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