Register pointer architecture for efficient embedded processors. - JongSoo Park; Sung-Boem Park; James D. Balfour; David Black-Schaffer; Christos Kozyrakis; William J. Dally (DATE, 2007)

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)

Hierarchical Instruction Register Organization. - David Black-Schaffer; James D. Balfour; William J. Dally; Vishal Parikh; JongSoo Park (IEEE Comput. Archit. Lett., 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)

A Practical Improvement to the Partial Redundancy Elimination in SSA Form. - Jongsoo Park; Jaejin Lee (J. Comput. Sci. Eng., 2008)

Fine-grain dynamic instruction placement for L0 scratch-pad memory. - JongSoo Park; James D. Balfour; William J. Dally (CASES, 2010)

Buffer-space efficient and deadlock-free scheduling of stream applications on multi-core architectures. - JongSoo Park; William J. Dally (SPAA, 2010)

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 (SC, 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 (SIGMOD Conference, 2012)

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 001 (SC, 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 001 (SC, 2013)

Distributed SociaLite: A Datalog-Based Language for Large-Scale Graph Analysis. - Jiwon Seo 002; Jongsoo Park; Jaeho Shin 001; Monica S. Lam (Proc. VLDB Endow., 2013)

Efficient backprojection-based synthetic aperture radar computation with many-core processors. - Jongsoo Park; Ping Tak Peter Tang; Mikhail Smelyanskiy; Daehyun Kim 001; Thomas Benson (Sci. Program., 2013)

A framework for low-communication 1-D FFT. - Ping Tak Peter Tang; Jongsoo Park; Daehyun Kim 001; Vladimir Petrov (Sci. Program., 2013)

Versatile and scalable parallel histogram construction. - Wookeun Jung; Jongsoo Park; Jaejin Lee (PACT, 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 001; Aniruddha G. Shet; Bharat Kaul; Bálint Joó; Pradeep Dubey (IPDPS, 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 (SC, 2014)

Navigating the maze of graph analytics frameworks using massive graph datasets. - Nadathur Satish; Narayanan Sundaram; Md. Mostofa Ali Patwary; Jiwon Seo 002; Jongsoo Park; Muhammad Amber Hassaan; Shubho Sengupta; Zhaoming Yin; Pradeep Dubey (SIGMOD Conference, 2014)

Sparsifying Synchronization for High-Performance Shared-Memory Sparse Triangular Solver. - Jongsoo Park; Mikhail Smelyanskiy; Narayanan Sundaram; Pradeep Dubey (ISC, 2014)

Exploring Shared-Memory Optimizations for an Unstructured Mesh CFD Application on Modern Parallel Systems. - Dheevatsa Mudigere; Srinivas Sridharan 002; Anand M. Deshpande; Jongsoo Park; Alexander Heinecke; Mikhail Smelyanskiy; Bharat Kaul; Pradeep Dubey; Dinesh K. Kaushik; David E. Keyes (IPDPS, 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 (SC, 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 002; Jongsoo Park; Bálint Joó (SC, 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 002; Sergey G. Pudov; Vadim O. Pirogov; Pradeep Dubey (ISC, 2015)

Sparso: Context-driven Optimizations of Sparse Linear Algebra. - Hongbo Rong; Jongsoo Park; Lingxiang Xiang; Todd A. Anderson 001; Mikhail Smelyanskiy (PACT, 2016)

An exploration of optimization algorithms for high performance tensor completion. - Shaden Smith; Jongsoo Park; George Karypis (SC, 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 (SC, 2016)

Holistic SparseCNN: Forging the Trident of Accuracy, Speed, and Size. - Jongsoo Park; Sheng R. Li; Wei Wen; Hai Li 001; Yiran Chen 001; Pradeep Dubey (CoRR, 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)

Faster CNNs with Direct Sparse Convolutions and Guided Pruning. - Jongsoo Park; Sheng R. Li; Wei Wen; Ping Tak Peter Tang; Hai Li 001; Yiran Chen 001; Pradeep Dubey (ICLR (Poster), 2017)

Sparse Tensor Factorization on Many-Core Processors with High-Bandwidth Memory. - Shaden Smith; Jongsoo Park; George Karypis (IPDPS, 2017)

Enabling Sparse Winograd Convolution by Native Pruning. - Sheng R. Li; Jongsoo Park; Ping Tak Peter Tang (CoRR, 2017)

Gate scheduling for quantum algorithms. - Gian Giacomo Guerreschi; Jongsoo Park (CoRR, 2017)

Dynamic fine-grained sparse memory accesses. - Berkin Akin; Chiachen Chou; Jongsoo Park; Christopher J. Hughes; Rajat Agarwal (MEMSYS, 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; et al. (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)

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; et al. (CoRR, 2018)

HPC formulations of optimization algorithms for tensor completion. - Shaden Smith; Jongsoo Park; George Karypis (Parallel Comput., 2018)

Spatial-Winograd Pruning Enabling Sparse Winograd Convolution. - Jiecao Yu; Jongsoo Park; Maxim Naumov (CoRR, 2019)

A Study of BFLOAT16 for Deep Learning Training. - Dhiraj D. Kalamkar; Dheevatsa Mudigere; Naveen Mellempudi; Dipankar Das 002; Kunal Banerjee 001; Sasikanth Avancha; Dharma Teja Vooturi; Nataraj Jammalamadaka; Jianyu Huang; Hector Yuen; Jiyan Yang; Jongsoo Park; et al. (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 020; Udit Gupta; Carole-Jean Wu; Alisson G. Azzolini; Dmytro Dzhulgakov; Andrey Mallevich; et al. (CoRR, 2019)

Post-Training 4-bit Quantization on Embedding Tables. - Hui Guan 001; Andrey Malevich; Jiyan Yang; Jongsoo Park; Hector Yuen (CoRR, 2019)

Adaptive Dense-to-Sparse Paradigm for Pruning Online Recommendation System with Non-Stationary Data. - Mao Ye 006; Dhruv Choudhary; Jiecao Yu; Ellie Wen; Zeliang Chen; Jiyan Yang; Jongsoo Park; Qiang Liu 001; Arun Kejariwal (CoRR, 2020)

Mixed-Precision Embedding Using a Cache. - Jie Amy Yang; Jianyu Huang; Jongsoo Park; Ping Tak Peter Tang; Andrew Tulloch (CoRR, 2020)

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 001; Arun Kejariwal (ICMLA, 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)

High-performance, Distributed Training of Large-scale Deep Learning Recommendation Models. - Dheevatsa Mudigere; Yuchen Hao; Jianyu Huang; Andrew Tulloch; Srinivas Sridharan 002; Xing Liu; Mustafa Ozdal; Jade Nie; Jongsoo Park; Liang Luo; Jie Amy Yang; Leon Gao; et al. (CoRR, 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; et al. (CoRR, 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; et al. (IEEE Micro, 2021)

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 (IEEE Big Data, 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 002; Xing Liu; Mustafa Ozdal; Jade Nie; Jongsoo Park; Liang Luo; Jie Amy Yang; et al. (ISCA, 2022)

Unity: Accelerating DNN Training Through Joint Optimization of Algebraic Transformations and Parallelization. - Colin Unger; Zhihao Jia; Wei Wu 016; Sina Lin; Mandeep Baines; Carlos Efrain Quintero Narvaez; Vinay Ramakrishnaiah; Nirmal Prajapati; Patrick S. McCormick; Jamaludin Mohd-Yusof; Xi Luo; Dheevatsa Mudigere; et al. (OSDI, 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; et al. (CoRR, 2022)

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; et al. (ISCA, 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 (MLSys, 2023)

AdaEmbed: Adaptive Embedding for Large-Scale Recommendation Models. - Fan Lai 001; Wei Zhang; Rui Liu; William Tsai; Xiaohan Wei; Yuxi Hu 001; Sabin Devkota; Jianyu Huang; Jongsoo Park; Xing Liu; Zeliang Chen; Ellie Wen; et al. (OSDI, 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; et al. (CoRR, 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)

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, 2023)

Discovering regional digital innovation tasks to revitalize digital platform government. - Min-Seok Bang; Taewoo Nam; Seok-Hyun Song; Hyang-Won Kwon; Jongsoo Park; Kun Yoon; Sung-Soo Hwang; Gyeongseok Oh (DG.O, 2024)

Wukong: Towards a Scaling Law for Large-Scale Recommendation. - Buyun Zhang; Liang Luo; Yuxin Chen 001; Jade Nie; Xi Liu; Shen Li; Yanli Zhao; Yuchen Hao; Yantao Yao; Ellie Dingqiao Wen; Jongsoo Park; Maxim Naumov; et al. (ICML, 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 001; Shen Li; Yuchen Hao; Yanli Zhao; Guna Lakshminarayanan; Ellie Wen; Jongsoo Park; et al. (MLSys, 2024)

Wukong: Towards a Scaling Law for Large-Scale Recommendation. - Buyun Zhang; Liang Luo; Yuxin Chen 001; Jade Nie; Xi Liu; Daifeng Guo; Yanli Zhao; Shen Li; Yuchen Hao; Yantao Yao; Guna Lakshminarayanan; Ellie Dingqiao Wen; et al. (CoRR, 2024)

The Llama 3 Herd of Models. - 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; et al. (CoRR, 2024)

Context Parallelism for Scalable Million-Token Inference. - Amy Yang; Jingyi Yang; Aya Ibrahim; Xinfeng Xie; Bangsheng Tang; Grigory Sizov; Jeremy Reizenstein; Jongsoo Park; Jianyu Huang (CoRR, 2024)

Scaling Llama 3 Training with Efficient Parallelism Strategies. - Weiwei Chu; Xinfeng Xie; Jiecao Yu; Jie Wang 022; Amar Phanishayee; Chunqiang Tang; Yuchen Hao; Jianyu Huang; Mustafa Ozdal; Jun Wang; Vedanuj Goswami; Naman Goyal 001; et al. (ISCA, 2025)

Meta's Second Generation AI Chip: Model-Chip Co-Design and Productionization Experiences. - Joel Coburn; Chunqiang Tang; Sameer Abu Asal; Neeraj Agrawal; Raviteja Chinta; Harish Dattatraya Dixit; Brian Dodds; Saritha Dwarakapuram; Amin Firoozshahian; Cao Gao; Kaustubh Gondkar; Tyler Graf; et al. (ISCA, 2025)

gpt-oss-120b & gpt-oss-20b Model Card. - Sandhini Agarwal; Lama Ahmad; Jason Ai; Sam Altman; Andy Applebaum; Edwin Arbus; Rahul K. Arora; Yu Bai; Bowen Baker; Haiming Bao; Boaz Barak; Ally Bennett; et al. (CoRR, 2025)