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Domain-Specific Code Transformations for Computational Science Based on the Polyhedral Model
Domain-Specific Code Transformations for Computational Science Based on the Polyhedral Mod...
Domain-Specific Code Transformations for Computational Science Based on the Polyhedral Model

상세정보

자료유형  
 학위논문 서양
최종처리일시  
20260209102859
ISBN  
9798291576946
DDC  
004
저자명  
Kulkarni, Kaushik G.
서명/저자  
Domain-Specific Code Transformations for Computational Science Based on the Polyhedral Model
발행사항  
[Sl] : University of Illinois at Urbana-Champaign, 2023
발행사항  
Ann Arbor : ProQuest Dissertations & Theses, 2023
형태사항  
147 p
주기사항  
Source: Dissertations Abstracts International, Volume: 87-03, Section: B.
주기사항  
Advisor: Klockner, Andreas.
학위논문주기  
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2023.
초록/해제  
요약Recent advancements in hardware design have shifted the responsibility of optimizing performance from the hardware itself to the programmer. This shift includes decisions related to caching strategies, execution grid sizes, SIMD mapping, and more. These choices significantly impact the overall performance of programs, making it increasingly difficult for general-purpose compilers to achieve roofline performance. In this thesis, we design abstractions that facilitate the integration of domain-specific transformations into the compilation pipeline. We also identify key optimization passes tailored to specific classes of programs, particularly in the field of Scientific Computing.First, this thesis proposes a transformation pipeline for efficient execution of matrix-free Finite Element Method (FEM) operators on GPUs, particularly those lowered from the Unified Form Language (UFL). The assembly kernels corresponding to different variational forms exhibit significant algorithmic variation, posing challenges in achieving roofline performance. To address these challenges, a parametric transform space combined with an auto-tuning scheme is employed. Accompanying performance evaluation using a suite of real-world applications observes that the transformed code delivers at least 50% roofline performance for 70% of the test cases. Furthermore, the portability of the transform strategy is evident across various micro-architectures, function spaces, and different Partial Differential Equations (PDEs).Then, this thesis describes a novel abstraction to record code transformations for the class of Einstein Summation ("einsum") subprograms. One of the key contributions is a grammar specification that facilitates matching the components of a high-level expression to those in an einsum. This matching can be utilized to transfer the transform knowledge regarding an einsum to a broader class of expressions. This matching is possible through a formulation of a canonical form of an einsum expression. Furthermore, experiments are conducted to compare the proposed approach against the state-of-the-art toolchains utilizing XLA / CUBLAS. The experimental results demonstrate substantial performance improvements, with reported speedups ranging from 1.7-35x for a suite of macro-kernels encountered in Discontinuous Galerkin Finite Element Method (DG-FEM) solvers.Finally, this thesis explores separating concerns in computational science frameworks via a compiler infrastructure based on the n-d array programming paradigm. A sequence of abstractions are proposed that enables the application of domain-specific transformation during the compilation of an array expression graph, both at the loop-level and the computation graph-level. The proposed abstractions are leveraged to implement a DG-FEM solver that realizes primitives as array operations and employs a domain-specific kernel fusion transformation on the array expression graphs during compilation. A comprehensive performance evaluation demonstrates that even in the context of array programming paradigms, domain-specific transformations offer substantial speedups over general-purpose compilers.
일반주제명  
Computer science
일반주제명  
Computer engineering
일반주제명  
Mathematics
키워드  
Loop transformations
키워드  
Polyhedral model
키워드  
Array programming
키워드  
Computational science
키워드  
Partial Differential Equations
기타저자  
University of Illinois at Urbana-Champaign Computer Science
기본자료저록  
Dissertations Abstracts International. 87-03B.
전자적 위치 및 접속  
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MARC

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■1001  ▼aKulkarni,  Kaushik  G.
■24510▼aDomain-Specific  Code  Transformations  for  Computational  Science  Based  on  the  Polyhedral  Model
■260    ▼a[Sl]▼bUniversity  of  Illinois  at  Urbana-Champaign▼c2023
■260  1▼aAnn  Arbor▼bProQuest  Dissertations  &  Theses▼c2023
■300    ▼a147  p
■500    ▼aSource:  Dissertations  Abstracts  International,  Volume:  87-03,  Section:  B.
■500    ▼aAdvisor:  Klockner,  Andreas.
■5021  ▼aThesis  (Ph.D.)--University  of  Illinois  at  Urbana-Champaign,  2023.
■520    ▼aRecent  advancements  in  hardware  design  have  shifted  the  responsibility  of  optimizing  performance  from  the  hardware  itself  to  the  programmer.  This  shift  includes  decisions  related  to  caching  strategies,  execution  grid  sizes,  SIMD  mapping,  and  more.  These  choices  significantly  impact  the  overall  performance  of  programs,  making  it  increasingly  difficult  for  general-purpose  compilers  to  achieve  roofline  performance.  In  this  thesis,  we  design  abstractions  that  facilitate  the  integration  of  domain-specific  transformations  into  the  compilation  pipeline.  We  also  identify  key  optimization  passes  tailored  to  specific  classes  of  programs,  particularly  in  the  field  of  Scientific  Computing.First,  this  thesis  proposes  a  transformation  pipeline  for  efficient  execution  of  matrix-free  Finite  Element  Method  (FEM)  operators  on  GPUs,  particularly  those  lowered  from  the  Unified  Form  Language  (UFL).  The  assembly  kernels  corresponding  to  different  variational  forms  exhibit  significant  algorithmic  variation,  posing  challenges  in  achieving  roofline  performance.  To  address  these  challenges,  a  parametric  transform  space  combined  with  an  auto-tuning  scheme  is  employed.  Accompanying  performance  evaluation  using  a  suite  of  real-world  applications  observes  that  the  transformed  code  delivers  at  least  50%  roofline  performance  for  70%  of  the  test  cases.  Furthermore,  the  portability  of  the  transform  strategy  is  evident  across  various  micro-architectures,  function  spaces,  and  different  Partial  Differential  Equations  (PDEs).Then,  this  thesis  describes  a  novel  abstraction  to  record  code  transformations  for  the  class  of  Einstein  Summation  ("einsum")  subprograms.  One  of  the  key  contributions  is  a  grammar  specification  that  facilitates  matching  the  components  of  a  high-level  expression  to  those  in  an  einsum.  This  matching  can  be  utilized  to  transfer  the  transform  knowledge  regarding  an  einsum  to  a  broader  class  of  expressions.  This  matching  is  possible  through  a  formulation  of  a  canonical  form  of  an  einsum  expression.  Furthermore,  experiments  are  conducted  to  compare  the  proposed  approach  against  the  state-of-the-art  toolchains  utilizing  XLA  /  CUBLAS.  The  experimental  results  demonstrate  substantial  performance  improvements,  with  reported  speedups  ranging  from  1.7-35x  for  a  suite  of  macro-kernels  encountered  in  Discontinuous  Galerkin  Finite  Element  Method  (DG-FEM)  solvers.Finally,  this  thesis  explores  separating  concerns  in  computational  science  frameworks  via  a  compiler  infrastructure  based  on  the  n-d  array  programming  paradigm.  A  sequence  of  abstractions  are  proposed  that  enables  the  application  of  domain-specific  transformation  during  the  compilation  of  an  array  expression  graph,  both  at  the  loop-level  and  the  computation  graph-level.  The  proposed  abstractions  are  leveraged  to  implement  a  DG-FEM  solver  that  realizes  primitives  as  array  operations  and  employs  a  domain-specific  kernel  fusion  transformation  on  the  array  expression  graphs  during  compilation.  A  comprehensive  performance  evaluation  demonstrates  that  even  in  the  context  of  array  programming  paradigms,  domain-specific  transformations  offer  substantial  speedups  over  general-purpose  compilers.
■590    ▼aSchool  code:  0090.
■650  4▼aComputer  science
■650  4▼aComputer  engineering
■650  4▼aMathematics
■653    ▼aLoop  transformations
■653    ▼aPolyhedral  model
■653    ▼aArray  programming
■653    ▼aComputational  science
■653    ▼aPartial  Differential  Equations
■690    ▼a0984
■690    ▼a0464
■690    ▼a0405
■71020▼aUniversity  of  Illinois  at  Urbana-Champaign▼bComputer  Science.
■7730  ▼tDissertations  Abstracts  International▼g87-03B.
■790    ▼a0090
■791    ▼aPh.D.
■792    ▼a2023
■793    ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17365940▼nKERIS▼z이  자료의  원문은  한국교육학술정보원에서  제공합니다.

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