Sarunya Pumma

According to our database, Sarunya Pumma authored at least 12 papers between 2012 and 2024.

Collaborative distances:

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

2024

Toward 100TB Recommendation Models with Embedding Offloading.

Intaik Park, Ehsan Ardestani, Damian Reeves, Sarunya Pumma, Henry Tsang, Levy Zhao, Jian He, Joshua Deng, Dennis Van Der Staay, Yu Guo, Paul Zhang

Proceedings of the 18th ACM Conference on Recommender Systems, 2024

2023

RecD: Deduplication for End-to-End Deep Learning Recommendation Model Training Infrastructure.

Mark Zhao, Dhruv Choudhary, Devashish Tyagi, Ajay Somani, Max Kaplan, Sung-Han Lin, Sarunya Pumma, Jongsoo Park, Aarti Basant, Niket Agarwal, Carole-Jean Wu, Christos Kozyrakis

Proceedings of the Sixth Conference on Machine Learning and Systems, 2023

2021

Semantic-Aware Lossless Data Compression for Deep Learning Recommendation Model (DLRM).

Sarunya Pumma, Abhinav Vishnu

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

2020

Scalability Analysis and Optimization for Large-Scale Deep Learning.

Sarunya Pumma

PhD thesis, 2020

A Feasibility Study for MPI over HDFS.

Wu-chun Feng, Da Zhang, Jing Zhang, Kaixi Hou, Sarunya Pumma, Hao Wang

Proceedings of the 2020 IEEE High Performance Extreme Computing Conference, 2020

Alleviating Load Imbalance in Data Processing for Large-Scale Deep Learning.

Sarunya Pumma, Daniele Buono, Fabio Checconi, Xinyu Que, Wu-chun Feng

Proceedings of the 20th IEEE/ACM International Symposium on Cluster, 2020

2019

Scalable Deep Learning via I/O Analysis and Optimization.

Sarunya Pumma, Min Si, Wu-Chun Feng, Pavan Balaji

ACM Trans. Parallel Comput., 2019

2017

A runtime estimation framework for ALICE.

Sarunya Pumma, Wu-chun Feng, Phond Phunchongharn, Sylvain Chapeland, Tiranee Achalakul

Future Gener. Comput. Syst., 2017

PaPar: A Parallel Data Partitioning Framework for Big Data Applications.

Hao Wang, Jing Zhang, Da Zhang, Sarunya Pumma, Wu-chun Feng

Proceedings of the 2017 IEEE International Parallel and Distributed Processing Symposium, 2017

Parallel I/O Optimizations for Scalable Deep Learning.

Sarunya Pumma, Min Si, Wu-chun Feng, Pavan Balaji

Proceedings of the 23rd IEEE International Conference on Parallel and Distributed Systems, 2017

Towards Scalable Deep Learning via I/O Analysis and Optimization.

Sarunya Pumma, Min Si, Wu-chun Feng, Pavan Balaji

Proceedings of the 19th IEEE International Conference on High Performance Computing and Communications; 15th IEEE International Conference on Smart City; 3rd IEEE International Conference on Data Science and Systems, 2017

2012

Automatic VM Allocation for Scientific Application.

Sarunya Pumma, Tiranee Achalakul, Xiaorong Li

Proceedings of the 18th IEEE International Conference on Parallel and Distributed Systems, 2012