Jongsoo Park

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 48

Top Topics

Avoid Overfitting

Top Venues

Publications

Liang Luo, Buyun Zhang, Michael Tsang, Yinbin Ma, Ching-Hsiang Chu, Yuxin Chen, Shen Li, Yuchen Hao, Yanli Zhao, Guna Lakshminarayanan, Ellie Dingqiao Wen, Jongsoo Park, Dheevatsa Mudigere, Maxim Naumov
Disaggregated Multi-Tower: Topology-aware Modeling Technique for Efficient Large-Scale Recommendation. CoRR (2024)
Buyun Zhang, Liang Luo, Yuxin Chen, Jade Nie, Xi Liu, Daifeng Guo, Yanli Zhao, Shen Li, Yuchen Hao, Yantao Yao, Guna Lakshminarayanan, Ellie Dingqiao Wen, Jongsoo Park, Maxim Naumov, Wenlin Chen
Wukong: Towards a Scaling Law for Large-Scale Recommendation. CoRR (2024)
Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, Anirudh Goyal, Anthony Hartshorn, Aobo Yang, Archi Mitra, Archie Sravankumar, Artem Korenev, Arthur Hinsvark, Arun Rao, Aston Zhang, Aurélien Rodriguez, Austen Gregerson, Ava Spataru, Baptiste Rozière, Bethany Biron, Binh Tang, Bobbie Chern, Charlotte Caucheteux, Chaya Nayak, Chloe Bi, Chris Marra, Chris McConnell, Christian Keller, Christophe Touret, Chunyang Wu, Corinne Wong, Cristian Canton Ferrer, Cyrus Nikolaidis, Damien Allonsius, Daniel Song, Danielle Pintz, Danny Livshits, David Esiobu, Dhruv Choudhary, Dhruv Mahajan, Diego Garcia-Olano, Diego Perino, Dieuwke Hupkes, Egor Lakomkin, Ehab AlBadawy, Elina Lobanova, Emily Dinan, Eric Michael Smith, Filip Radenovic, Frank Zhang, Gabriel Synnaeve, Gabrielle Lee, Georgia Lewis Anderson, Graeme Nail, Grégoire Mialon, Guan Pang, Guillem Cucurell, Hailey Nguyen, Hannah Korevaar, Hu Xu, Hugo Touvron, Iliyan Zarov, Imanol Arrieta Ibarra, Isabel M. Kloumann, Ishan Misra, Ivan Evtimov, Jade Copet, Jaewon Lee, Jan Geffert, Jana Vranes, Jason Park, Jay Mahadeokar, Jeet Shah, Jelmer van der Linde, Jennifer Billock, Jenny Hong, Jenya Lee, Jeremy Fu, Jianfeng Chi, Jianyu Huang, Jiawen Liu, Jie Wang, Jiecao Yu, Joanna Bitton, Joe Spisak, Jongsoo Park, Joseph Rocca, Joshua Johnstun, Joshua Saxe, Junteng Jia, Kalyan Vasuden Alwala, Kartikeya Upasani, Kate Plawiak, Ke Li, Kenneth Heafield, Kevin Stone, et al.
The Llama 3 Herd of Models. CoRR (2024)
Min-Seok Bang, Taewoo Nam, Seok-Hyun Song, Hyang-Won Kwon, Jongsoo Park, Kun Yoon, Sung-Soo Hwang, Gyeongseok Oh
Discovering regional digital innovation tasks to revitalize digital platform government. DG.O (2024)
Liang Luo, Buyun Zhang, Michael Tsang, Yinbin Ma, Ching-Hsiang Chu, Yuxin Chen, Shen Li, Yuchen Hao, Yanli Zhao, Guna Lakshminarayanan, Ellie Wen, Jongsoo Park, Dheevatsa Mudigere, Maxim Naumov
Disaggregated Multi-Tower: Topology-aware Modeling Technique for Efficient Large Scale Recommendation. MLSys (2024)
Bita Darvish Rouhani, Ritchie Zhao, Venmugil Elango, Rasoul Shafipour, Mathew Hall, Maral Mesmakhosroshahi, Ankit More, Levi Melnick, Maximilian Golub, Girish Varatkar, Lai Shao, Gaurav Kolhe, Dimitry Melts, Jasmine Klar, Renee L'Heureux, Matt Perry, Doug Burger, Eric S. Chung, Zhaoxia (Summer) Deng, Sam Naghshineh, Jongsoo Park, Maxim Naumov
With Shared Microexponents, A Little Shifting Goes a Long Way. ISCA (2023)
Fan Lai, Wei Zhang, Rui Liu, William Tsai, Xiaohan Wei, Yuxi Hu, Sabin Devkota, Jianyu Huang, Jongsoo Park, Xing Liu, Zeliang Chen, Ellie Wen, Paul Rivera, Jie You, Chun-cheng Jason Chen, Mosharaf Chowdhury
AdaEmbed: Adaptive Embedding for Large-Scale Recommendation Models. OSDI (2023)
Bita Rouhani, Ritchie Zhao, Venmugil Elango, Rasoul Shafipour, Mathew Hall, Maral Mesmakhosroshahi, Ankit More, Levi Melnick, Maximilian Golub, Girish Varatkar, Lei Shao, Gaurav Kolhe, Dimitry Melts, Jasmine Klar, Renee L'Heureux, Matt Perry, Doug Burger, Eric S. Chung, Zhaoxia Deng, Sam Naghshineh, Jongsoo Park, Maxim Naumov
Shared Microexponents: A Little Shifting Goes a Long Way. CoRR (2023)
Hiwot Tadese Kassa, Paul Johnson, Jason Akers, Mrinmoy Ghosh, Andrew Tulloch, Dheevatsa Mudigere, Jongsoo Park, Xing Liu, Ronald G. Dreslinski, Ehsan K. Ardestani
MTrainS: Improving DLRM training efficiency using heterogeneous memories. CoRR (2023)
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
RecD: Deduplication for End-to-End Deep Learning Recommendation Model Training Infrastructure. MLSys (2023)
Gyeong Deok Jo, Chul Kyun Ahn, Jung Hee Hong, Da Som Kim, Jongsoo Park, Hyungjin Kim, Jong Hyo Kim, Jin Mo Goo, Ju Gang Nam
75% radiation dose reduction using deep learning reconstruction on low-dose chest CT. BMC Medical Imaging 23 (1) (2023)
Buyun Zhang, Liang Luo, Xi Liu, Jay Li, Zeliang Chen, Weilin Zhang, Xiaohan Wei, Yuchen Hao, Michael Tsang, Wenjun Wang, Yang Liu, Huayu Li, Yasmine Badr, Jongsoo Park, Jiyan Yang, Dheevatsa Mudigere, Ellie Wen
DHEN: A Deep and Hierarchical Ensemble Network for Large-Scale Click-Through Rate Prediction. CoRR (2022)
Colin Unger, Zhihao Jia, Wei Wu, Sina Lin, Mandeep Baines, Carlos Efrain Quintero Narvaez, Vinay Ramakrishnaiah, Nirmal Prajapati, Patrick S. McCormick, Jamaludin Mohd-Yusof, Xi Luo, Dheevatsa Mudigere, Jongsoo Park, Misha Smelyanskiy, Alex Aiken
Unity: Accelerating DNN Training Through Joint Optimization of Algebraic Transformations and Parallelization. OSDI (2022)
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
RecD: Deduplication for End-to-End Deep Learning Recommendation Model Training Infrastructure. CoRR (2022)
Dheevatsa Mudigere, Yuchen Hao, Jianyu Huang, Zhihao Jia, Andrew Tulloch, Srinivas Sridharan, Xing Liu, Mustafa Ozdal, Jade Nie, Jongsoo Park, Liang Luo, Jie Amy Yang, Leon Gao, Dmytro Ivchenko, Aarti Basant, Yuxi Hu, Jiyan Yang, Ehsan K. Ardestani, Xiaodong Wang, Rakesh Komuravelli, Ching-Hsiang Chu, Serhat Yilmaz, Huayu Li, Jiyuan Qian, Zhuobo Feng, Yinbin Ma, Junjie Yang, Ellie Wen, Hong Li, Lin Yang, Chonglin Sun, Whitney Zhao, Dimitry Melts, Krishna Dhulipala, K. R. Kishore, Tyler Graf, Assaf Eisenman, Kiran Kumar Matam, Adi Gangidi, Guoqiang Jerry Chen, Manoj Krishnan, Avinash Nayak, Krishnakumar Nair, Bharath Muthiah, Mahmoud khorashadi, Pallab Bhattacharya, Petr Lapukhov, Maxim Naumov, Ajit Mathews, Lin Qiao, Mikhail Smelyanskiy, Bill Jia, Vijay Rao
Software-hardware co-design for fast and scalable training of deep learning recommendation models. ISCA (2022)
Sihuan Li, Jianyu Huang, Ping Tak Peter Tang, Daya Shanker Khudia, Jongsoo Park, Harish Dattatraya Dixit, Zizhong Chen
Efficient Soft-Error Detection for Low-precision Deep Learning Recommendation Models. Big Data (2022)
Michael J. Anderson, Benny Chen, Stephen Chen, Summer Deng, Jordan Fix, Michael Gschwind, Aravind Kalaiah, Changkyu Kim, Jaewon Lee, Jason Liang, Haixin Liu, Yinghai Lu, Jack Montgomery, Arun Moorthy, Nadathur Satish, Sam Naghshineh, Avinash Nayak, Jongsoo Park, Chris Petersen, Martin Schatz, Narayanan Sundaram, Bangsheng Tang, Peter Tang, Amy Yang, Jiecao Yu, Hector Yuen, Ying Zhang, Aravind Anbudurai, Vandana Balan, Harsha Bojja, Joe Boyd, Matthew Breitbach, Claudio Caldato, Anna Calvo, Garret Catron, Sneh Chandwani, Panos Christeas, Brad Cottel, Brian Coutinho, Arun Dalli, Abhishek Dhanotia, Oniel Duncan, Roman Dzhabarov, Simon Elmir, Chunli Fu, Wenyin Fu, Michael Fulthorp, Adi Gangidi, Nick Gibson, Sean Gordon, Beatriz Padilla Hernandez, Daniel Ho, Yu-Cheng Huang, Olof Johansson, Shishir Juluri, et al.
First-Generation Inference Accelerator Deployment at Facebook. CoRR (2021)
Zhaoxia Deng, Jongsoo Park, Ping Tak Peter Tang, Haixin Liu, Jie Yang, Hector Yuen, Jianyu Huang, Daya Shanker Khudia, Xiaohan Wei, Ellie Wen, Dhruv Choudhary, Raghuraman Krishnamoorthi, Carole-Jean Wu, Nadathur Satish, Changkyu Kim, Maxim Naumov, Sam Naghshineh, Mikhail Smelyanskiy
Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale. IEEE Micro 41 (5) (2021)
Daya Shanker Khudia, Jianyu Huang, Protonu Basu, Summer Deng, Haixin Liu, Jongsoo Park, Mikhail Smelyanskiy
FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference. CoRR (2021)
Sihuan Li, Jianyu Huang, Ping Tak Peter Tang, Daya Shanker Khudia, Jongsoo Park, Harish Dattatraya Dixit, Zizhong Chen
Efficient Soft-Error Detection for Low-precision Deep Learning Recommendation Models. CoRR (2021)
Xiaocong Du, Bhargav Bhushanam, Jiecao Yu, Dhruv Choudhary, Tianxiang Gao, Sherman Wong, Louis Feng, Jongsoo Park, Yu Cao, Arun Kejariwal
Alternate Model Growth and Pruning for Efficient Training of Recommendation Systems. CoRR (2021)
Dheevatsa Mudigere, Yuchen Hao, Jianyu Huang, Andrew Tulloch, Srinivas Sridharan, Xing Liu, Mustafa Ozdal, Jade Nie, Jongsoo Park, Liang Luo, Jie Amy Yang, Leon Gao, Dmytro Ivchenko, Aarti Basant, Yuxi Hu, Jiyan Yang, Ehsan K. Ardestani, Xiaodong Wang, Rakesh Komuravelli, Ching-Hsiang Chu, Serhat Yilmaz, Huayu Li, Jiyuan Qian, Zhuobo Feng, Yinbin Ma, Junjie Yang, Ellie Wen, Hong Li, Lin Yang, Chonglin Sun, Whitney Zhao, Dimitry Melts, Krishna Dhulipala, K. R. Kishore, Tyler Graf, Assaf Eisenman, Kiran Kumar Matam, Adi Gangidi, Guoqiang Jerry Chen, Manoj Krishnan, Avinash Nayak, Krishnakumar Nair, Bharath Muthiah, Mahmoud khorashadi, Pallab Bhattacharya, Petr Lapukhov, Maxim Naumov, Lin Qiao, Mikhail Smelyanskiy, Bill Jia, Vijay Rao
High-performance, Distributed Training of Large-scale Deep Learning Recommendation Models. CoRR (2021)
Xiaocong Du, Bhargav Bhushanam, Jiecao Yu, Dhruv Choudhary, Tianxiang Gao, Sherman Wong, Louis Feng, Jongsoo Park, Yu Cao, Arun Kejariwal
Alternate Model Growth and Pruning for Efficient Training of Recommendation Systems. ICMLA (2021)
Zhaoxia Deng, Jongsoo Park, Ping Tak Peter Tang, Haixin Liu, Jie Yang, Hector Yuen, Jianyu Huang, Daya Shanker Khudia, Xiaohan Wei, Ellie Wen, Dhruv Choudhary, Raghuraman Krishnamoorthi, Carole-Jean Wu, Nadathur Satish, Changkyu Kim, Maxim Naumov, Sam Naghshineh, Mikhail Smelyanskiy
Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale. CoRR (2021)
Jie Amy Yang, Jianyu Huang, Jongsoo Park, Ping Tak Peter Tang, Andrew Tulloch
Mixed-Precision Embedding Using a Cache. CoRR (2020)
Mao Ye, Dhruv Choudhary, Jiecao Yu, Ellie Wen, Zeliang Chen, Jiyan Yang, Jongsoo Park, Qiang Liu, Arun Kejariwal
Adaptive Dense-to-Sparse Paradigm for Pruning Online Recommendation System with Non-Stationary Data. CoRR (2020)
Jiecao Yu, Jongsoo Park, Maxim Naumov
Spatial-Winograd Pruning Enabling Sparse Winograd Convolution. CoRR (2019)
Hui Guan, Andrey Malevich, Jiyan Yang, Jongsoo Park, Hector Yuen
Post-Training 4-bit Quantization on Embedding Tables. CoRR (2019)
Maxim Naumov, Dheevatsa Mudigere, Hao-Jun Michael Shi, Jianyu Huang, Narayanan Sundaraman, Jongsoo Park, Xiaodong Wang, Udit Gupta, Carole-Jean Wu, Alisson G. Azzolini, Dmytro Dzhulgakov, Andrey Mallevich, Ilia Cherniavskii, Yinghai Lu, Raghuraman Krishnamoorthi, Ansha Yu, Volodymyr Kondratenko, Stephanie Pereira, Xianjie Chen, Wenlin Chen, Vijay Rao, Bill Jia, Liang Xiong, Misha Smelyanskiy
Deep Learning Recommendation Model for Personalization and Recommendation Systems. CoRR (2019)
Dhiraj D. Kalamkar, Dheevatsa Mudigere, Naveen Mellempudi, Dipankar Das, Kunal Banerjee, Sasikanth Avancha, Dharma Teja Vooturi, Nataraj Jammalamadaka, Jianyu Huang, Hector Yuen, Jiyan Yang, Jongsoo Park, Alexander Heinecke, Evangelos Georganas, Sudarshan Srinivasan, Abhisek Kundu, Misha Smelyanskiy, Bharat Kaul, Pradeep Dubey
A Study of BFLOAT16 for Deep Learning Training. CoRR (2019)
Jongsoo Park, Maxim Naumov, Protonu Basu, Summer Deng, Aravind Kalaiah, Daya Shanker Khudia, James Law, Parth Malani, Andrey Malevich, Nadathur Satish, Juan Miguel Pino, Martin Schatz, Alexander Sidorov, Viswanath Sivakumar, Andrew Tulloch, Xiaodong Wang, Yiming Wu, Hector Yuen, Utku Diril, Dmytro Dzhulgakov, Kim M. Hazelwood, Bill Jia, Yangqing Jia, Lin Qiao, Vijay Rao, Nadav Rotem, Sungjoo Yoo, Mikhail Smelyanskiy
Deep Learning Inference in Facebook Data Centers: Characterization, Performance Optimizations and Hardware Implications. CoRR (2018)
Berkin Akin, Chiachen Chou, Jongsoo Park, Christopher J. Hughes, Rajat Agarwal
Dynamic fine-grained sparse memory accesses. MEMSYS (2018)
Maxim Naumov, Utku Diril, Jongsoo Park, Benjamin Ray, Jedrzej Jablonski, Andrew Tulloch
On Periodic Functions as Regularizers for Quantization of Neural Networks. CoRR (2018)
Shaden Smith, Jongsoo Park, George Karypis
HPC formulations of optimization algorithms for tensor completion. Parallel Comput. 74 (2018)
Nadav Rotem, Jordan Fix, Saleem Abdulrasool, Summer Deng, Roman Dzhabarov, James Hegeman, Roman Levenstein, Bert Maher, Nadathur Satish, Jakob Olesen, Jongsoo Park, Artem Rakhov, Misha Smelyanskiy
Glow: Graph Lowering Compiler Techniques for Neural Networks. CoRR (2018)
Shaden Smith, Jongsoo Park, George Karypis
Sparse Tensor Factorization on Many-Core Processors with High-Bandwidth Memory. IPDPS (2017)
Jongsoo Park, Sheng R. Li, Wei Wen, Ping Tak Peter Tang, Hai Li, Yiran Chen, Pradeep Dubey
Faster CNNs with Direct Sparse Convolutions and Guided Pruning. ICLR (Poster) (2017)
Gian Giacomo Guerreschi, Jongsoo Park
Gate scheduling for quantum algorithms. CoRR (2017)
Sheng R. Li, Jongsoo Park, Ping Tak Peter Tang
Enabling Sparse Winograd Convolution by Native Pruning. CoRR (2017)
Anand Venkat, Mahdi Soltan Mohammadi, Jongsoo Park, Hongbo Rong, Rajkishore Barik, Michelle Mills Strout, Mary W. Hall
Automating wavefront parallelization for sparse matrix computations. SC (2016)
Shaden Smith, Jongsoo Park, George Karypis
An exploration of optimization algorithms for high performance tensor completion. SC (2016)
Jongsoo Park, Sheng R. Li, Wei Wen, Hai Li, Yiran Chen, Pradeep Dubey
Holistic SparseCNN: Forging the Trident of Accuracy, Speed, and Size. CoRR (2016)
Jongsoo Park, Mikhail Smelyanskiy, Karthikeyan Vaidyanathan, Alexander Heinecke, Dhiraj D. Kalamkar, Md. Mostofa Ali Patwary, Vadim O. Pirogov, Pradeep Dubey, Xing Liu, Carlos Rosales, Cyril Mazauric, Christopher S. Daley
Optimizations in a high-performance conjugate gradient benchmark for IA-based multi- and many-core processors. Int. J. High Perform. Comput. Appl. 30 (1) (2016)
Hongbo Rong, Jongsoo Park, Lingxiang Xiang, Todd A. Anderson, Mikhail Smelyanskiy
Sparso: Context-driven Optimizations of Sparse Linear Algebra. PACT (2016)
Dheevatsa Mudigere, Srinivas Sridharan, Anand M. Deshpande, Jongsoo Park, Alexander Heinecke, Mikhail Smelyanskiy, Bharat Kaul, Pradeep Dubey, Dinesh K. Kaushik, David E. Keyes
Exploring Shared-Memory Optimizations for an Unstructured Mesh CFD Application on Modern Parallel Systems. IPDPS (2015)
Jongsoo Park, Mikhail Smelyanskiy, Ulrike Meier Yang, Dheevatsa Mudigere, Pradeep Dubey
High-performance algebraic multigrid solver optimized for multi-core based distributed parallel systems. SC (2015)
Md. Mostofa Ali Patwary, Nadathur Rajagopalan Satish, Narayanan Sundaram, Jongsoo Park, Michael J. Anderson, Satya Gautam Vadlamudi, Dipankar Das, Sergey G. Pudov, Vadim O. Pirogov, Pradeep Dubey
Parallel Efficient Sparse Matrix-Matrix Multiplication on Multicore Platforms. ISC (2015)
Karthikeyan Vaidyanathan, Dhiraj D. Kalamkar, Kiran Pamnany, Jeff R. Hammond, Pavan Balaji, Dipankar Das, Jongsoo Park, Bálint Joó
Improving concurrency and asynchrony in multithreaded MPI applications using software offloading. SC (2015)
Karthikeyan Vaidyanathan, Kiran Pamnany, Dhiraj D. Kalamkar, Alexander Heinecke, Mikhail Smelyanskiy, Jongsoo Park, Daehyun Kim, Aniruddha G. Shet, Bharat Kaul, Bálint Joó, Pradeep Dubey
Improving Communication Performance and Scalability of Native Applications on Intel Xeon Phi Coprocessor Clusters. IPDPS (2014)
Jongsoo Park, Mikhail Smelyanskiy, Karthikeyan Vaidyanathan, Alexander Heinecke, Dhiraj D. Kalamkar, Xing Liu, Md. Mostofa Ali Patwary, Yutong Lu, Pradeep Dubey
Efficient Shared-Memory Implementation of High-Performance Conjugate Gradient Benchmark and its Application to Unstructured Matrices. SC (2014)
Nadathur Satish, Narayanan Sundaram, Md. Mostofa Ali Patwary, Jiwon Seo, Jongsoo Park, Muhammad Amber Hassaan, Shubho Sengupta, Zhaoming Yin, Pradeep Dubey
Navigating the maze of graph analytics frameworks using massive graph datasets. SIGMOD Conference (2014)
Wookeun Jung, Jongsoo Park, Jaejin Lee
Versatile and scalable parallel histogram construction. PACT (2014)
Jongsoo Park, Mikhail Smelyanskiy, Narayanan Sundaram, Pradeep Dubey
Sparsifying Synchronization for High-Performance Shared-Memory Sparse Triangular Solver. ISC (2014)
Jongsoo Park, Ganesh Bikshandi, Karthikeyan Vaidyanathan, Ping Tak Peter Tang, Pradeep Dubey, Daehyun Kim
Tera-scale 1D FFT with low-communication algorithm and Intel® Xeon Phi™ coprocessors. SC (2013)
Jiwon Seo, Jongsoo Park, Jaeho Shin, Monica S. Lam
Distributed SociaLite: A Datalog-Based Language for Large-Scale Graph Analysis. Proc. VLDB Endow. 6 (14) (2013)
Ping Tak Peter Tang, Jongsoo Park, Daehyun Kim, Vladimir Petrov
A framework for low-communication 1-D FFT. Sci. Program. 21 (3-4) (2013)
Jongsoo Park, Ping Tak Peter Tang, Mikhail Smelyanskiy, Daehyun Kim, Thomas Benson
Efficient backprojection-based synthetic aperture radar computation with many-core processors. Sci. Program. 21 (3-4) (2013)
Jongsoo Park, Richard M. Yoo, Daya Shanker Khudia, Christopher J. Hughes, Daehyun Kim
Location-aware cache management for many-core processors with deep cache hierarchy. SC (2013)
Jongsoo Park, Ping Tak Peter Tang, Mikhail Smelyanskiy, Daehyun Kim, Thomas Benson
Efficient backprojection-based synthetic aperture radar computation with many-core processors. SC (2012)
Ping Tak Peter Tang, Jongsoo Park, Daehyun Kim, Vladimir Petrov
A framework for low-communication 1-D FFT. SC (2012)
Jatin Chhugani, Changkyu Kim, Hemant Shukla, Jongsoo Park, Pradeep Dubey, John Shalf, Horst D. Simon
Billion-particle SIMD-friendly two-point correlation on large-scale HPC cluster systems. SC (2012)
Changkyu Kim, Jongsoo Park, Nadathur Satish, Hongrae Lee, Pradeep Dubey, Jatin Chhugani
CloudRAMSort: fast and efficient large-scale distributed RAM sort on shared-nothing cluster. SIGMOD Conference (2012)
Jongsoo Park, Jaejin Lee
A Practical Improvement to the Partial Redundancy Elimination in SSA Form. J. Comput. Sci. Eng. 2 (3) (2008)