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Jongsoo Park
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2020 – today
- 2024
- [i24]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 abs/2403.00877 (2024) - [i23]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 abs/2403.02545 (2024) - 2023
- [j11]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): 121 (2023) - [c30]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: 83:1-83:13 - [c29]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: 817-831 - [i22]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 abs/2302.08007 (2023) - [i21]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 abs/2305.01515 (2023) - 2022
- [c28]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. IEEE Big Data 2022: 1556-1563 - [c27]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: 993-1011 - [c26]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: 267-284 - [i20]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 abs/2203.11014 (2022) - [i19]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 abs/2211.05239 (2022) - 2021
- [j10]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): 93-100 (2021) - [c25]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: 1421-1428 - [i18]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 abs/2101.05615 (2021) - [i17]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 abs/2103.00130 (2021) - [i16]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 abs/2104.05158 (2021) - [i15]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 abs/2105.01064 (2021) - [i14]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 abs/2105.12676 (2021) - [i13]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 abs/2107.04140 (2021) - 2020
- [i12]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 abs/2010.08655 (2020) - [i11]Jie Amy Yang, Jianyu Huang, Jongsoo Park, Ping Tak Peter Tang, Andrew Tulloch:
Mixed-Precision Embedding Using a Cache. CoRR abs/2010.11305 (2020)
2010 – 2019
- 2019
- [i10]Jiecao Yu, Jongsoo Park, Maxim Naumov:
Spatial-Winograd Pruning Enabling Sparse Winograd Convolution. CoRR abs/1901.02132 (2019) - [i9]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 abs/1905.12322 (2019) - [i8]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 abs/1906.00091 (2019) - [i7]Hui Guan, Andrey Malevich, Jiyan Yang, Jongsoo Park, Hector Yuen:
Post-Training 4-bit Quantization on Embedding Tables. CoRR abs/1911.02079 (2019) - 2018
- [j9]Shaden Smith, Jongsoo Park, George Karypis
:
HPC formulations of optimization algorithms for tensor completion. Parallel Comput. 74: 99-117 (2018) - [c24]Berkin Akin, Chiachen Chou, Jongsoo Park, Christopher J. Hughes, Rajat Agarwal:
Dynamic fine-grained sparse memory accesses. MEMSYS 2018: 85-97 - [i6]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 abs/1805.00907 (2018) - [i5]Maxim Naumov, Utku Diril, Jongsoo Park, Benjamin Ray, Jedrzej Jablonski, Andrew Tulloch:
On Periodic Functions as Regularizers for Quantization of Neural Networks. CoRR abs/1811.09862 (2018) - [i4]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 abs/1811.09886 (2018) - 2017
- [c23]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 - [c22]Shaden Smith, Jongsoo Park, George Karypis
:
Sparse Tensor Factorization on Many-Core Processors with High-Bandwidth Memory. IPDPS 2017: 1058-1067 - [i3]Sheng R. Li, Jongsoo Park, Ping Tak Peter Tang:
Enabling Sparse Winograd Convolution by Native Pruning. CoRR abs/1702.08597 (2017) - [i2]Gian Giacomo Guerreschi, Jongsoo Park:
Gate scheduling for quantum algorithms. CoRR abs/1708.00023 (2017) - 2016
- [j8]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): 11-27 (2016) - [c21]Hongbo Rong, Jongsoo Park, Lingxiang Xiang, Todd A. Anderson, Mikhail Smelyanskiy:
Sparso: Context-driven Optimizations of Sparse Linear Algebra. PACT 2016: 247-259 - [c20]Shaden Smith, Jongsoo Park, George Karypis
:
An exploration of optimization algorithms for high performance tensor completion. SC 2016: 359-371 - [c19]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: 480-491 - [i1]Jongsoo Park, Sheng R. Li, Wei Wen, Hai Li, Yiran Chen, Pradeep Dubey:
Holistic SparseCNN: Forging the Trident of Accuracy, Speed, and Size. CoRR abs/1608.01409 (2016) - 2015
- [c18]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: 723-732 - [c17]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: 30:1-30:12 - [c16]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: 54:1-54:12 - [c15]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: 48-57 - 2014
- [c14]Wookeun Jung, Jongsoo Park, Jaejin Lee:
Versatile and scalable parallel histogram construction. PACT 2014: 127-138 - [c13]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: 1083-1092 - [c12]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: 945-955 - [c11]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: 979-990 - [c10]Jongsoo Park, Mikhail Smelyanskiy, Narayanan Sundaram, Pradeep Dubey:
Sparsifying Synchronization for High-Performance Shared-Memory Sparse Triangular Solver. ISC 2014: 124-140 - 2013
- [j7]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): 1906-1917 (2013) - [j6]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): 165-179 (2013) - [j5]Ping Tak Peter Tang, Jongsoo Park, Daehyun Kim, Vladimir Petrov:
A framework for low-communication 1-D FFT. Sci. Program. 21(3-4): 181-195 (2013) - [c9]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: 20:1-20:12 - [c8]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: 34:1-34:12 - 2012
- [c7]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: 1 - [c6]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: 28 - [c5]Ping Tak Peter Tang, Jongsoo Park, Daehyun Kim, Vladimir Petrov:
A framework for low-communication 1-D FFT. SC 2012: 42 - [c4]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: 841-850 - 2010
- [c3]JongSoo Park, James D. Balfour, William J. Dally:
Fine-grain dynamic instruction placement for L0 scratch-pad memory. CASES 2010: 137-146 - [c2]JongSoo Park, William J. Dally:
Buffer-space efficient and deadlock-free scheduling of stream applications on multi-core architectures. SPAA 2010: 1-10
2000 – 2009
- 2008
- [j4]James D. Balfour, William J. Dally, David Black-Schaffer, Vishal Parikh, JongSoo Park:
An Energy-Efficient Processor Architecture for Embedded Systems. IEEE Comput. Archit. Lett. 7(1): 29-32 (2008) - [j3]David Black-Schaffer, James D. Balfour, William J. Dally, Vishal Parikh, JongSoo Park:
Hierarchical Instruction Register Organization. IEEE Comput. Archit. Lett. 7(2): 41-44 (2008) - [j2]William J. Dally, James D. Balfour, David Black-Schaffer, James Chen, R. Curtis Harting, Vishal Parikh, JongSoo Park, David Sheffield:
Efficient Embedded Computing. Computer 41(7): 27-32 (2008) - [j1]Jongsoo Park, Jaejin Lee:
A Practical Improvement to the Partial Redundancy Elimination in SSA Form. J. Comput. Sci. Eng. 2(3): 301-320 (2008) - 2007
- [c1]JongSoo Park, Sung-Boem Park, James D. Balfour, David Black-Schaffer, Christos Kozyrakis, William J. Dally:
Register pointer architecture for efficient embedded processors. DATE 2007: 600-605
Coauthor Index
aka: Misha Smelyanskiy
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