Sarunya Pumma
Sarunya Pumma
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Towards Scalable Deep Learning via I/O Analysis and Optimization
S Pumma, M Si, W Feng, P Balaji
IEEE High Performance Computing and Communications (HPCC), 2017
Parallel I/O Optimizations for Scalable Deep Learning
S Pumma, M Si, W Feng, P Balaji
International Conference on Parallel and Distributed Systems (ICPADS), 2017
Scalable Deep Learning via I/O Analysis and Optimization
S Pumma, M Si, W Feng, P Balaji
ACM Trans. Parallel Comput. 6 (2), 6:1--6:34, 2019
A runtime estimation framework for ALICE
S Pumma, W Feng, P Phunchongharn, S Chapeland, T Achalakul
Future Generation Computer Systems 72, 65-77, 2017
Automatic VM allocation for scientific application
S Pumma, T Achalakul, L Xiaorong
Workshop on Scalable Computing for Big Data Analytics (SC-BDA), in …, 2012
PaPar: A parallel data partitioning framework for big data applications
H Wang, J Zhang, D Zhang, S Pumma, W Feng
2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2017
Design and analysis of a cloud-based epidemic simulation framework
P Sukcharoen, S Pumma, O Mongkolsermporn, T Achalakul, X Li
2012 9th International Conference on Electrical Engineering/Electronics …, 2012
Alleviating Load Imbalance in Data Processing for Large-Scale Deep Learning
S Pumma, D Buono, F Checconi, X Que, W Feng
2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet …, 2020
Data Synchronization Method Between FLPs and EPNs
S Pumma
Extracting Topics from Tweets and Webpages for IDEAL: LDA project in CS 5604, Spring 2015
S Pumma, X Liu
The Design of SkyPACS: A High-Performance Mobile Medical Imaging Solution
T Pattanangkur, S Tanupabrungson, K Areekijseree, S Pumma, ...
GPU Computing and Applications, 119-133, 2015
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