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Ehsan K. Ardestani

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

13

Venues

10

Active years

2008–2025

Best venue rank

A*

Where they publish

Papers

13 indexed papers, newest first.

YearVenueTitleAuthors
2025HPCAMachine Learning-Guided Memory Optimization for DLRM Inference on Tiered Memory.Jie Ren, Bin Ma, Shuangyan Yang, Benjamin Francis, Ehsan K. Ardestani, Min Si, Dong Li
2024RecSysToward 100TB Recommendation Models with Embedding Offloading.Intaik Park, Ehsan K. Ardestani, Damian Reeves, Sarunya Pumma, Henry Tsang, Levy Zhao, Jian He, Joshua Deng, Dennis Van Der Staay, Yu Guo, Paul Zhang
2023ISCAMTIA: First Generation Silicon Targeting Meta's Recommendation Systems.Amin Firoozshahian, Joel Coburn, Roman Levenstein, Rakesh Nattoji, Ashwin Kamath, Olvia 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
2022HiPCBuilding a Performance Model for Deep Learning Recommendation Model Training on GPUs.Zhongyi Lin, Louis Feng, Ehsan K. Ardestani, Jaewon Lee, John Lundell, Changkyu Kim, Arun Kejariwal, John D. Owens
2022ICDCSSupporting Massive DLRM Inference through Software Defined Memory.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
2022ISCASoftware-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
2022ISPASSBuilding a Performance Model for Deep Learning Recommendation Model Training on GPUs.Zhongyi Lin, Louis Feng, Ehsan K. Ardestani, Jaewon Lee, John Lundell, Changkyu Kim, Arun Kejariwal, John D. Owens
2013HPCAESESC: A fast multicore simulator using Time-Based Sampling.Ehsan K. Ardestani, Jose Renau
2013ISLPEDAn energy efficient GPGPU memory hierarchy with tiny incoherent caches.Alamelu Sankaranarayanan, Ehsan K. Ardestani, Jos Luis Briz, Jose Renau
2012ISLPEDThermal-aware sampling in architectural simulation.Ehsan K. Ardestani, Elnaz Ebrahimi, Gabriel Southern, Jose Renau
2010ASPLOSCharacterizing processor thermal behavior.Francisco J. Mesa-Martinez, Ehsan K. Ardestani, Jose Renau
2009DATEUsing randomization to cope with circuit uncertainty.Hamid Safizadeh, Mohammad Tahghighi, Ehsan K. Ardestani, Gholamhossein Tavasoli, Kia Bazargan
2008DSDA Fast Transformation-Based Synthesis Algorithm for Reversible Circuits.Ehsan K. Ardestani, Morteza Saheb Zamani, Mehdi Sedighi