Paulius Micikevicius

According to our database, Paulius Micikevicius authored at least 19 papers between 2002 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Microscaling Data Formats for Deep Learning.

Bita Darvish Rouhani, Ritchie Zhao, Ankit More, Mathew Hall, Alireza Khodamoradi, Summer Deng, Dhruv Choudhary, Marius Cornea, Eric Dellinger, Kristof Denolf, Dusan Stosic, Venmugil Elango, Maximilian Golub, Alexander Heinecke, Phil James-Roxby, Dharmesh Jani, Gaurav Kolhe, Martin Langhammer, Ada Li, Levi Melnick, Maral Mesmakhosroshahi, Andres Rodriguez, Michael Schulte, Rasoul Shafipour, Lei Shao, Michael Y. Siu, Pradeep Dubey, Paulius Micikevicius, Maxim Naumov, Colin Verilli, Ralph Wittig, Doug Burger, Eric S. Chung

CoRR, 2023

2022

FP8 Formats for Deep Learning.

Paulius Micikevicius, Dusan Stosic, Neil Burgess, Marius Cornea, Pradeep Dubey, Richard Grisenthwaite, Sangwon Ha, Alexander Heinecke, Patrick Judd, John Kamalu, Naveen Mellempudi, Stuart F. Oberman, Mohammad Shoeybi, Michael Y. Siu, Hao Wu

CoRR, 2022

2021

Accelerating Sparse Deep Neural Networks.

Asit K. Mishra, Jorge Albericio Latorre, Jeff Pool, Darko Stosic, Dusan Stosic, Ganesh Venkatesh, Chong Yu, Paulius Micikevicius

CoRR, 2021

2020

MLPerf: An Industry Standard Benchmark Suite for Machine Learning Performance.

Peter Mattson, Hanlin Tang, Gu-Yeon Wei, Carole-Jean Wu, Vijay Janapa Reddi, Christine Cheng, Cody Coleman, Greg Diamos, David Kanter, Paulius Micikevicius, David A. Patterson, Guenther Schmuelling

IEEE Micro, 2020

Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation.

Hao Wu, Patrick Judd, Xiaojie Zhang, Mikhail Isaev, Paulius Micikevicius

CoRR, 2020

MLPerf Training Benchmark.

Peter Mattson, Christine Cheng, Gregory F. Diamos, Cody Coleman, Paulius Micikevicius, David A. Patterson, Hanlin Tang, Gu-Yeon Wei, Peter Bailis, Victor Bittorf, David Brooks, Dehao Chen, Debo Dutta, Udit Gupta, Kim M. Hazelwood, Andy Hock, Xinyuan Huang, Daniel Kang, David Kanter, Naveen Kumar, Jeffery Liao, Deepak Narayanan, Tayo Oguntebi, Gennady Pekhimenko, Lillian Pentecost, Vijay Janapa Reddi, Taylor Robie, Tom St. John, Carole-Jean Wu, Lingjie Xu, Cliff Young, Matei Zaharia

Proceedings of Machine Learning and Systems 2020, 2020

MLPerf Inference Benchmark.

Vijay Janapa Reddi, Christine Cheng, David Kanter, Peter Mattson, Guenther Schmuelling, Carole-Jean Wu, Brian Anderson, Maximilien Breughe, Mark Charlebois, William Chou, Ramesh Chukka, Cody Coleman, Sam Davis, Pan Deng, Greg Diamos, Jared Duke, Dave Fick, J. Scott Gardner, Itay Hubara, Sachin Idgunji, Thomas B. Jablin, Jeff Jiao, Tom St. John, Pankaj Kanwar, David Lee, Jeffery Liao, Anton Lokhmotov, Francisco Massa, Peng Meng, Paulius Micikevicius, Colin Osborne, Gennady Pekhimenko, Arun Tejusve Raghunath Rajan, Dilip Sequeira, Ashish Sirasao, Fei Sun, Hanlin Tang, Michael Thomson, Frank Wei, Ephrem Wu, Lingjie Xu, Koichi Yamada, Bing Yu, George Yuan, Aaron Zhong, Peizhao Zhang, Yuchen Zhou

Proceedings of the 47th ACM/IEEE Annual International Symposium on Computer Architecture, 2020

2019

MLPerf Training Benchmark.

Peter Mattson, Christine Cheng, Cody Coleman, Greg Diamos, Paulius Micikevicius, David A. Patterson, Hanlin Tang, Gu-Yeon Wei, Peter Bailis, Victor Bittorf, David Brooks, Dehao Chen, Debojyoti Dutta, Udit Gupta, Kim M. Hazelwood, Andrew Hock, Xinyuan Huang, Bill Jia, Daniel Kang, David Kanter, Naveen Kumar, Jeffery Liao, Guokai Ma, Deepak Narayanan, Tayo Oguntebi, Gennady Pekhimenko, Lillian Pentecost, Vijay Janapa Reddi, Taylor Robie, Tom St. John, Carole-Jean Wu, Lingjie Xu, Cliff Young, Matei Zaharia

CoRR, 2019

2018

OpenSeq2Seq: extensible toolkit for distributed and mixed precision training of sequence-to-sequence models.

Oleksii Kuchaiev, Boris Ginsburg, Igor Gitman, Vitaly Lavrukhin, Carl Case, Paulius Micikevicius

CoRR, 2018

Mixed Precision Training.

Paulius Micikevicius, Sharan Narang, Jonah Alben, Gregory F. Diamos, Erich Elsen, David García, Boris Ginsburg, Michael Houston, Oleksii Kuchaiev, Ganesh Venkatesh, Hao Wu

Proceedings of the 6th International Conference on Learning Representations, 2018

2015

Fusing convolution kernels through tiling.

Mahesh Ravishankar, Paulius Micikevicius, Vinod Grover

Proceedings of the 2nd ACM SIGPLAN International Workshop on Libraries, 2015

2014

Scaling the Power Wall: A Path to Exascale.

Oreste Villa, Daniel R. Johnson, Mike O'Connor, Evgeny Bolotin, David W. Nellans, Justin Luitjens, Nikolai Sakharnykh, Peng Wang, Paulius Micikevicius, Anthony Scudiero, Stephen W. Keckler, William J. Dally

Proceedings of the International Conference for High Performance Computing, 2014

2013

Progress towards accelerating HOMME on hybrid multi-core systems.

Ilene Carpenter, Rick Archibald, Katherine J. Evans, Jeffrey M. Larkin, Paulius Micikevicius, Matthew R. Norman, James Rosinski, Jim Schwarzmeier, Mark A. Taylor

Int. J. High Perform. Comput. Appl., 2013

2009

3D finite difference computation on GPUs using CUDA.

Paulius Micikevicius

Proceedings of 2nd Workshop on General Purpose Processing on Graphics Processing Units, 2009

2007

Exploring Topological Properties of NMR Graphs.

Paulius Micikevicius, Narsingh Deo

Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, 2007

2005

Cluster Computing for Determining Three-Dimensional Protein Structure.

Paulius Micikevicius, Narsingh Deo

J. Supercomput., 2005

2004

General Parallel Computation on Commodity Graphics Hardware: Case Study with the All-Pairs Shortest Paths Problem.

Paulius Micikevicius

Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications, 2004

2002

Applying Mixed Reality to Entertainment.

Christopher B. Stapleton, Charles E. Hughes, J. Michael Moshell, Paulius Micikevicius, Marty Altman

Computer, 2002

Coarse-Grained Parallelization of Distance-Bound Smoothing for the Molecular Conformation Problem.

Narsingh Deo, Paulius Micikevicius

Proceedings of the Distributed Computing, 2002