Search

Your search keyword '"STROUT, MICHELLE"' showing total 211 results
Start Over Author "STROUT, MICHELLE"

Refine your results

more »

more »

more »

more »
211 results on '"STROUT, MICHELLE"'

1. Polyhedral Specification and Code Generation of Sparse Tensor Contraction with Co-Iteration

Author

Zhao, Tuowen, Popoola, Tobi, Hall, Mary, Olschanowsky, Catherine, and Strout, Michelle Mills

Subjects
Computer Science - Programming Languages, Computer Science - Performance
Abstract

This paper presents a code generator for sparse tensor contraction computations. It leverages a mathematical representation of loop nest computations in the sparse polyhedral framework (SPF), which extends the polyhedral model to support non-affine computations, such as arise in sparse tensors. SPF is extended to perform layout specification, optimization, and code generation of sparse tensor code: 1) we develop a polyhedral layout specification that decouples iteration spaces for layout and computation; and, 2) we develop efficient co-iteration of sparse tensors by combining polyhedra scanning over the layout of one sparse tensor with the synthesis of code to find corresponding elements in other tensors through an SMT solver. We compare the generated code with that produced by a state-of-the-art tensor compiler, TACO. We achieve on average 1.63$\times$ faster parallel performance than TACO on sparse-sparse co-iteration and describe how to improve that to 2.72$\times$ average speedup by switching the find algorithms. We also demonstrate that decoupling iteration spaces of layout and computation enables additional layout and computation combinations to be supported.

Published
2022

2. Composing Loop-carried Dependence with Other Loops

Author

Cheshmi, Kazem, Strout, Michelle Mills, and Dehnavi, Maryam Mehri

Subjects
Computer Science - Programming Languages
Abstract

Sparse fusion is a compile-time loop transformation and runtime scheduling implemented as a domain-specific code generator. Sparse fusion generates efficient parallel code for the combination of two sparse matrix kernels where at least one of the kernels has loop-carried dependencies. Available implementations optimize individual sparse kernels. When optimized separately, the irregular dependence patterns of sparse kernels create synchronization overheads and load imbalance, and their irregular memory access patterns result in inefficient cache usage, which reduces parallel efficiency. Sparse fusion uses a novel inspection strategy with code transformations to generate parallel fused code for sparse kernel combinations that is optimized for data locality and load balance. Code generated by Sparse fusion outperforms the existing implementations ParSy and MKL on average 1.6X and 5.1X respectively and outperforms the LBC and DAGP coarsening strategies applied to a fused data dependence graph on average 5.1X and 7.2X respectively for various kernel combinations.

Published
2021

3. Extreme Heterogeneity 2018 - Productive Computational Science in the Era of Extreme Heterogeneity: Report for DOE ASCR Workshop on Extreme Heterogeneity

Author

Vetter, Jeffrey S, Brightwell, Ron, Gokhale, Maya, McCormick, Pat, Ross, Rob, Shalf, John, Antypas, Katie, Donofrio, David, Humble, Travis, Schuman, Catherine, Van Essen, Brian, Yoo, Shinjae, Aiken, Alex, Bernholdt, David, Byna, Suren, Cameron, Kirk, Cappello, Frank, Chapman, Barbara, Chien, Andrew, Hall, Mary, Hartman-Baker, Rebecca, Lan, Zhiling, Lang, Michael, Leidel, John, Li, Sherry, Lucas, Robert, Mellor-Crummey, John, Peltz Jr., Paul, Peterka, Thomas, Strout, Michelle, and Wilke, Jeremiah

Published
2021

4. MatRox: Modular approach for improving data locality in Hierarchical (Mat)rix App(Rox)imation

Author

Liu, Bangtian, Cheshmi, Kazem, Soori, Saeed, Strout, Michelle Mills, and Dehnavi, Maryam Mehri

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

Hierarchical matrix approximations have gained significant traction in the machine learning and scientific community as they exploit available low-rank structures in kernel methods to compress the kernel matrix. The resulting compressed matrix, HMatrix, is used to reduce the computational complexity of operations such as HMatrix-matrix multiplications with tuneable accuracy in an evaluation phase. Existing implementations of HMatrix evaluations do not preserve locality and often lead to unbalanced parallel execution with high synchronization. Also, current solutions require the compression phase to re-execute if the kernel method or the required accuracy change. In this work, we describe MatRox, a framework that uses novel structure analysis strategies, blocking and coarsen, with code specialization and a storage format to improve locality and create load-balanced parallel tasks for HMatrix-matrix multiplications. Modularization of the matrix compression phase enables the reuse of computations when there are changes to the input accuracy and the kernel function. The MatRox-generated code for matrix-matrix multiplication is 2.98x, 1.60x, and 5.98x faster than library implementations available in GOFMM, SMASH, and STRUMPACK respectively. Additionally, the ability to reuse portions of the compression computation for changes to the accuracy leads to up to 2.64x improvement with MatRox over five changes to accuracy using GOFMM.

Published
2018

5. Expanding Opportunities for Array Privatization in Sparse Computations

Author

Mohammadi, Mahdi Soltan, Hall, Mary, Strout, Michelle Mills, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Chapman, Barbara, editor, and Moreira, José, editor

Published
2022
Full Text
View/download PDF

6. Sparse Matrix Code Dependence Analysis Simplification at Compile Time

Author

Mohammadi, Mahdi Soltan, Cheshmi, Kazem, Gopalakrishnan, Ganesh, Hall, Mary, Dehnavi, Maryam Mehri, Venkat, Anand, Yuki, Tomofumi, and Strout, Michelle Mills

Subjects
Computer Science - Programming Languages
Abstract

Analyzing array-based computations to determine data dependences is useful for many applications including automatic parallelization, race detection, computation and communication overlap, verification, and shape analysis. For sparse matrix codes, array data dependence analysis is made more difficult by the use of index arrays that make it possible to store only the nonzero entries of the matrix (e.g., in A[B[i]], B is an index array). Here, dependence analysis is often stymied by such indirect array accesses due to the values of the index array not being available at compile time. Consequently, many dependences cannot be proven unsatisfiable or determined until runtime. Nonetheless, index arrays in sparse matrix codes often have properties such as monotonicity of index array elements that can be exploited to reduce the amount of runtime analysis needed. In this paper, we contribute a formulation of array data dependence analysis that includes encoding index array properties as universally quantified constraints. This makes it possible to leverage existing SMT solvers to determine whether such dependences are unsatisfiable and significantly reduces the number of dependences that require runtime analysis in a set of eight sparse matrix kernels. Another contribution is an algorithm for simplifying the remaining satisfiable data dependences by discovering equalities and/or subset relationships. These simplifications are essential to make a runtime-inspection-based approach feasible.

Published
2018

7. Potential of Interpreter Specialization for Data Analysis

Author

He, Wei, Strout, Michelle Mills, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Jagode, Heike, editor, Anzt, Hartwig, editor, Ltaief, Hatem, editor, and Luszczek, Piotr, editor

Published
2021
Full Text
View/download PDF

8. Handling Nested Parallelism and Extreme Load Imbalance in an Orbital Analysis Code

Author

Gaska, Benjamin James, Jothi, Neha, Mohammadi, Mahdi Soltan, Volk, Kat, and Strout, Michelle Mills

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

Nested parallelism exists in scientific codes that are searching multi-dimensional spaces. However, implementations of nested parallelism often have overhead and load balance issues. The Orbital Analysis code we present exhibits a sparse search space, significant load imbalances, and stopping when the first solution is reached. All these aspects of the algorithm exacerbate the problem of using nested parallelism effectively. In this paper, we present an inspector/executor strategy for chunking such computations into parallel wavefronts. The presented shared memory parallelization is no longer nested and exhibits significantly less load imbalance. We evaluate this approach on an Orbital analysis code, and we improve the execution time from the original implementation by an order of magnitude. As part of a Graduate Computer Science course in Parallel Programming models, we show how the approach can be implemented in parallel Perl, Python, Chapel, Pthreads, and OpenMP. Future work includes investigating how to automate and generalize the parallelization approach., Comment: 11 pages, 14 figures

Published
2017

9. Sympiler: Transforming Sparse Matrix Codes by Decoupling Symbolic Analysis

Author

Cheshmi, Kazem, Kamil, Shoaib, Strout, Michelle Mills, and Dehnavi, Maryam Mehri

Subjects
Computer Science - Programming Languages
Abstract

Sympiler is a domain-specific code generator that optimizes sparse matrix computations by decoupling the symbolic analysis phase from the numerical manipulation stage in sparse codes. The computation patterns in sparse numerical methods are guided by the input sparsity structure and the sparse algorithm itself. In many real-world simulations, the sparsity pattern changes little or not at all. Sympiler takes advantage of these properties to symbolically analyze sparse codes at compile-time and to apply inspector-guided transformations that enable applying low-level transformations to sparse codes. As a result, the Sympiler-generated code outperforms highly-optimized matrix factorization codes from commonly-used specialized libraries, obtaining average speedups over Eigen and CHOLMOD of 3.8X and 1.5X respectively., Comment: 12 pages

Published
2017
Full Text
View/download PDF

11. Unified Sequential Optimization Directives in OpenMP

Author

Neth, Brandon, Scogland, Thomas R. W., Strout, Michelle Mills, de Supinski, Bronis R., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Milfeld, Kent, editor, de Supinski, Bronis R., editor, Koesterke, Lars, editor, and Klinkenberg, Jannis, editor

Published
2020
Full Text
View/download PDF

12. Language-Agnostic Optimization and Parallelization for Interpreted Languages

Author

Strout, Michelle Mills, Debray, Saumya, Isaacs, Kate, Kreaseck, Barbara, Cárdenas-Rodríguez, Julio, Hurwitz, Bonnie, Volk, Kat, Badger, Sam, Bartels, Jesse, Bertolacci, Ian, Devkota, Sabin, Encinas, Anthony, Gaska, Ben, Neth, Brandon, Sackos, Theo, Stephens, Jon, Willer, Sarah, Yadegari, Babak, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, and Rauchwerger, Lawrence, editor

Published
2019
Full Text
View/download PDF

13. Extending Index-Array Properties for Data Dependence Analysis

Author

Mohammadi, Mahdi Soltan, Cheshmi, Kazem, Dehnavi, Maryam Mehri, Venkat, Anand, Yuki, Tomofumi, Strout, Michelle Mills, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Hall, Mary, editor, and Sundar, Hari, editor

Published
2019
Full Text
View/download PDF

15. The Chemistry Between High School Students and Computer Science

Author

Lenczycki, Timothy T., Suto, Kelly, Williams, Christina, and Strout, Michelle Mills

Subjects
Computer Science - Computers and Society, K.3.2
Abstract

Computer science enrollments have started to rise again, but the percentage of women undergraduates in computer science is still low. Some studies indicate this might be due to a lack of awareness of computer science at the high school level. We present our experiences running a 5-year, high school outreach program that introduces information about computer science within the context of required chemistry courses. We developed interactive worksheets using Molecular Workbench that help the students learn chemistry and computer science concepts related to relevant events such as the gulf oil spill. Our evaluation of the effectiveness of this approach indicates that the students do become more aware of computer science as a discipline, but system support issues in the classroom can make the approach difficult for teachers and discouraging for the students., Comment: 8 pages, 2 figures

Published
2014

16. Extending OpenMP to Facilitate Loop Optimization

Author

Bertolacci, Ian, Strout, Michelle Mills, de Supinski, Bronis R., Scogland, Thomas R. W., Davis, Eddie C., Olschanowsky, Catherine, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, de Supinski, Bronis R., editor, Valero-Lara, Pedro, editor, Martorell, Xavier, editor, Mateo Bellido, Sergi, editor, and Labarta, Jesus, editor

Published
2018
Full Text
View/download PDF

18. Analyzing Parallel Programming Models for Magnetic Resonance Imaging

Author

Danford, Forest, Welch, Eric, Cárdenas-Ródriguez, Julio, Strout, Michelle Mills, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Ding, Chen, editor, Criswell, John, editor, and Wu, Peng, editor

Published
2017
Full Text
View/download PDF

19. Language-Agnostic Optimization and Parallelization for Interpreted Languages

Author

Strout, Michelle Mills, primary, Debray, Saumya, additional, Isaacs, Kate, additional, Kreaseck, Barbara, additional, Cárdenas-Rodríguez, Julio, additional, Hurwitz, Bonnie, additional, Volk, Kat, additional, Badger, Sam, additional, Bartels, Jesse, additional, Bertolacci, Ian, additional, Devkota, Sabin, additional, Encinas, Anthony, additional, Gaska, Ben, additional, Neth, Brandon, additional, Sackos, Theo, additional, Stephens, Jon, additional, Willer, Sarah, additional, and Yadegari, Babak, additional

Published
2019
Full Text
View/download PDF

21. An Approach for Proving the Correctness of Inspector/Executor Transformations

Author

Norrish, Michael, Strout, Michelle Mills, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Brodman, James, editor, and Tu, Peng, editor

Published
2015
Full Text
View/download PDF

22. Proof of Correctness for Sparse Tiling of Gauss-Seidel

Author

Strout, Michelle Mills, Carter, Larry, and Ferrante, Jeanne

Abstract

Gauss-Seidel is an iterative computation used for solving a set ofsimultaneous linear equations, $A\vec{u}=\vec{f}$. If the matrix $A$ uses asparse matrix representation, storing only nonzeros, then the data dependencesin the computation arise from $A$'s nonzero structure. We use this structure toschedule the computation at runtime using a technique called full sparsetiling. The sparse tiled computation exhibits better data locality andtherefore improved performance. This paper gives a complete proof that a serialschedule for full sparse tiled Gauss-Seidel generates results equivalent tothose that a typical Gauss-Seidel computation produces. We also provideimplementation and correctness details for full sparse tiling with reducedworst-case complexity.Pre-2018 CSE ID: CS2003-0741

Published
2003

25. Proof of Correctness for Sparse Tiling of Gauss-Seidel

Author

Strout, Michelle Mills, Carter, Larry, and Ferrante, Jeanne

Abstract

Gauss-Seidel is an iterative computation used for solving sets ofsimulataneous linear equations, $Au=f$. When these unknowns are associated withnodes in an irregular mesh, then the Gauss-Seidel computation structure isrelated to the mesh structure. We use this structure to subdivide thecomputation at runtime using a technique called {\em sparse tiling}. Therescheduled computation exhibits better data locality and therefore improvedperformance. This paper gives a complete proof that a serial schedule based onsparse tiling generates results equivalent to those that a standardGauss-Seidel computation produces.Pre-2018 CSE ID: CS2001-0690

Published
2001

29. Set and Relation Manipulation for the Sparse Polyhedral Framework

Author

Strout, Michelle Mills, Georg, Geri, Olschanowsky, Catherine, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Kasahara, Hironori, editor, and Kimura, Keiji, editor

Published
2013
Full Text
View/download PDF

30. A Fast Parallel Graph Partitioner for Shared-Memory Inspector/Executor Strategies

Author

Krieger, Christopher D., Strout, Michelle Mills, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Kasahara, Hironori, editor, and Kimura, Keiji, editor

Published
2013
Full Text
View/download PDF

31. Evaluation of Hierarchical Mesh Reorderings

Author

Strout, Michelle Mills, Osheim, Nissa, Rostron, Dave, Hovland, Paul D., Pothen, Alex, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Allen, Gabrielle, editor, Nabrzyski, Jarosław, editor, Seidel, Edward, editor, van Albada, Geert Dick, editor, Dongarra, Jack, editor, and Sloot, Peter M. A., editor

Published
2009
Full Text
View/download PDF

32. Smashing: Folding Space to Tile through Time

Author

Osheim, Nissa, Strout, Michelle Mills, Rostron, Dave, Rajopadhye, Sanjay, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, and Amaral, José Nelson, editor

Published
2008
Full Text
View/download PDF

35. Linearity Analysis for Automatic Differentiation

Author

Strout, Michelle Mills, Hovland, Paul, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Alexandrov, Vassil N., editor, van Albada, Geert Dick, editor, Sloot, Peter M. A., editor, and Dongarra, Jack, editor

Published
2006
Full Text
View/download PDF

36. Hybrid Static/Dynamic Activity Analysis

Author

Kreaseck, Barbara, Ramos, Luis, Easterday, Scott, Strout, Michelle, Hovland, Paul, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Alexandrov, Vassil N., editor, van Albada, Geert Dick, editor, Sloot, Peter M. A., editor, and Dongarra, Jack, editor

Published
2006
Full Text
View/download PDF

37. Extreme Heterogeneity 2018 - Productive Computational Science in the Era of Extreme Heterogeneity: Report for DOE ASCR Workshop on Extreme Heterogeneity

Author

Vetter, Jeffrey S., primary, Brightwell, Ron, additional, Gokhale, Maya, additional, McCormick, Pat, additional, Ross, Rob, additional, Shalf, John, additional, Antypas, Katie, additional, Donofrio, David, additional, Humble, Travis, additional, Schuman, Catherine, additional, Van Essen, Brian, additional, Yoo, Shinjae, additional, Aiken, Alex, additional, Bernholdt, David, additional, Byna, Suren, additional, Cameron, Kirk, additional, Cappello, Frank, additional, Chapman, Barbara, additional, Chien, Andrew, additional, Hall, Mary, additional, Hartman-Baker, Rebecca, additional, Lan, Zhiling, additional, Lang, Michael, additional, Leidel, John, additional, Li, Sherry, additional, Lucas, Robert, additional, Mellor-Crummey, John, additional, Peltz Jr., Paul, additional, Peterka, Thomas, additional, Strout, Michelle, additional, and Wilke, Jeremiah, additional

Published
2018
Full Text
View/download PDF

41. Rescheduling for Locality in Sparse Matrix Computations

Author

Strout, Michelle Mills, Carter, Larry, Ferrante, Jeanne, Goos, G., editor, Hartmanis, J., editor, van Leeuwen, J., editor, Alexandrov, Vassil N., editor, Dongarra, Jack J., editor, Juliano, Benjoe A., editor, Renner, René S., editor, and Tan, C. J. Kenneth, editor

Published
2001
Full Text
View/download PDF

42. Extreme Heterogeneity 2018: Productive Computational Science in the Era of Extreme Heterogeneity Report for DOE ASCR Basic Research Needs Workshop on Extreme Heterogeneity January 23–25, 2018

Author

Vetter, Jeffrey S., primary, Brightwell, Ron, additional, Gokhale, Maya, additional, McCormick, Pat, additional, Ross, Rob, additional, Shalf, John, additional, Antypas, Katie, additional, Donofrio, David, additional, Dubey, Anshu, additional, Humble, Travis, additional, Schuman, Catherine, additional, Van Essen, Brian, additional, Yoo, Shinjae, additional, Aiken, Alex, additional, Bernholdt, David, additional, Byna, Suren, additional, Cameron, Kirk, additional, Cappello, Frank, additional, Chapman, Barbara, additional, Chien, Andrew, additional, Hall, Mary, additional, Hartman-Baker, Rebecca, additional, Lan, Zhiling, additional, Lang, Michael, additional, Leidel, John, additional, Li, Sherry, additional, Lucas, Robert, additional, Mellor-Crummey, John, additional, Peltz Jr., Paul, additional, Peterka, Thomas, additional, Strout, Michelle, additional, and Wilke, Jeremiah, additional

Published
2018
Full Text
View/download PDF

47. Abstractions for Defining Semi-Regular Grids Orthogonally from Stencils

Author

Stone, Andrew, Strout, Michelle Mills, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Kasahara, Hironori, editor, and Kimura, Keiji, editor

Published
2013
Full Text
View/download PDF

49. OpenAD/F: a modular open-source tool for automatic differentiation of Fortran codes

Author

Utke, Jean, Naumann, Uwe, Fagan, Mike, Tallent, Nathan, Strout, Michelle, Heimbach, Patrick, Hill, Chris, and Wunsch, Carl

Subjects
Algorithm, Numerical differentiation -- Methods, FORTRAN -- Usage, Algorithms -- Usage, Coding theory
Abstract

The OpenAD/F tool allows the evaluation of derivatives of functions defined by a Fortran program. The derivative evaluation is performed by a Fortran code resulting from the analysis and transformation of the original program that defines the function of interest. OpenAD/F has been designed with a particular emphasis on modularity, flexibility, and the use of open source components. While the code transformation follows the basic principles of automatic differentiation, the tool implements new algorithmic approaches at various levels, for example, for basic block preaccumulation and call graph reversal. Unlike most other automatic differentiation tools, OpenAD/F uses components provided by the OpenAD framework, which supports a comparatively easy extension of the code transformations in a language-independent fashion. It uses code analysis results implemented in the OpenAnalysis component. The interface to the language-independent transformation engine is an XML-based format, specified through an XML schema. The implemented transformation algorithms allow efficient derivative computations using locally optimized cross-country sequences of vertex, edge, and face elimination steps. Specifically, for the generation of adjoint codes, OpenAD/F supports various code reversal schemes with hierarchical checkpointing at the subroutine level. As an example from geophysical fluid dynamics, a nonlinear time-dependent scalable, yet simple, barotropic ocean model is considered. OpenAD/F's reverse mode is applied to compute sensitivities of some of the model's transport properties with respect to gridded fields such as bottom topography as independent (control) variables. Categories and Subject Descriptors: G.1.4 [Numerical Analysis]: --Automatic differentiation; D.3.4 [Programming Languages]: --Code generation, Compilers; F.3.2 [Logics and Meanings of Program]: Semantics of Programming Languages Program analysis; G. 1.6 [Numerical Analysis]: --Gradient methods General Terms: Algorithms, Performance Additional Key Words and Phrases: Automatic differentiation, source transformation, adjoint compiler

Published
2008

Catalog

Books, media, physical & digital resources
See catalog results