Jan Balewski

According to our database, Jan Balewski authored at least 11 papers between 2020 and 2023.

Collaborative distances:

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

2023

Quantum Computing and Visualization: A Disruptive Technological Change Ahead.

E. Wes Bethel, Mercy G. Amankwah, Jan Balewski, Roel Van Beeumen, Daan Camps, Daniel Huang, Talita Perciano

IEEE Computer Graphics and Applications, 2023

Efficient Quantum Counting and Quantum Content-Addressable Memory for DNA Similarity.

Jan Balewski, Daan Camps, Katherine Klymko, Andrew Tritt

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2023

2022

Scaling and Benchmarking an Evolutionary Algorithm for Constructing Biophysical Neuronal Models.

Alexander Ladd, Kyung Geun Kim, Jan Balewski, Kristofer E. Bouchard, Roy Ben-Shalom

Frontiers Neuroinformatics, 2022

Time-series ML-regression on Graphcore IPU-M2000 and Nvidia A100.

Jan Balewski, Zhenying Liu, Alexander Tsyplikhin, Manuel Lopez Roland, Kristofer E. Bouchard

Proceedings of the IEEE/ACM International Workshop on Performance Modeling, 2022

Using Multi-Resolution Data to Accelerate Neural Network Training in Scientific Applications.

Kewei Wang, Sunwoo Lee, Jan Balewski, Alex Sim, Peter Nugent, Ankit Agrawal, Alok N. Choudhary, Kesheng Wu, Wei-Keng Liao

Proceedings of the 22nd IEEE International Symposium on Cluster, 2022

2021

The Case for Strong Scaling in Deep Learning: Training Large 3D CNNs With Hybrid Parallelism.

Yosuke Oyama, Naoya Maruyama, Nikoli Dryden, Erin McCarthy, Peter Harrington, Jan Balewski, Satoshi Matsuoka, Peter Nugent, Brian Van Essen

IEEE Trans. Parallel Distributed Syst., 2021

Co-design Center for Exascale Machine Learning Technologies (ExaLearn).

Francis J. Alexander, James A. Ang, Jenna A. Bilbrey, Jan Balewski, Tiernan Casey, Ryan Chard, Jong Choi, Sutanay Choudhury, Bert J. Debusschere, Anthony M. DeGennaro, Nikoli Dryden, J. Austin Ellis, Ian T. Foster, Cristina Garcia-Cardona, Sayan Ghosh, Peter Harrington, Yunzhi Huang, Shantenu Jha, Travis Johnston, Ai Kagawa, Ramakrishnan Kannan, Neeraj Kumar, Zhengchun Liu, Naoya Maruyama, Satoshi Matsuoka, Erin McCarthy, Jamaludin Mohd-Yusof, Peter Nugent, Yosuke Oyama, Thomas Proffen, David Pugmire, Sivasankaran Rajamanickam, Vinay Ramakrishniah, Malachi Schram, Sudip K. Seal, Ganesh Sivaraman, Christine Sweeney, Li Tan, Rajeev Thakur, Brian Van Essen, Logan T. Ward, Paul M. Welch, Michael Wolf, Sotiris S. Xantheas, Kevin G. Yager, Shinjae Yoo, Byung-Jun Yoon

Int. J. High Perform. Comput. Appl., 2021

MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems.

Steven Farrell, Murali Emani, Jacob Balma, Lukas Drescher, Aleksandr Drozd, Andreas Fink, Geoffrey C. Fox, David Kanter, Thorsten Kurth, Peter Mattson, Dawei Mu, Amit Ruhela, Kento Sato, Koichi Shirahata, Tsuguchika Tabaru, Aristeidis Tsaris, Jan Balewski, Ben Cumming, Takumi Danjo, Jens Domke, Takaaki Fukai, Naoto Fukumoto, Tatsuya Fukushi, Balazs Gerofi, Takumi Honda, Toshiyuki Imamura, Akihiko Kasagi, Kentaro Kawakami, Shuhei Kudo, Akiyoshi Kuroda, Maxime Martinasso, Satoshi Matsuoka, Henrique Mendonça, Kazuki Minami, Prabhat Ram, Takashi Sawada, Mallikarjun Shankar, Tom St. John, Akihiro Tabuchi, Venkatram Vishwanath, Mohamed Wahib, Masafumi Yamazaki, Junqi Yin

CoRR, 2021

MLPerf™ HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems.

Steven Farrell, Murali Emani, Jacob Balma, Lukas Drescher, Aleksandr Drozd, Andreas Fink, Geoffrey C. Fox, David Kanter, Thorsten Kurth, Peter Mattson, Dawei Mu, Amit Ruhela, Kento Sato, Koichi Shirahata, Tsuguchika Tabaru, Aristeidis Tsaris, Jan Balewski, Ben Cumming, Takumi Danjo, Jens Domke, Takaaki Fukai, Naoto Fukumoto, Tatsuya Fukushi, Balazs Gerofi, Takumi Honda, Toshiyuki Imamura, Akihiko Kasagi, Kentaro Kawakami, Shuhei Kudo, Akiyoshi Kuroda, Maxime Martinasso, Satoshi Matsuoka, Henrique Mendonça, Kazuki Minami, Prabhat Ram, Takashi Sawada, Mallikarjun Shankar, Tom St. John, Akihiro Tabuchi, Venkatram Vishwanath, Mohamed Wahib, Masafumi Yamazaki, Junqi Yin

Proceedings of the IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments, 2021

Asynchronous I/O Strategy for Large-Scale Deep Learning Applications.

Sunwoo Lee, Qiao Kang, Kewei Wang, Jan Balewski, Alex Sim, Ankit Agrawal, Alok N. Choudhary, Peter Nugent, Kesheng Wu, Wei-keng Liao

Proceedings of the 28th IEEE International Conference on High Performance Computing, 2021

2020

Atmospheric Blocking Pattern Recognition in Global Climate Model Simulation Data.

Grzegorz Muszynski, Prabhat, Jan Balewski, Karthik Kashinath, Michael F. Wehner, Vitaliy Kurlin

Proceedings of the 25th International Conference on Pattern Recognition, 2020