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1. Encoding integers and rationals on neuromorphic computers using virtual neuron

Author

Prasanna Date, Shruti Kulkarni, Aaron Young, Catherine Schuman, Thomas Potok, and Jeffrey Vetter

Subjects
Medicine, Science
Abstract

Abstract Neuromorphic computers emulate the human brain while being extremely power efficient for computing tasks. In fact, they are poised to be critical for energy-efficient computing in the future. Neuromorphic computers are primarily used in spiking neural network–based machine learning applications. However, they are known to be Turing-complete, and in theory can perform all general-purpose computation. One of the biggest bottlenecks in realizing general-purpose computations on neuromorphic computers today is the inability to efficiently encode data on the neuromorphic computers. To fully realize the potential of neuromorphic computers for energy-efficient general-purpose computing, efficient mechanisms must be devised for encoding numbers. Current encoding mechanisms (e.g., binning, rate-based encoding, and time-based encoding) have limited applicability and are not suited for general-purpose computation. In this paper, we present the virtual neuron abstraction as a mechanism for encoding and adding integers and rational numbers by using spiking neural network primitives. We evaluate the performance of the virtual neuron on physical and simulated neuromorphic hardware. We estimate that the virtual neuron could perform an addition operation using just 23 nJ of energy on average with a mixed-signal, memristor-based neuromorphic processor. We also demonstrate the utility of the virtual neuron by using it in some of the μ-recursive functions, which are the building blocks of general-purpose computation.

Published
2023
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2. DESTINY: A Comprehensive Tool with 3D and Multi-Level Cell Memory Modeling Capability

Author

Sparsh Mittal, Rujia Wang, and Jeffrey Vetter

Subjects
cache, SRAM, eDRAM, non-volatile memory (NVM or NVRAM), STT-RAM, ReRAM, PCM, SOT-RAM, DRAM, DWM, flash, open-source, modeling tool, emerging memory technologies, Applications of electric power, TK4001-4102
Abstract

To enable the design of large capacity memory structures, novel memory technologies such as non-volatile memory (NVM) and novel fabrication approaches, e.g., 3D stacking and multi-level cell (MLC) design have been explored. The existing modeling tools, however, cover only a few memory technologies, technology nodes and fabrication approaches. We present DESTINY, a tool for modeling 2D/3D memories designed using SRAM, resistive RAM (ReRAM), spin transfer torque RAM (STT-RAM), phase change RAM (PCM) and embedded DRAM (eDRAM) and 2D memories designed using spin orbit torque RAM (SOT-RAM), domain wall memory (DWM) and Flash memory. In addition to single-level cell (SLC) designs for all of these memories, DESTINY also supports modeling MLC designs for NVMs. We have extensively validated DESTINY against commercial and research prototypes of these memories. DESTINY is very useful for performing design-space exploration across several dimensions, such as optimizing for a target (e.g., latency, area or energy-delay product) for a given memory technology, choosing the suitable memory technology or fabrication method (i.e., 2D v/s 3D) for a given optimization target, etc. We believe that DESTINY will boost studies of next-generation memory architectures used in systems ranging from mobile devices to extreme-scale supercomputers. The latest source-code of DESTINY is available from the following git repository: https://bitbucket.org/sparshmittal/destinyv2.

Published
2017
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3. A Technique for Improving Lifetime of Non-Volatile Caches Using Write-Minimization

Author

Sparsh Mittal and Jeffrey Vetter

Subjects
non-volatile memory (NVM), SRAM, cache, write-endurance, temporal locality, write minimization, device lifetime, Applications of electric power, TK4001-4102
Abstract

While non-volatile memories (NVMs) provide high-density and low-leakage, they also have low write-endurance. This, along with the write-variation introduced by the cache management policies, can lead to very small cache lifetime. In this paper, we propose ENLIVE, a technique for ENhancing the LIfetime of non-Volatile cachEs. Our technique uses a small SRAM (static random access memory) storage, called HotStore. ENLIVE detects frequently written blocks and transfers them to the HotStore so that they can be accessed with smaller latency and energy. This also reduces the number of writes to the NVM cache which improves its lifetime. We present microarchitectural schemes for managing the HotStore. Simulations have been performed using an x86-64 simulator and benchmarks from SPEC2006 suite. We observe that ENLIVE provides higher improvement in lifetime and better performance and energy efficiency than two state-of-the-art techniques for improving NVM cache lifetime. ENLIVE provides 8.47×, 14.67× and 15.79× improvement in lifetime or two, four and eight core systems, respectively. In addition, it works well for a range of system and algorithm parameters and incurs only small overhead.

Published
2016
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4. Towards enhancing coding productivity for GPU programming using static graphs

Author

Jeffrey Vetter, Antonio J. Peña Monferrer, Pedro Valero-Lara, Leonel Toledo, and Barcelona Supercomputing Center

Subjects
Computer Networks and Communications, Particle swarm optimization, Data dependencies, Informàtica::Enginyeria del software [Àrees temàtiques de la UPC], Static graph, CUDA, Coding productivity, OpenACC, CUDA (Computer architecture), Supercomputadors, Hardware and Architecture, Control and Systems Engineering, Signal Processing, Electrical and Electronic Engineering, Graphics processing units, Conjugate gradient, Tasking, coding productivity, tasking, data dependencies, static graph, conjugate gradient, particle swarm optimization
Abstract

The main contribution of this work is to increase the coding productivity of GPU programming by using the concept of Static Graphs. GPU capabilities have been increasing significantly in terms of performance and memory capacity. However, there are still some problems in terms of scalability and limitations to the amount of work that a GPU can perform at a time. To minimize the overhead associated with the launch of GPU kernels, as well as to maximize the use of GPU capacity, we have combined the new CUDA Graph API with the CUDA programming model (including CUDA math libraries) and the OpenACC programming model. We use as test cases two different, well-known and widely used problems in HPC and AI: the Conjugate Gradient method and the Particle Swarm Optimization. In the first test case (Conjugate Gradient) we focus on the integration of Static Graphs with CUDA. In this case, we are able to significantly outperform the NVIDIA reference code, reaching an acceleration of up to 11× thanks to a better implementation, which can benefit from the new CUDA Graph capabilities. In the second test case (Particle Swarm Optimization), we complement the OpenACC functionality with the use of CUDA Graph, achieving again accelerations of up to one order of magnitude, with average speedups ranging from 2× to 4×, and performance very close to a reference and optimized CUDA code. Our main target is to achieve a higher coding productivity model for GPU programming by using Static Graphs, which provides, in a very transparent way, a better exploitation of the GPU capacity. The combination of using Static Graphs with two of the current most important GPU programming models (CUDA and OpenACC) is able to reduce considerably the execution time w.r.t. the use of CUDA and OpenACC only, achieving accelerations of up to more than one order of magnitude. Finally, we propose an interface to incorporate the concept of Static Graphs into the OpenACC Specifications. his research was funded by EPEEC project from the European Union’s Horizon 2020 Research and Innovation program under grant agreement No. 801051. This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan, accessed on 13 April 2022).

Published
2022
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7. Advanced Scientific Computing Research Exascale Requirements Review. An Office of Science review sponsored by Advanced Scientific Computing Research, September 27-29, 2016, Rockville, Maryland

Author

Ann Almgren, Phil DeMar, Jeffrey Vetter, Katherine Riley, Katie Antypas, Deborah Bard, Richard Coffey, Eli Dart, Sudip Dosanjh, Richard Gerber, James Hack, Inder Monga, Michael E. Papka, Lauren Rotman, Tjerk Straatsma, Jack Wells, David E. Bernholdt, Wes Bethel, George Bosilca, Frank Cappello, Todd Gamblin, Salman Habib, Judy Hill, Jeffrey K. Hollingsworth, Lois Curfman McInnes, Kathryn Mohror, Shirley Moore, Ken Moreland, Rob Roser, Sameer Shende, Galen Shipman, and Samuel Williams

Published
2017
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8. ORNL Laboratory Directed Research and Development Program FY 2008 Annual Report

Author

Joanna McFarlane, Valmor de Almeida, Johney Green, Stuart Daw, Kalyan Chakravarthy, Sam Lewis, Scott Sluder, Bill Steele, Robert Wagner, Rolf Reitz, Gary Bell, Rick Battiste, Ralph Dinwiddie, Sam Sham, Panos Datskos, Nickolay Lavrik, Barton Smith, Viviane Schwartz, Costas Tsouris, Claus Daniel, Leon Tolbert, Madhu Chinthavali, Burak Ozpineci, Fran Li, John Kueck, Michael Starke, Hui Zhang, Yan Xu, David DePaoli, Alicia Compere, William Griffith, Chaitanya Narula, Arpad Vass, Luis Sanchez, Joel McDuffee, Jess Gehin, Randy Hobbs, Larry Ott, Lance Snead, Donald Spellman, Dennis Heatherly, Ronald Ellis, Kenneth Thoms, Sheng Dai, Huimin Luo, Gary Baker, Todd Toops, C. Britton, G. Alley, M. Ericson, R. Warmack, S. Retterer, Glenn Young, Bernadetta Srijanto, Chad Duty, Ron Ott, Philip Boudreaux, Adrian Sabau, Gerald Jellison, Curt Maxey, Keith Leonard, Biswajit Das, Volker Urban, Kunlun Hong, Phillip Britt, Jimmy Mays, Alexander Boeker, Miroslaw Gruszkiewicz, Ariel Chialvo, David Cole, Michael Simonson, Douglas Goeringer, Gary Van Berkel, Vilmos Kertesz, William Whitten, Robert Shaw, G. Stocks, Amit Goyal, Jianxin Zhong, Yanfei Gao, Albina Borisevich, Niels Jonge, Andrew Lupini, Stephen Pennycook, Gabriel Veith, Ho Lee, Matthew Chisholm, David Singh, Sergei Kalinin, Gilbert Brown, Ilia Ivanov, Stephen Jesse, David Hoelzer, James Bentley, Chong Fu, Michael Miller, Xingqiu Chen, Xun-Li Wang, Benjamin Hay, Jeremy Jackson, David Geohegan, Gernot Rother, Petro Maksymovych, Vincent Meunier, J. Wendelken, Zhenyu Zhang, Gyula Eres, M. Paranthaman, Baohua Gu, Wenguang Zhu, A. Buchanan III, Michelle Kidder, Reza Dabestani, Edward Hagaman, Minghu Pan, John Ankner, Mark Dadmun, S. Kilbey II, John Simpson, Nancy Dudney, Karren More, Ed Hagaman, Bob Shaw, De-en Jiang, Andrew Payzant, Edgar Lara-Curzio, Charles Collier, Seung-Yong Jung, Scott Retterer, Zhiyu Hu, Mark Buckner, Michael Moore, Michael Vann, Nageswara Rao, Lawrence MacIntryre, Miljko Bobrek, Benjamin Huey, Donald Bouldin, A. Qualls, B. Sumpter, S. Labinov, John Neal, Lynn Boatner, Slobodan Rajic, Mallikarjun Shankar, Yu Jiao, Ryan Kerekes, Rick Lusk, Thomas Potok, Timothy Rhyne, Vladimir Protopopescu, William Heller, Yiming Mo, Dean Myles, Greg Smith, Eugene Mamontov, Peter Cummings, Kenneth Herwig, Louis Santodonato, J. Ankner, J. Mays, J. Messman, D. Myles, B. Lokitz, Liyuan Liang, Wei Wang, Alex Johs, Hugh O’Neill, Edward Snell, Chris Tulk, Antonio Dos Santos, Jamie Molaison, Bryan Chakoumakos, Juske Horita, Dave Cole, Robert Welton, F. Baity, Richard Goulding, Andrew Christianson, Sheila Baker, Mark Lumsden, Stephen Nagler, Brian Sales, Thomas Schulthess, Thomas McManamy, Roy Crawford, Phillip Ferguson, James Janney, Mark Rennich, Leighton Coates, Flora Meilleur, Randy Fishman, Lee Robertson, Jian Shen, Wei-Ren Chen, Gregory Smith, William Goddard, Yi Liu, Yun Liu, Lionel Porcar, Pratul Agarwal, Edward Michaud III, Carmen Foster, Martin Keller, Zamin Yang, Amudhan Venkateswaran, Mircea Podar, Christopher Schadt, Steven Brown, Shihui Yang, Timothy Tschaplinski, Dale Pelletier, Gregory Hurst, Yunfeng Yang, Udaya Kalluri, Timothy McKnight, Jennifer Morrell-Falvey, Patricia Lankford, Sara Jawdy, A. Borole, Anthony Palumbo, Nance Ericson, Jeremy Smith, Elissa Chesler, Virginia Dale, Latha Baskaran, Budhendra Bhaduri, Robin Graham, Richard Middleton, Patrick Mulholland, Esther Parish, Alexandre Sorokine, Amy Wolfe, Thomas Wilbanks, Auroop Ganguly, Anthony King, David Erickson, Keith Kline, Sherry Wright, Hector Castro-Gonzalez, Marie De Graaff, Charles Garten III, Aimee Classen, Paul Hanson, Stan Wullschleger, Richard Norby, Kenneth Childs, Warren Thomas, Brynn Voy, Ram Datar, Olaf Storaasli, Edoardo Apra, Jerzy Bernholc, Robert Harrison, William Shelton, Bobby Sumpter, Sudharshan Vazhkudai, John Cobb, Xiaosong Ma, Stephen Scott, Hong Ong, Christian Engelmann, Geoffroy Vallee, Ricky Kendall, Ron Brightwell, Barney Maccabe, T. Schulthess, M. Eisenbach, D. Nicholson, X. Tao, C. Zhou, J. Levesque, Andrey Gorin, Nabeela Ahmad, Andrew Bordner, Jessie Gu, Guruprasad Kora, Chongle Pan, Byung-Hoon Park, Nagiza Samatova, Xiuping Tao, Edward Uberbacher, Kalyan Perumalla, Sudip Seal, Jeffrey Vetter, Srikanth Yoginath, Srdjan Simunovic, Phani Nukala, Kevin Clarno, Ian Gauld, Theodore Besmann, Charles Weber, Warren Grice, Ryan Bennink, Philip Evans, Travis Humble, David Bernholdt, Richard Barrett, Wael Elwasif, Aniruddha Shet, John Drake, J. White III, R. Archibald, J. Drake, K. Evans, D. Kothe, P. Worley, Jim Kohl, Doug Lepro, Dude Neergaard, Thomas Maier, Gonzalo Alvarez, Jeremy Meredith, Michael Summers, Mark Bannister, Robert Hettich, Charles Vane, Charles Havener, Herbert Krause, Michael Fogle, Jr., David Schultz, Robert Continetti, Mats Larsson, Richard Thomas, Mitchel Doktycz, David Allison, Thomas Thundat, Christopher Rey, Abhijeet Borole, Ali Passian, Yisong Wang, Yie Liu, Henry Lin, Boyd Evans, Siyang Zheng, Jason Fowlkes, Philip Rack, James Lee, Barbara Evans, Peter Reilly, Elias Greenbaum, Sylvia McLain, David Baker, Chengdu Liang, Jane Howe, Jun Xu, Radu Custelcean, Steve Overbury, Seth Cohen, Richard Ward, Kara Kruse, James Nutaro, Barbara Beckerman, Oscar Grandas, Xiaohui Cui, B. Radhakrishnan, X.-G. Zhang, An-Ping Li, N. Kulkarni, Shannon Mahurin, Meng-Dawn Cheng, David Gossage, Bruce Wilson, T. Yin, L. Gunter, Ken Littrell, Hassina Bilheux, D. Bjornstad, A. Wolfe, Jeff Warren, Timothy Bigelow, John Caughman, John McKeever, Philip Ryan, Matthew Scudiere, Gary Alley, Nagraj Kulkarni, Hsin Wang, Harry Meyer, Bala Radhakrishnan, Don Nicholson, Peter Todd, Kenneth Tobin, Vincent Paquit, Jeffery Price, John Jansen, Lonnie Love, Peter Lloyd, Christopher Mann, Philip Bingham, John Biggerstaff, Michael Zemel, Brian D’Urso, Randy Lind, Justin Baba, Seung Lee, S. Rajic, P. Datskos, Fernando Reboredo, Chengjun Sun, Xiaoguang Zhang, David Mandrus, C. Narula, M. Moses-DeBusk, A. Buchanan, C. Hsueh, P. Becher, C. Liu, John Wang, Narendra Dahotre, Seokho Kim, Peter Blau, Steve Pawel, Hans Christen, Joachim Schneibel, Michael Brady, Terry Tiegs, John Vitek, J. Horton, Ken Liu, Dan Naus, I. Wright, Lance. Snead, Thak Byun, Roger Miller, B. Bischoff, K. Adcock, Evan Ohriner, Donald Erdmann III, Katyayani Seal, James Haynes, Bruce Pint, Pengcheng Dai, Zheng Gai, Lifeng Yin, Y. Melnichenko, G. Wignall, D. Cole, A. Radlinski, M. Mastalerz, C. Alexander, R. Smithwick, L. Lewis, L. Boatner, Juan Ferrada, Jack Collins, Les Dole, Charles Forsberg, M. Haire, Rodney Hunt, Ben Lewis, Ray Wymer, Jennifer Ladd-Lively, Michael Hu, Lei Shao, Hatice Akkurt, Keith Eckerman, Ida Lee, Sotira Yiacoumi, Daniel Hollenbach, D. Dean, M. Ramsey-Musolf, Michael Smith, Eric Lingerfelt, Kim Buckner, and Caroline Nesaraja

Subjects
Engineering, Aeronautics, business.industry, Annual report, business
Published
2009
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