GVR - Revision history

Pinfold at 04:39, July 10, 2023

2023-07-10T04:39:41Z

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	\| imagecaption =		\| imagecaption =
	\| team-members = [http://www.uchicago.edu/ U. of Chicago], [http://www.anl.gov/ ANL], [http://www.hpl.hp.com/ HP Labs]		\| team-members = [http://www.uchicago.edu/ U. of Chicago], [http://www.anl.gov/ ANL], [http://www.hpl.hp.com/ HP Labs]
	\| pi = [~~http://www.cs.uchicago.edu/people/aachien~~ Andrew A. Chien ~~(U. of Chicago)~~]		\| pi = [[Andrew Chien]]
	\| co-pi = [http://www.mcs.anl.gov/person/pavan-balaji/ Pavan Balaji (ANL)]		\| co-pi = [http://www.mcs.anl.gov/person/pavan-balaji/ Pavan Balaji (ANL)]
	\| website = http://gvr.cs.uchicago.edu/		\| website = http://gvr.cs.uchicago.edu/

imported>Sonia at 01:50, September 21, 2016

2016-09-21T01:50:09Z

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	[[File:GVR-Resilience-Co-design.png\|400px]]		[[File:GVR-Resilience-Co-design.png\|400px]]

			== Project Impact ==

			* [https://xstackwiki.modelado.org/images/4/4c/GVR_Highlights_Summary9-2016.pdf GVR Project Impact]

	'''Challenges'''		'''Challenges'''

imported>Achien: /* Team Members */

2015-12-07T00:25:22Z

Team Members

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	* Particle codes (ddcMD) (David Richards, Ignacio Laguna, LLNL)		* Particle codes (ddcMD) (David Richards, Ignacio Laguna, LLNL)
	* Adaptive Mesh Refinement (Chombo) (Brian van Straalen, Anshu Dubey, LBNL)		* Adaptive Mesh Refinement (Chombo) (Brian van Straalen, Anshu Dubey, LBNL)
			* Combustion (S3D) (Jackie Chen, Sandia)

imported>Achien: /* Team Members */

2015-12-07T00:22:06Z

Team Members

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	== Team Members ==		== Team Members ==
	* [http://www.uchicago.edu/ University of Chicago]: [http://www.cs.uchicago.edu/people/aachien/ Andrew A. Chien] (PI), [http://www.cs.uchicago.edu/people/hfujita Hajime Fujita], [http://www.cs.uchicago.edu/people/zar1 Zachary Rubenstein], [http://www.cs.uchicago.edu/people/zimingzheng Ziming Zheng], [http://www.cs.uchicago.edu/people/dun Nan Dun], [http://www.cs.uchicago.edu/people/aimanf Aiman Fang]		* [http://www.uchicago.edu/ University of Chicago]: [http://www.cs.uchicago.edu/people/aachien/ Andrew A. Chien] (PI), [http://www.cs.uchicago.edu/people/hfujita Hajime Fujita], [http://www.cs.uchicago.edu/people/zar1 Zachary Rubenstein], [http://www.cs.uchicago.edu/people/zimingzheng Ziming Zheng], [http://www.cs.uchicago.edu/people/dun Nan Dun], [http://www.cs.uchicago.edu/people/aimanf Aiman Fang], Yan Liu
	* [http://www.anl.gov/ Argonne National Laboratory (ANL)]: [http://www.mcs.anl.gov/person/pavan-balaji/ Pavan Balaji] (co-PI), [http://www.mcs.anl.gov/person/pete-beckman Pete Beckman], [http://www.mcs.anl.gov/person/kamil-iskra/ Kamil Iskra]		* [http://www.anl.gov/ Argonne National Laboratory (ANL)]: [http://www.mcs.anl.gov/person/pavan-balaji/ Pavan Balaji] (co-PI), [http://www.mcs.anl.gov/person/pete-beckman Pete Beckman], [http://www.mcs.anl.gov/person/kamil-iskra/ Kamil Iskra], Wes Bland
	* [http://www.hpl.hp.com/ HP Labs]: Robert Schreiber		* [http://www.hpl.hp.com/ HP Labs]: Robert Schreiber

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	Global View Resilience (GVR) is a new programming approach that exploits a global view data model (global naming of data, consistency, and distributed layout), adding reliability to globally visible distributed arrays. The globally-visible distributed array abstraction is "multi-version", providing redundancy in time, and a convenient location for application annotations for reliability needs. Because the distributed array abstraction is portable, GVR enables application programmers to manage reliability (and its overhead) in a flexible, portable fashion, tapping their deep scientific and application code insights. Further, GVR will provide a flexible, efficient, cross-layer error management architecture called “open reliability” that allows applications to describe error detection (checking) and recovery routines and inject them into the GVR stack for efficient implementation. This architecture enables applications and systems to work in concert, exploiting semantics (algorithmic or even scientific domain) and key capabilities (e.g., fast error detection in hardware) to dramatically increase the range of errors that can be detected and corrected.		Global View Resilience (GVR) is a new programming approach that exploits a global view data model (global naming of data, consistency, and distributed layout), adding reliability to globally visible distributed arrays. The globally-visible distributed array abstraction is "multi-version", providing redundancy in time, and a convenient location for application annotations for reliability needs. Because the distributed array abstraction is portable, GVR enables application programmers to manage reliability (and its overhead) in a flexible, portable fashion, tapping their deep scientific and application code insights. Further, GVR will provide a flexible, efficient, cross-layer error management architecture called “open reliability” that allows applications to describe error detection (checking) and recovery routines and inject them into the GVR stack for efficient implementation. This architecture enables applications and systems to work in concert, exploiting semantics (algorithmic or even scientific domain) and key capabilities (e.g., fast error detection in hardware) to dramatically increase the range of errors that can be detected and corrected.

	== Resilience Challenges ==		== Resilience Challenges ==

imported>Achien: /* Publications */

2015-12-07T00:20:57Z

Publications

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	* Aiman Fang, Hajime Fujita and Andrew A. Chien, "Towards Understanding Post-Recovery Efficiency for Shrinking and Non-Shrinking Recovery", in Proceedings of the 8th Workshop on Resiliency in High Performance Computing (Resilience) in Clusters, Clouds, and Grids, at Euro-Par 2015, Vienna, Austria, August 24, 2015		* Aiman Fang, Hajime Fujita and Andrew A. Chien, "Towards Understanding Post-Recovery Efficiency for Shrinking and Non-Shrinking Recovery", in Proceedings of the 8th Workshop on Resiliency in High Performance Computing (Resilience) in Clusters, Clouds, and Grids, at Euro-Par 2015, Vienna, Austria, August 24, 2015
	* Anshu Dubey, Hajime Fujita, Zachary Rubenstein, Brian Van Straalen and Andrew Chien. "A Case Study Of Application Structure Aware Resilience Through Differentiated State Saving And Recovery", in Proceedings of the 8th Workshop on Resiliency in High Performance Computing (Resilience) in Clusters, Clouds, and Grids, at Euro-Par 2015, Vienna, Austria, August 24, 2015		* Anshu Dubey, Hajime Fujita, Zachary Rubenstein, Brian Van Straalen and Andrew Chien. "A Case Study Of Application Structure Aware Resilience Through Differentiated State Saving And Recovery", in Proceedings of the 8th Workshop on Resiliency in High Performance Computing (Resilience) in Clusters, Clouds, and Grids, at Euro-Par 2015, Vienna, Austria, August 24, 2015
	Hajime Fujita, Kamil Iskra, Pavan Balaji, and Andrew A. Chien, "Empirical Characterization of Versioning Architectures", in Proceedings of IEEE Cluster, September 8-10, 2015, Chicago.		* Hajime Fujita, Kamil Iskra, Pavan Balaji, and Andrew A. Chien, "Empirical Characterization of Versioning Architectures", in Proceedings of IEEE Cluster, September 8-10, 2015, Chicago.
	* A. Chien, P. Balaji, N. Dun, A. Fang, H. Fujita, K. Iskra, Z. Rubenstein, Z. Zheng, J. Hammond, I. Laguna, D. Richards, A. Dubey, B. van Straalen, M Hoemmen, M. Heroux, K. Teranishi, A. Siegel. Exploring Versioning for Resilience in Scientific Applications: Global-view Resilience, submitted for publication, March 2015. (Best overall project summary)		* A. Chien, P. Balaji, N. Dun, A. Fang, H. Fujita, K. Iskra, Z. Rubenstein, Z. Zheng, J. Hammond, I. Laguna, D. Richards, A. Dubey, B. van Straalen, M Hoemmen, M. Heroux, K. Teranishi, A. Siegel. Exploring Versioning for Resilience in Scientific Applications: Global-view Resilience, submitted for publication, March 2015. (Best overall project summary)
	* Aiman Fang and Andrew A. Chien, "How Much SSD Is Useful for Resilience in Supercomputers”, in ACM Symposium on Fault-tolerance at Extreme-Scale (FTXS) associated with HPDC 2015, Portland, Oregon, June 15, 2015 (Slides)		* Aiman Fang and Andrew A. Chien, "How Much SSD Is Useful for Resilience in Supercomputers”, in ACM Symposium on Fault-tolerance at Extreme-Scale (FTXS) associated with HPDC 2015, Portland, Oregon, June 15, 2015 (Slides)

imported>Achien at 00:20, December 7, 2015

2015-12-07T00:20:28Z

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 * Demonstrated easy application integration, <2% lines of code change in large (10K-100K line applications)
 * Demonstrated controllable and low performance overhead (application scaling to 16,384 nodes and <2% overhead)
 * Demonstrated flexible, portable application-semantics based forward-error correction in multiple applications (OpenMC, ddcMD, etc.)
 * Software release available from http://gvr.cs.uchicago.edu/ and deployed at multiple supercomputing centers, including NERSC.

imported>Achien: /* Research Products */

2015-06-08T20:11:51Z

Research Products

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	== Research Products ==		== Research Products ==

	Full report = [[gvr-research-products.pdf]]		Full report = [[Media:gvr-research-products.pdf]]

	* Demonstrated easy application integration, <2% lines of code change in large (10K-100K line applications)		* Demonstrated easy application integration, <2% lines of code change in large (10K-100K line applications)

imported>Achien at 20:10, June 8, 2015

2015-06-08T20:10:50Z

← Older revision		Revision as of 20:10, June 8, 2015
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	== Research Products ==		== Research Products ==

			Full report = [[gvr-research-products.pdf]]

	* Demonstrated easy application integration, <2% lines of code change in large (10K-100K line applications)		* Demonstrated easy application integration, <2% lines of code change in large (10K-100K line applications)

imported>Achien at 19:32, June 8, 2015

2015-06-08T19:32:18Z

← Older revision		Revision as of 19:32, June 8, 2015
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	\| co-pi = [http://www.mcs.anl.gov/person/pavan-balaji/ Pavan Balaji (ANL)]		\| co-pi = [http://www.mcs.anl.gov/person/pavan-balaji/ Pavan Balaji (ANL)]
	\| website = http://gvr.cs.uchicago.edu/		\| website = http://gvr.cs.uchicago.edu/
			\| download = https://sites.google.com/site/uchicagolssg/lssg/research/gvr/downloads
	}}		}}

imported>Achien at 19:29, June 8, 2015

2015-06-08T19:29:49Z

← Older revision		Revision as of 19:29, June 8, 2015
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	* Rich Solver Library Building Block		* Rich Solver Library Building Block
	* Programming System Target		* Programming System Target


			== Research Products ==

			* Demonstrated easy application integration, <2% lines of code change in large (10K-100K line applications)
			* Demonstrated controllable and low performance overhead (application scaling to 16,384 nodes and <2% overhead)
			* Demonstrated flexible, portable application-semantics based forward-error correction in multiple applications (OpenMC, ddcMD, etc.)
			* Software release available from http://gvr.cs.uchicago.edu/ and deployed at multiple supercomputing centers, including NERSC.