Gregory Frederick Diamos

According to our database, Gregory Frederick Diamos authored at least 46 papers between 2008 and 2024.

Collaborative distances:

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

2024

Banishing LLM Hallucinations Requires Rethinking Generalization.

Johnny Li, Saksham Consul, Eda Zhou, James Wong, Naila Farooqui, Yuxin Ye, Nithyashree Manohar, Zhuxiaona Wei, Tian Wu, Ben Echols, Sharon Zhou, Gregory F. Diamos

CoRR, 2024

2023

Federated benchmarking of medical artificial intelligence with MedPerf.

Alexandros Karargyris, Renato Umeton, Micah J. Sheller, Alejandro Aristizabal, Johnu George, Anna Wuest, Sarthak Pati, Hasan Kassem, Maximilian Zenk, Ujjwal Baid, Prakash Narayana Moorthy, Alexander Chowdhury, Junyi Guo, Sahil S. Nalawade, Jacob Rosenthal, David Kanter, Maria Xenochristou, Daniel J. Beutel, Verena Chung, Timothy Bergquist, James A. Eddy, Abubakar Abid, Lewis Tunstall, Omar Sanseviero, Dimitrios Dimitriadis, Yiming Qian, Xinxing Xu, Yong Liu, Rick Siow Mong Goh, Srini Bala, Victor Bittorf, Sreekar Reddy Puchala, Biagio Ricciuti, Soujanya Samineni, Eshna Sengupta, Akshay Chaudhari, Cody Coleman, Bala Desinghu, Gregory F. Diamos, Debo Dutta, Diane Feddema, Grigori Fursin, Xinyuan Huang, Satyananda Kashyap, Nicholas D. Lane, Indranil Mallick, Pietro Mascagni, Virendra Mehta, Cassiano Ferro Moraes, Vivek Natarajan, Nikola Nikolov, Nicolas Padoy, Gennady Pekhimenko, Vijay Janapa Reddi, G. Anthony Reina, Pablo Ribalta, Abhishek Singh, Jayaraman J. Thiagarajan, Jacob Albrecht, Thomas Wolf, Geralyn Miller, Huazhu Fu, Prashant Shah, Daguang Xu, Poonam Yadav, David Talby, Mark M. Awad, Jeremy P. Howard, Michael Rosenthal, Luigi Marchionni, Massimo Loda, Jason M. Johnson, Spyridon Bakas, Peter Mattson

Nat. Mac. Intell., July, 2023

DataPerf: Benchmarks for Data-Centric AI Development.

Mark Mazumder, Colby R. Banbury, Xiaozhe Yao, Bojan Karlas, William Gaviria Rojas, Sudnya Frederick Diamos, Greg Diamos, Lynn He, Alicia Parrish, Hannah Rose Kirk, Jessica Quaye, Charvi Rastogi, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Will Cukierski, Juan Ciro, Lora Aroyo, Bilge Acun, Lingjiao Chen, Mehul Raje, Max Bartolo, Evan Sabri Eyuboglu, Amirata Ghorbani, Emmett D. Goodman, Addison Howard, Oana Inel, Tariq Kane, Christine R. Kirkpatrick, D. Sculley, Tzu-Sheng Kuo, Jonas W. Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen K. Paritosh, Ce Zhang, James Y. Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

DataPerf: Benchmarks for Data-Centric AI Development.

Mark Mazumder, Colby R. Banbury, Xiaozhe Yao, Bojan Karlas, William Gaviria Rojas, Sudnya Frederick Diamos, Greg Diamos, Lynn He, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Juan Ciro, Lora Aroyo, Bilge Acun, Sabri Eyuboglu, Amirata Ghorbani, Emmett D. Goodman, Tariq Kane, Christine R. Kirkpatrick, Tzu-Sheng Kuo, Jonas Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen K. Paritosh, Ce Zhang, James Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi

CoRR, 2022

2021

The People's Speech: A Large-Scale Diverse English Speech Recognition Dataset for Commercial Usage.

Daniel Galvez, Greg Diamos, Juan Ciro, Juan Felipe Cerón, Keith Achorn, Anjali Gopi, David Kanter, Maximilian Lam, Mark Mazumder, Vijay Janapa Reddi

CoRR, 2021

MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation.

Alexandros Karargyris, Renato Umeton, Micah J. Sheller, Alejandro Aristizabal, Johnu George, Srini Bala, Daniel J. Beutel, Victor Bittorf, Akshay Chaudhari, Alexander Chowdhury, Cody Coleman, Bala Desinghu, Gregory F. Diamos, Debo Dutta, Diane Feddema, Grigori Fursin, Junyi Guo, Xinyuan Huang, David Kanter, Satyananda Kashyap, Nicholas D. Lane, Indranil Mallick, Pietro Mascagni, Virendra Mehta, Vivek Natarajan, Nikola Nikolov, Nicolas Padoy, Gennady Pekhimenko, Vijay Janapa Reddi, G. Anthony Reina, Pablo Ribalta, Jacob Rosenthal, Abhishek Singh, Jayaraman J. Thiagarajan, Anna Wuest, Maria Xenochristou, Daguang Xu, Poonam Yadav, Michael Rosenthal, Massimo Loda, Jason M. Johnson, Peter Mattson

CoRR, 2021

Data Engineering for Everyone.

Vijay Janapa Reddi, Greg Diamos, Pete Warden, Peter Mattson, David Kanter

CoRR, 2021

Multilingual Spoken Words Corpus.

Mark Mazumder, Sharad Chitlangia, Colby R. Banbury, Yiping Kang, Juan Ciro, Keith Achorn, Daniel Galvez, Mark Sabini, Peter Mattson, David Kanter, Greg Diamos, Pete Warden, Josh Meyer, Vijay Janapa Reddi

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

The People's Speech: A Large-Scale Diverse English Speech Recognition Dataset for Commercial Usage.

Daniel Galvez, Greg Diamos, Juan Torres, Keith Achorn, Juan Felipe Cerón, Anjali Gopi, David Kanter, Max Lam, Mark Mazumder, Vijay Janapa Reddi

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 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

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 the Third Conference on Machine Learning and Systems, 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

Fast Spectrogram Inversion Using Multi-Head Convolutional Neural Networks.

Sercan Ömer Arik, Heewoo Jun, Gregory Frederick Diamos

IEEE Signal Process. Lett., 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

EPNAS: Efficient Progressive Neural Architecture Search.

Yanqi Zhou, Peng Wang, Sercan Ömer Arik, Haonan Yu, Syed Zawad, Feng Yan, Greg Diamos

CoRR, 2019

Coloring Big Graphs with AlphaGoZero.

Jiayi Huang, Md. Mostofa Ali Patwary, Gregory F. Diamos

CoRR, 2019

Beyond human-level accuracy: computational challenges in deep learning.

Joel Hestness, Newsha Ardalani, Gregory F. Diamos

Proceedings of the 24th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2019

Language Modeling at Scale.

Md. Mostofa Ali Patwary, Milind Chabbi, Heewoo Jun, Jiaji Huang, Greg Diamos, Kenneth Church

Proceedings of the 2019 IEEE International Parallel and Distributed Processing Symposium, 2019

2018

Resource-Efficient Neural Architect.

Yanqi Zhou, Siavash Ebrahimi, Sercan Ömer Arik, Haonan Yu, Hairong Liu, Greg Diamos

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

2017

Deep Learning Scaling is Predictable, Empirically.

Joel Hestness, Sharan Narang, Newsha Ardalani, Gregory F. Diamos, Heewoo Jun, Hassan Kianinejad, Md. Mostofa Ali Patwary, Yang Yang, Yanqi Zhou

CoRR, 2017

Block-Sparse Recurrent Neural Networks.

Sharan Narang, Eric Undersander, Gregory F. Diamos

CoRR, 2017

Deep Voice: Real-time Neural Text-to-Speech.

Sercan Ömer Arik, Mike Chrzanowski, Adam Coates, Greg Diamos, Andrew Gibiansky, Yongguo Kang, Xian Li, John Miller, Jonathan Raiman, Shubho Sengupta, Mohammad Shoeybi

CoRR, 2017

Deep Voice 2: Multi-Speaker Neural Text-to-Speech.

Andrew Gibiansky, Sercan Ömer Arik, Gregory Frederick Diamos, John Miller, Kainan Peng, Wei Ping, Jonathan Raiman, Yanqi Zhou

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

The road to exascale AI.

Gregory F. Diamos

Proceedings of the Workshop on Trends in Machine-Learning (and impact on computer architecture), 2017

Deep Voice: Real-time Neural Text-to-Speech.

Sercan Ömer Arik, Mike Chrzanowski, Adam Coates, Gregory Frederick Diamos, Andrew Gibiansky, Yongguo Kang, Xian Li, John Miller, Andrew Y. Ng, Jonathan Raiman, Shubho Sengupta, Mohammad Shoeybi

Proceedings of the 34th International Conference on Machine Learning, 2017

Exploring Sparsity in Recurrent Neural Networks.

Sharan Narang, Greg Diamos, Shubho Sengupta, Erich Elsen

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Persistent RNNs: Stashing Recurrent Weights On-Chip.

Greg Diamos, Shubho Sengupta, Bryan Catanzaro, Mike Chrzanowski, Adam Coates, Erich Elsen, Jesse H. Engel, Awni Y. Hannun, Sanjeev Satheesh

Proceedings of the 33nd International Conference on Machine Learning, 2016

Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin.

Dario Amodei, Sundaram Ananthanarayanan, Rishita Anubhai, Jingliang Bai, Eric Battenberg, Carl Case, Jared Casper, Bryan Catanzaro, Jingdong Chen, Mike Chrzanowski, Adam Coates, Greg Diamos, Erich Elsen, Jesse H. Engel, Linxi Fan, Christopher Fougner, Awni Y. Hannun, Billy Jun, Tony Han, Patrick LeGresley, Xiangang Li, Libby Lin, Sharan Narang, Andrew Y. Ng, Sherjil Ozair, Ryan Prenger, Sheng Qian, Jonathan Raiman, Sanjeev Satheesh, David Seetapun, Shubho Sengupta, Chong Wang, Yi Wang, Zhiqian Wang, Bo Xiao, Yan Xie, Dani Yogatama, Jun Zhan, Zhenyao Zhu

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Deep Speech 2: End-to-End Speech Recognition in English and Mandarin.

Dario Amodei, Rishita Anubhai, Eric Battenberg, Carl Case, Jared Casper, Bryan Catanzaro, Jingdong Chen, Mike Chrzanowski, Adam Coates, Greg Diamos, Erich Elsen, Jesse H. Engel, Linxi Fan, Christopher Fougner, Tony Han, Awni Y. Hannun, Billy Jun, Patrick LeGresley, Libby Lin, Sharan Narang, Andrew Y. Ng, Sherjil Ozair, Ryan Prenger, Jonathan Raiman, Sanjeev Satheesh, David Seetapun, Shubho Sengupta, Yi Wang, Zhiqian Wang, Chong Wang, Bo Xiao, Dani Yogatama, Jun Zhan, Zhenyao Zhu

CoRR, 2015

2014

Deep Speech: Scaling up end-to-end speech recognition.

Awni Y. Hannun, Carl Case, Jared Casper, Bryan Catanzaro, Greg Diamos, Erich Elsen, Ryan Prenger, Sanjeev Satheesh, Shubho Sengupta, Adam Coates, Andrew Y. Ng

CoRR, 2014

Red Fox: An Execution Environment for Relational Query Processing on GPUs.

Haicheng Wu, Gregory F. Diamos, Tim Sheard, Molham Aref, Sean Baxter, Michael Garland, Sudhakar Yalamanchili

Proceedings of the 12th Annual IEEE/ACM International Symposium on Code Generation and Optimization, 2014

2013

Relational algorithms for multi-bulk-synchronous processors.

Gregory Frederick Diamos, Haicheng Wu, Jin Wang, Ashwin Sanjay Lele, Sudhakar Yalamanchili

Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2013

2012

Characterization and transformation of unstructured control flow in bulk synchronous GPU applications.

Haicheng Wu, Gregory F. Diamos, Jin Wang, Si Li, Sudhakar Yalamanchili

Int. J. High Perform. Comput. Appl., 2012

Kernel Weaver: Automatically Fusing Database Primitives for Efficient GPU Computation.

Haicheng Wu, Gregory Frederick Diamos, Srihari Cadambi, Sudhakar Yalamanchili

Proceedings of the 45th Annual IEEE/ACM International Symposium on Microarchitecture, 2012

Simultaneous branch and warp interweaving for sustained GPU performance.

Nicolas Brunie, Caroline Collange, Gregory Frederick Diamos

Proceedings of the 39th International Symposium on Computer Architecture (ISCA 2012), 2012

Optimizing Data Warehousing Applications for GPUs Using Kernel Fusion/Fission.

Haicheng Wu, Gregory F. Diamos, Jin Wang, Srihari Cadambi, Sudhakar Yalamanchili, Srimat T. Chakradhar

Proceedings of the 26th IEEE International Parallel and Distributed Processing Symposium Workshops & PhD Forum, 2012

Dynamic compilation of data-parallel kernels for vector processors.

Andrew Kerr, Gregory Frederick Diamos, Sudhakar Yalamanchili

Proceedings of the 10th Annual IEEE/ACM International Symposium on Code Generation and Optimization, 2012

2011

Harmony: an execution model for heterogeneous systems.

Gregory Frederick Diamos

PhD thesis, 2011

SIMD re-convergence at thread frontiers.

Gregory Frederick Diamos, Benjamin Ashbaugh, Subramaniam Maiyuran, Andrew Kerr, Haicheng Wu, Sudhakar Yalamanchili

Proceedings of the 44rd Annual IEEE/ACM International Symposium on Microarchitecture, 2011

A framework for dynamically instrumenting GPU compute applications within GPU Ocelot.

Naila Farooqui, Andrew Kerr, Gregory Frederick Diamos, Sudhakar Yalamanchili, Karsten Schwan

Proceedings of 4th Workshop on General Purpose Processing on Graphics Processing Units, 2011

2010

Speculative execution on multi-GPU systems.

Gregory F. Diamos, Sudhakar Yalamanchili

Proceedings of the 24th IEEE International Symposium on Parallel and Distributed Processing, 2010

Modeling GPU-CPU workloads and systems.

Andrew Kerr, Gregory F. Diamos, Sudhakar Yalamanchili

Proceedings of 3rd Workshop on General Purpose Processing on Graphics Processing Units, 2010

Ocelot: a dynamic optimization framework for bulk-synchronous applications in heterogeneous systems.

Gregory Frederick Diamos, Andrew Kerr, Sudhakar Yalamanchili, Nathan Clark

Proceedings of the 19th International Conference on Parallel Architectures and Compilation Techniques, 2010

2009

A characterization and analysis of PTX kernels.

Andrew Kerr, Gregory F. Diamos, Sudhakar Yalamanchili

Proceedings of the 2009 IEEE International Symposium on Workload Characterization, 2009

2008

Harmony: an execution model and runtime for heterogeneous many core systems.

Gregory F. Diamos, Sudhakar Yalamanchili

Proceedings of the 17th International Symposium on High-Performance Distributed Computing (HPDC-17 2008), 2008