| Benchmarking gpu-accelerated edge devices J Jo, S Jeong, P Kang 2020 IEEE international conference on big data and smart computing (BigComp …, 2020 | 47 | 2020 |
| Benchmarking modern edge devices for ai applications P Kang, J Jo IEICE TRANSACTIONS on Information and Systems 104 (3), 394-403, 2021 | 27 | 2021 |
| A taste of scientific computing on the GPU-accelerated edge device P Kang, S Lim IEEE Access 8, 208337-208347, 2020 | 15 | 2020 |
| Modular, fine-grained adaptation of parallel programs P Kang, NKC Selvarasu, N Ramakrishnan, CJ Ribbens, DK Tafti, ... Computational Science–ICCS 2009: 9th International Conference Baton Rouge …, 2009 | 14 | 2009 |
| An evaluation of modern accelerator-based edge devices for object detection applications P Kang, A Somtham Mathematics 10 (22), 4299, 2022 | 13 | 2022 |
| Function call interception techniques P Kang Software: Practice and Experience 48 (3), 385-401, 2018 | 13 | 2018 |
| Modular implementation of adaptive decisions in stochastic simulations P Kang, Y Cao, N Ramakrishnan, CJ Ribbens, S Varadarajan Proceedings of the 2009 ACM symposium on Applied Computing, 995-1001, 2009 | 10 | 2009 |
| Maintainable and reusable scientific software adaptation: democratizing scientific software adaptation P Kang, E Tilevich, S Varadarajan, N Ramakrishnan Proceedings of the tenth international conference on Aspect-oriented …, 2011 | 8 | 2011 |
| Dynamic tuning of algorithmic parameters of parallel scientific codes P Kang, NKC Selvarasu, N Ramakrishnan, CJ Ribbens, DK Tafti, ... Procedia Computer Science 1 (1), 145-153, 2010 | 8 | 2010 |
| Programming for high-performance computing on edge accelerators P Kang Mathematics 11 (4), 1055, 2023 | 7 | 2023 |
| Implementing scientific simulations on GPU-accelerated edge devices S Lim, P Kang 2020 International Conference on Information Networking (ICOIN), 756-760, 2020 | 7 | 2020 |
| Modular implementation of dynamic algorithm switching in parallel simulations P Kang Cluster Computing 15, 321-332, 2012 | 6 | 2012 |
| Implementing modular adaptation of scientific software P Kang, NKC Selvarasu, N Ramakrishnan, CJ Ribbens, DK Tafti, Y Cao, ... Journal of Computational Science 3 (1-2), 28-45, 2012 | 6 | 2012 |
| A self-adapting system for linear solver selection V Eijkhout, E Fuentes, N Ramakrishnan, P Kang, S Bhowmick, D Keyes, ... Proc. 1st int’l workshop on automatic performance tuning (iWAPT2006), 44-53, 2006 | 6 | 2006 |
| Adaptive code collage: a framework to transparently modify scientific codes P Kang, N Ramakrishnan, C Ribbens, S Varadarajan, M Heffner Computing in Science & Engineering 14 (1), 52-63, 2011 | 5 | 2011 |
| GPU-accelerated stochastic simulation of biochemical networks P Kang IEICE TRANSACTIONS on Information and Systems 101 (3), 786-790, 2018 | 4 | 2018 |
| Software analysis techniques for detecting data race P Kang IEICE TRANSACTIONS on Information and Systems 100 (11), 2674-2682, 2017 | 4 | 2017 |
| The adaptive code kitchen: Flexible tools for dynamic application composition P Kang, M Heffner, J Mukherjee, N Ramakrishnan, S Varadarajan, ... 2007 IEEE International Parallel and Distributed Processing Symposium, 1-8, 2007 | 3 | 2007 |
| OpenACC Parallelization of Stochastic Simulations on GPUs P Kang IEICE TRANSACTIONS on Information and Systems 102 (8), 1565-1568, 2019 | 1 | 2019 |
| Dynamic Algorithm Switching in Parallel Simulations using AOP. P Kang Journal of Information Science & Engineering 34 (6), 2018 | 1 | 2018 |
Naren RamakrishnanThomas L. Phillips Professor, Virginia Tech在 cs.vt.edu 的电子邮件经过验证
