Jongsoo Park

According to our database, Jongsoo Park authored at least 60 papers between 2007 and 2024.

Collaborative distances:

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

2024

Wukong: Towards a Scaling Law for Large-Scale Recommendation.

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

CoRR, 2024

Disaggregated Multi-Tower: Topology-aware Modeling Technique for Efficient Large-Scale Recommendation.

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

CoRR, 2024

2023

75% radiation dose reduction using deep learning reconstruction on low-dose chest CT.

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

BMC Medical Imaging, December, 2023

MTrainS: Improving DLRM training efficiency using heterogeneous memories.

Hiwot Tadese Kassa, Paul Johnson, Jason Akers, Mrinmoy Ghosh, Andrew Tulloch, Dheevatsa Mudigere, Jongsoo Park, Xing Liu, Ronald G. Dreslinski, Ehsan K. Ardestani

CoRR, 2023

Shared Microexponents: A Little Shifting Goes a Long Way.

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

CoRR, 2023

AdaEmbed: Adaptive Embedding for Large-Scale Recommendation Models.

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

Proceedings of the 17th USENIX Symposium on Operating Systems Design and Implementation, 2023

With Shared Microexponents, A Little Shifting Goes a Long Way.

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

Proceedings of the 50th Annual International Symposium on Computer Architecture, 2023

2022

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

CoRR, 2022

DHEN: A Deep and Hierarchical Ensemble Network for Large-Scale Click-Through Rate Prediction.

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

CoRR, 2022

Unity: Accelerating DNN Training Through Joint Optimization of Algebraic Transformations and Parallelization.

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

Proceedings of the 16th USENIX Symposium on Operating Systems Design and Implementation, 2022

Software-hardware co-design for fast and scalable training of deep learning recommendation models.

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

Proceedings of the ISCA '22: The 49th Annual International Symposium on Computer Architecture, New York, New York, USA, June 18, 2022

Efficient Soft-Error Detection for Low-precision Deep Learning Recommendation Models.

Sihuan Li, Jianyu Huang, Ping Tak Peter Tang, Daya Shanker Khudia, Jongsoo Park, Harish Dattatraya Dixit, Zizhong Chen

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale.

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

IEEE Micro, 2021

First-Generation Inference Accelerator Deployment at Facebook.

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.

CoRR, 2021

High-performance, Distributed Training of Large-scale Deep Learning Recommendation Models.

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

CoRR, 2021

FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference.

Daya Shanker Khudia, Jianyu Huang, Protonu Basu, Summer Deng, Haixin Liu, Jongsoo Park, Mikhail Smelyanskiy

CoRR, 2021

Alternate Model Growth and Pruning for Efficient Training of Recommendation Systems.

Xiaocong Du, Bhargav Bhushanam, Jiecao Yu, Dhruv Choudhary, Tianxiang Gao, Sherman Wong, Louis Feng, Jongsoo Park, Yu Cao, Arun Kejariwal

Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

2020

Mixed-Precision Embedding Using a Cache.

Jie Amy Yang, Jianyu Huang, Jongsoo Park, Ping Tak Peter Tang, Andrew Tulloch

CoRR, 2020

Adaptive Dense-to-Sparse Paradigm for Pruning Online Recommendation System with Non-Stationary Data.

Mao Ye, Dhruv Choudhary, Jiecao Yu, Ellie Wen, Zeliang Chen, Jiyan Yang, Jongsoo Park, Qiang Liu, Arun Kejariwal

CoRR, 2020

2019

Post-Training 4-bit Quantization on Embedding Tables.

Hui Guan, Andrey Malevich, Jiyan Yang, Jongsoo Park, Hector Yuen

CoRR, 2019

Deep Learning Recommendation Model for Personalization and Recommendation Systems.

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

CoRR, 2019

A Study of BFLOAT16 for Deep Learning Training.

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

CoRR, 2019

Spatial-Winograd Pruning Enabling Sparse Winograd Convolution.

Jiecao Yu, Jongsoo Park, Maxim Naumov

CoRR, 2019

2018

HPC formulations of optimization algorithms for tensor completion.

Shaden Smith, Jongsoo Park, George Karypis

Parallel Comput., 2018

Deep Learning Inference in Facebook Data Centers: Characterization, Performance Optimizations and Hardware Implications.

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

CoRR, 2018

On Periodic Functions as Regularizers for Quantization of Neural Networks.

Maxim Naumov, Utku Diril, Jongsoo Park, Benjamin Ray, Jedrzej Jablonski, Andrew Tulloch

CoRR, 2018

Glow: Graph Lowering Compiler Techniques for Neural Networks.

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

CoRR, 2018

Dynamic fine-grained sparse memory accesses.

Berkin Akin, Chiachen Chou, Jongsoo Park, Christopher J. Hughes, Rajat Agarwal

Proceedings of the International Symposium on Memory Systems, 2018

2017

Gate scheduling for quantum algorithms.

Gian Giacomo Guerreschi, Jongsoo Park

CoRR, 2017

Enabling Sparse Winograd Convolution by Native Pruning.

Sheng R. Li, Jongsoo Park, Ping Tak Peter Tang

CoRR, 2017

Sparse Tensor Factorization on Many-Core Processors with High-Bandwidth Memory.

Shaden Smith, Jongsoo Park, George Karypis

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

Faster CNNs with Direct Sparse Convolutions and Guided Pruning.

Jongsoo Park, Sheng R. Li, Wei Wen, Ping Tak Peter Tang, Hai Li, Yiran Chen, Pradeep Dubey

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Optimizations in a high-performance conjugate gradient benchmark for IA-based multi- and many-core processors.

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

Int. J. High Perform. Comput. Appl., 2016

Holistic SparseCNN: Forging the Trident of Accuracy, Speed, and Size.

Jongsoo Park, Sheng R. Li, Wei Wen, Hai Li, Yiran Chen, Pradeep Dubey

CoRR, 2016

Automating wavefront parallelization for sparse matrix computations.

Anand Venkat, Mahdi Soltan Mohammadi, Jongsoo Park, Hongbo Rong, Rajkishore Barik, Michelle Mills Strout, Mary W. Hall

Proceedings of the International Conference for High Performance Computing, 2016

An exploration of optimization algorithms for high performance tensor completion.

Shaden Smith, Jongsoo Park, George Karypis

Proceedings of the International Conference for High Performance Computing, 2016

Sparso: Context-driven Optimizations of Sparse Linear Algebra.

Hongbo Rong, Jongsoo Park, Lingxiang Xiang, Todd A. Anderson, Mikhail Smelyanskiy

Proceedings of the 2016 International Conference on Parallel Architectures and Compilation, 2016

2015

Parallel Efficient Sparse Matrix-Matrix Multiplication on Multicore Platforms.

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

Proceedings of the High Performance Computing - 30th International Conference, 2015

Improving concurrency and asynchrony in multithreaded MPI applications using software offloading.

Karthikeyan Vaidyanathan, Dhiraj D. Kalamkar, Kiran Pamnany, Jeff R. Hammond, Pavan Balaji, Dipankar Das, Jongsoo Park, Bálint Joó

Proceedings of the International Conference for High Performance Computing, 2015

High-performance algebraic multigrid solver optimized for multi-core based distributed parallel systems.

Jongsoo Park, Mikhail Smelyanskiy, Ulrike Meier Yang, Dheevatsa Mudigere, Pradeep Dubey

Proceedings of the International Conference for High Performance Computing, 2015

Exploring Shared-Memory Optimizations for an Unstructured Mesh CFD Application on Modern Parallel Systems.

Dheevatsa Mudigere, Srinivas Sridharan, Anand M. Deshpande, Jongsoo Park, Alexander Heinecke, Mikhail Smelyanskiy, Bharat Kaul, Pradeep Dubey, Dinesh K. Kaushik, David E. Keyes

Proceedings of the 2015 IEEE International Parallel and Distributed Processing Symposium, 2015

2014

Sparsifying Synchronization for High-Performance Shared-Memory Sparse Triangular Solver.

Jongsoo Park, Mikhail Smelyanskiy, Narayanan Sundaram, Pradeep Dubey

Proceedings of the Supercomputing - 29th International Conference, 2014

Navigating the maze of graph analytics frameworks using massive graph datasets.

Nadathur Satish, Narayanan Sundaram, Md. Mostofa Ali Patwary, Jiwon Seo, Jongsoo Park, Muhammad Amber Hassaan, Shubho Sengupta, Zhaoming Yin, Pradeep Dubey

Proceedings of the International Conference on Management of Data, 2014

Efficient Shared-Memory Implementation of High-Performance Conjugate Gradient Benchmark and its Application to Unstructured Matrices.

Jongsoo Park, Mikhail Smelyanskiy, Karthikeyan Vaidyanathan, Alexander Heinecke, Dhiraj D. Kalamkar, Xing Liu, Md. Mostofa Ali Patwary, Yutong Lu, Pradeep Dubey

Proceedings of the International Conference for High Performance Computing, 2014

Improving Communication Performance and Scalability of Native Applications on Intel Xeon Phi Coprocessor Clusters.

Karthikeyan Vaidyanathan, Kiran Pamnany, Dhiraj D. Kalamkar, Alexander Heinecke, Mikhail Smelyanskiy, Jongsoo Park, Daehyun Kim, Aniruddha G. Shet, Bharat Kaul, Bálint Joó, Pradeep Dubey

Proceedings of the 2014 IEEE 28th International Parallel and Distributed Processing Symposium, 2014

Versatile and scalable parallel histogram construction.

Wookeun Jung, Jongsoo Park, Jaejin Lee

Proceedings of the International Conference on Parallel Architectures and Compilation, 2014

2013

A framework for low-communication 1-D FFT.

Ping Tak Peter Tang, Jongsoo Park, Daehyun Kim, Vladimir Petrov

Sci. Program., 2013

Efficient backprojection-based synthetic aperture radar computation with many-core processors.

Jongsoo Park, Ping Tak Peter Tang, Mikhail Smelyanskiy, Daehyun Kim, Thomas Benson

Sci. Program., 2013

Distributed SociaLite: A Datalog-Based Language for Large-Scale Graph Analysis.

Jiwon Seo, Jongsoo Park, Jaeho Shin, Monica S. Lam

Proc. VLDB Endow., 2013

Location-aware cache management for many-core processors with deep cache hierarchy.

Jongsoo Park, Richard M. Yoo, Daya Shanker Khudia, Christopher J. Hughes, Daehyun Kim

Proceedings of the International Conference for High Performance Computing, 2013

Tera-scale 1D FFT with low-communication algorithm and Intel® Xeon Phi™ coprocessors.

Jongsoo Park, Ganesh Bikshandi, Karthikeyan Vaidyanathan, Ping Tak Peter Tang, Pradeep Dubey, Daehyun Kim

Proceedings of the International Conference for High Performance Computing, 2013

2012

CloudRAMSort: fast and efficient large-scale distributed RAM sort on shared-nothing cluster.

Changkyu Kim, Jongsoo Park, Nadathur Satish, Hongrae Lee, Pradeep Dubey, Jatin Chhugani

Proceedings of the ACM SIGMOD International Conference on Management of Data, 2012

Billion-particle SIMD-friendly two-point correlation on large-scale HPC cluster systems.

Jatin Chhugani, Changkyu Kim, Hemant Shukla, Jongsoo Park, Pradeep Dubey, John Shalf, Horst D. Simon

Proceedings of the SC Conference on High Performance Computing Networking, 2012

2010

Buffer-space efficient and deadlock-free scheduling of stream applications on multi-core architectures.

JongSoo Park, William J. Dally

Proceedings of the SPAA 2010: Proceedings of the 22nd Annual ACM Symposium on Parallelism in Algorithms and Architectures, 2010

Fine-grain dynamic instruction placement for L0 scratch-pad memory.

JongSoo Park, James D. Balfour, William J. Dally

Proceedings of the 2010 International Conference on Compilers, 2010

2008

A Practical Improvement to the Partial Redundancy Elimination in SSA Form.

Jongsoo Park, Jaejin Lee

J. Comput. Sci. Eng., 2008

Efficient Embedded Computing.

William J. Dally, James D. Balfour, David Black-Schaffer, James Chen, R. Curtis Harting, Vishal Parikh, JongSoo Park, David Sheffield

Computer, 2008

Hierarchical Instruction Register Organization.

David Black-Schaffer, James D. Balfour, William J. Dally, Vishal Parikh, JongSoo Park

IEEE Comput. Archit. Lett., 2008

An Energy-Efficient Processor Architecture for Embedded Systems.

James D. Balfour, William J. Dally, David Black-Schaffer, Vishal Parikh, JongSoo Park

IEEE Comput. Archit. Lett., 2008

2007

Register pointer architecture for efficient embedded processors.

JongSoo Park, Sung-Boem Park, James D. Balfour, David Black-Schaffer, Christos Kozyrakis, William J. Dally

Proceedings of the 2007 Design, Automation and Test in Europe Conference and Exposition, 2007