Publications

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2022
Fortenberry, A., S. Tomov, and K. Wong, Extending MAGMA Portability with OneAPI , Dallas, TX, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC22), ACM Student Research Competition, November 2022.  (1.33 MB)
2021
Tomov, S., K. Wong, R. Febbo, and J. Halloy, Linear Algebra Prepara.on for Emergent Neural Network Architectures: MAGMA, BLAS, and Batched GPU Computing , Virtual, LAPENNA Workshop, November 2021.  (17.8 MB)
2020
Wong, K., S. Tomov, D. Nichols, R. Febbo, F. Lopez, J. Halloy, and X. Ma, How to Build Your Own Deep Neural Network : PEARC20, July 2020.  (18.8 MB)
Tomov, S., K. Wong, J. Dongarra, R. Archibald, E. Chow, E. D'Azevedo, M. Eisenbach, R. Febbo, F. Lopez, D. Nichols, et al., Integrating Deep Learning in Domain Science at Exascale (MagmaDNN) , virtual, DOD HPCMP seminar, December 2020.  (11.12 MB)
Archibald, R., E. Chow, E. D'Azevedo, J. Dongarra, M. Eisenbach, R. Febbo, F. Lopez, D. Nichols, S. Tomov, K. Wong, et al., “Integrating Deep Learning in Domain Sciences at Exascale,” Innovative Computing Laboratory Technical Report, no. ICL-UT-20-10: University of Tennessee, August 2020.  (1.09 MB)
Archibald, R., E. Chow, E. D'Azevedo, J. Dongarra, M. Eisenbach, R. Febbo, F. Lopez, D. Nichols, S. Tomov, K. Wong, et al., “Integrating Deep Learning in Domain Sciences at Exascale,” 2020 Smoky Mountains Computational Sciences and Engineering Conference (SMC 2020), August 2020.
2019
Wong, K., S. Tomov, and J. Dongarra, “Hands-on Research and Training in High-Performance Data Sciences, Data Analytics, and Machine Learning for Emerging Environments,” ISC High Performance, Frankfurt, Germany, Springer International Publishing, June 2019.  (1016.52 KB)
Ng, L., S. Chen, A. Gessinger, D. Nichols, S. Cheng, A. Meenasorna, K. Wong, S. Tomov, A. Haidar, E. D'Azevedo, et al., MagmaDNN 0.2 High-Performance Data Analytics for Manycore GPUs and CPUs : University of Tennessee, January 2019.  (7.84 MB)
Nichols, D., K. Wong, S. Tomov, L. Ng, S. Chen, and A. Gessinger, “MagmaDNN: Accelerated Deep Learning Using MAGMA,” Practice and Experience in Advanced Research Computing (PEARC ’19), Chicago, IL, ACM, July 2019.  (1.09 MB)
Nichols, D., N-S. Tomov, F. Betancourt, S. Tomov, K. Wong, and J. Dongarra, “MagmaDNN: Towards High-Performance Data Analytics and Machine Learning for Data-Driven Scientific Computing,” ISC High Performance, Frankfurt, Germany, Springer International Publishing, June 2019.  (1.37 MB) (8.72 MB)
Betancourt, F., K. Wong, E. Asemota, Q. Marshall, D. Nichols, and S. Tomov, “OpenDIEL: A Parallel Workflow Engine and DataAnalytics Framework,” Practice and Experience in Advanced Research Computing (PEARC ’19), Chicago, IL, ACM, July 2019.  (1.48 MB)
2018
Cheng, X., A. Soma, E. D'Azevedo, K. Wong, and S. Tomov, Accelerating 2D FFT: Exploit GPU Tensor Cores through Mixed-Precision , Dallas, TX, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC18), ACM Student Research Poster, November 2018.  (740.37 KB)
2017
Ng, L., K. Wong, A. Haidar, S. Tomov, and J. Dongarra, MagmaDNN – High-Performance Data Analytics for Manycore GPUs and CPUs , Knoxville, TN, 2017 Summer Research Experiences for Undergraduate (REU), Presentation, December 2017.  (5.06 MB)