Automated Design Space Exploration with Aspen

Spafford, Kyle L.; Vetter, Jeffrey S.

doi:10.1155/2015/157305

Title: Automated Design Space Exploration with Aspen

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Abstract

Architects and applications scientists often use performance models to explore a multidimensional design space of architectural characteristics, algorithm designs, and application parameters. With traditional performance modeling tools, these explorations forced users to first develop a performance model and then repeatedly evaluate and analyze the model manually. These manual investigations proved laborious and error prone. More importantly, the complexity of this traditional process often forced users to simplify their investigations. To address this challenge of design space exploration, we extend our Aspen (Abstract Scalable Performance Engineering Notation) language with three new language constructs: user-defined resources, parameter ranges, and a collection of costs in the abstract machine model. Then, we use these constructs to enable automated design space exploration via a nonlinear optimization solver. We show how four interesting classes of design space exploration scenarios can be derived from Aspen models and formulated as pure nonlinear programs. The analysis tools are demonstrated using examples based on Aspen models for a three-dimensional Fast Fourier Transform, the CoMD molecular dynamics proxy application, and the DARPA Streaming Sensor Challenge Problem. Our results show that this approach can compose and solve arbitrary performance modeling questions quickly and rigorously when compared to the traditional manual approach.

Authors:

Spafford, Kyle L. ^[1]; Vetter, Jeffrey S. ^[1]

Oak Ridge National Laboratory, One Bethel Valley Road, Building 5100, MS-6173 Oak Ridge, TN 37831-6173, USA

Publication Date:: Thu Jan 01 00:00:00 EST 2015

Sponsoring Org.:: USDOE

OSTI Identifier:: 1198095

Resource Type:: Published Article

Journal Name:: Scientific Programming

Additional Journal Information:: Journal Name: Scientific Programming Journal Volume: 2015; Journal ID: ISSN 1058-9244

Publisher:: Hindawi Publishing Corporation

Country of Publication:: Egypt

Language:: English

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                    Spafford, Kyle L., and Vetter, Jeffrey S. Automated Design Space Exploration with Aspen.  Egypt: N. p., 2015. 
Web.  doi:10.1155/2015/157305.

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                    Spafford, Kyle L., & Vetter, Jeffrey S. Automated Design Space Exploration with Aspen.  Egypt.  https://doi.org/10.1155/2015/157305

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                    Spafford, Kyle L., and Vetter, Jeffrey S. Thu .  
"Automated Design Space Exploration with Aspen".  Egypt.  https://doi.org/10.1155/2015/157305.

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@article{osti_1198095,

  title        = {Automated Design Space Exploration with Aspen},

  author       = {Spafford, Kyle L. and Vetter, Jeffrey S.},

  abstractNote = {Architects and applications scientists often use performance models to explore a multidimensional design space of architectural characteristics, algorithm designs, and application parameters. With traditional performance modeling tools, these explorations forced users to first develop a performance model and then repeatedly evaluate and analyze the model manually. These manual investigations proved laborious and error prone. More importantly, the complexity of this traditional process often forced users to simplify their investigations. To address this challenge of design space exploration, we extend our Aspen (Abstract Scalable Performance Engineering Notation) language with three new language constructs: user-defined resources, parameter ranges, and a collection of costs in the abstract machine model. Then, we use these constructs to enable automated design space exploration via a nonlinear optimization solver. We show how four interesting classes of design space exploration scenarios can be derived from Aspen models and formulated as pure nonlinear programs. The analysis tools are demonstrated using examples based on Aspen models for a three-dimensional Fast Fourier Transform, the CoMD molecular dynamics proxy application, and the DARPA Streaming Sensor Challenge Problem. Our results show that this approach can compose and solve arbitrary performance modeling questions quickly and rigorously when compared to the traditional manual approach.},

  doi          = {10.1155/2015/157305},

  journal      = {Scientific Programming},

  number       = ,

  volume       = 2015,

  place        = {Egypt},

  year         = {Thu Jan 01 00:00:00 EST 2015},

  month        = {Thu Jan 01 00:00:00 EST 2015}

}

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