Jacob Balma

According to our database, Jacob Balma authored at least 8 papers between 2019 and 2021.

Collaborative distances:

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

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

The Convergence of HPC, AI and Big Data in Rapid-Response to the COVID-19 Pandemic.

Sreenivas R. Sukumar, Jacob A. Balma, Christopher D. Rickett, Kristyn J. Maschhoff, Joseph Landman, Charles R. Yates, Amar G. Chittiboyina, Yuri K. Peterson, Aaron Vose, Kendall G. Byler, Jérôme Baudry, Ikhlas A. Khan

Proceedings of the Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation, 2021

Survival of the Fittest Amidst the Cambrian Explosion of Processor Architectures for Artificial Intelligence : Invited Paper.

Sreenivas R. Sukumar, Jacob Balma, Cong Xu, Sergey Serebryakov

Proceedings of the IEEE/ACM Programming Environments for Heterogeneous Computing, 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

2020

Deep Learning Predicts Protein-Ligand Interactions.

Jacob Balma, Aaron D. Vose, Yuri K. Peterson, Amar G. Chittiboyina, Pankaj Pandey, Charles R. Yates, Ikhlas A. Khan, Sreenivas R. Sukumar

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019

PharML.Bind: Pharmacologic Machine Learning for Protein-Ligand Interactions.

Aaron D. Vose, Jacob Balma, Damon Farnsworth, Kaylie Anderson, Yuri K. Peterson

CoRR, 2019

Recombination of Artificial Neural Networks.

Aaron Vose, Jacob Balma, Alex Heye, Alessandro Rigazzi, Charles Siegel, Diana Moise, Benjamin Robbins, Rangan Sukumar

CoRR, 2019

GPCNeT: designing a benchmark suite for inducing and measuring contention in HPC networks.

Sudheer Chunduri, Taylor L. Groves, Peter Mendygral, Brian Austin, Jacob Balma, Krishna Kandalla, Kalyan Kumaran, Glenn K. Lockwood, Scott Parker, Steven Warren, Nathan Wichmann, Nicholas J. Wright

Proceedings of the International Conference for High Performance Computing, 2019