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ORCIDEhsan K. Ardestani
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Journal Articles
- 2018
[j4]Rafael Trapani Possignolo
, Elnaz Ebrahimi, Ehsan K. Ardestani, Alamelu Sankaranarayanan, José Luis Briz, Jose Renau:
GPU NTC Process Variation Compensation With Voltage Stacking. IEEE Trans. Very Large Scale Integr. Syst. 26(9): 1713-1726 (2018)- 2016
- [j3]Ehsan K. Ardestani, Rafael Trapani Possignolo, José Luis Briz, Jose Renau:
Managing Mismatches in Voltage Stacking with CoreUnfolding. ACM Trans. Archit. Code Optim. 12(4): 43:1-43:26 (2016) - 2014
- [j2]Amirkoushyar Ziabari, Je-Hyoung Park, Ehsan K. Ardestani, Jose Renau, Sung-Mo Kang, Ali Shakouri:
Power Blurring: Fast Static and Transient Thermal Analysis Method for Packaged Integrated Circuits and Power Devices. IEEE Trans. Very Large Scale Integr. Syst. 22(11): 2366-2379 (2014) - 2013
- [j1]Ehsan K. Ardestani, Francisco J. Mesa-Martinez, Gabriel Southern, Elnaz Ebrahimi, Jose Renau:
Sampling in Thermal Simulation of Processors: Measurement, Characterization, and Evaluation. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 32(8): 1187-1200 (2013)
Conference and Workshop Papers
- 2023
- [c13]Amin Firoozshahian, Joel Coburn, Roman Levenstein, Rakesh Nattoji, Ashwin Kamath, Olívia Wu, Gurdeepak Grewal, Harish Aepala, Bhasker Jakka, Bob Dreyer, Adam Hutchin, Utku Diril, Krishnakumar Nair, Ehsan K. Ardestani, Martin Schatz, Yuchen Hao, Rakesh Komuravelli, Kunming Ho, Sameer Abu Asal, Joe Shajrawi, Kevin Quinn, Nagesh Sreedhara, Pankaj Kansal, Willie Wei, Dheepak Jayaraman, Linda Cheng, Pritam Chopda, Eric Wang, Ajay Bikumandla, Arun Karthik Sengottuvel, Krishna Thottempudi, Ashwin Narasimha, Brian Dodds, Cao Gao, Jiyuan Zhang, Mohammed Al-Sanabani, Ana Zehtabioskuie, Jordan Fix, Hangchen Yu, Richard Li, Kaustubh Gondkar, Jack Montgomery, Mike Tsai, Saritha Dwarakapuram, Sanjay Desai, Nili Avidan, Poorvaja Ramani, Karthik Narayanan, Ajit Mathews, Sethu Gopal, Maxim Naumov, Vijay Rao, Krishna Noru, Harikrishna Reddy, Prahlad Venkatapuram, Alexis Bjorlin:
MTIA: First Generation Silicon Targeting Meta's Recommendation Systems. ISCA 2023: 80:1-80:13 - 2022
- [c12]Zhongyi Lin, Louis Feng, Ehsan K. Ardestani, Jaewon Lee, John Lundell, Changkyu Kim, Arun Kejariwal, John D. Owens:
Building a Performance Model for Deep Learning Recommendation Model Training on GPUs. HIPC 2022: 48-58 - [c11]Ehsan K. Ardestani, Changkyu Kim, Seung Jae Lee, Luoshang Pan, Jens Axboe, Valmiki Rampersad, Banit Agrawal, Fuxun Yu, Ansha Yu, Trung Le, Hector Yuen, Dheevatsa Mudigere, Shishir Juluri, Akshat Nanda, Manoj Wodekar, Krishnakumar Nair, Maxim Naumov, Chris Petersen, Mikhail Smelyanskiy, Vijay Rao:
Supporting Massive DLRM Inference through Software Defined Memory. ICDCS 2022: 302-312 - [c10]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 - [c9]Zhongyi Lin, Louis Feng, Ehsan K. Ardestani, Jaewon Lee, John Lundell, Changkyu Kim, Arun Kejariwal, John D. Owens:
Building a Performance Model for Deep Learning Recommendation Model Training on GPUs. ISPASS 2022: 227-229 - 2013
- [c8]Ehsan K. Ardestani, Gabriel Southern, Jason Doung, Elnaz Ebrahimi, Jose Renau:
ESESC: A fast performance, power, and temperature multicore simulator. Hot Chips Symposium 2013: 1 - [c7]Ehsan K. Ardestani, Jose Renau:
ESESC: A fast multicore simulator using Time-Based Sampling. HPCA 2013: 448-459 - [c6]Alamelu Sankaranarayanan, Ehsan K. Ardestani, José Luis Briz, Jose Renau:
An energy efficient GPGPU memory hierarchy with tiny incoherent caches. ISLPED 2013: 9-14 - 2012
- [c5]John D. Davis, Suzanne Rivoire, Moisés Goldszmidt, Ehsan K. Ardestani:
CHAOS: Composable Highly Accurate OS-based power models. IISWC 2012: 153-163 - [c4]Ehsan K. Ardestani, Elnaz Ebrahimi, Gabriel Southern, Jose Renau:
Thermal-aware sampling in architectural simulation. ISLPED 2012: 33-38 - 2010
- [c3]Francisco J. Mesa-Martinez, Ehsan K. Ardestani, Jose Renau:
Characterizing processor thermal behavior. ASPLOS 2010: 193-204 - 2009
- [c2]Hamid Safizadeh, Mohammad Tahghighi, Ehsan K. Ardestani, Gholamhossein Tavasoli, Kia Bazargan:
Using randomization to cope with circuit uncertainty. DATE 2009: 815-820 - 2008
- [c1]Ehsan K. Ardestani, Morteza Saheb Zamani, Mehdi Sedighi:
A Fast Transformation-Based Synthesis Algorithm for Reversible Circuits. DSD 2008: 803-806
Informal and Other Publications
- 2023
- [i4]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
- [i3]Zhongyi Lin, Louis Feng, Ehsan K. Ardestani, Jaewon Lee, John Lundell, Changkyu Kim, Arun Kejariwal, John D. Owens:
Building a Performance Model for Deep Learning Recommendation Model Training on GPUs. CoRR abs/2201.07821 (2022) - 2021
- [i2]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) - [i1]Ehsan K. Ardestani, Changkyu Kim, Seung Jae Lee, Luoshang Pan, Valmiki Rampersad, Jens Axboe, Banit Agrawal, Fuxun Yu, Ansha Yu, Trung Le, Hector Yuen, Shishir Juluri, Akshat Nanda, Manoj Wodekar, Dheevatsa Mudigere, Krishnakumar Nair, Maxim Naumov, Chris Peterson, Mikhail Smelyanskiy, Vijay Rao:
Supporting Massive DLRM Inference Through Software Defined Memory. CoRR abs/2110.11489 (2021)
Coauthor Index
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