Amar Phanishayee

76 papers A* 19A 9B 1Misc 5Journal 29Unranked 12

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Auto-reconfiguration for Latency Minimization in CPU-based DNN Serving. ICML Ankit Bhardwaj, Amar Phanishayee, Deepak Narayanan, Ryan Stutsman
2025	—	`conf`	Forecasting GPU Performance for Deep Learning Training and Inference. ASPLOS (1) Seonho Lee, Amar Phanishayee, Divya Mahajan
2025	A*	`conf`	Scaling Llama 3 Training with Efficient Parallelism Strategies. ISCA Weiwei Chu, Xinfeng Xie, Jiecao Yu, Jie Wang, Amar Phanishayee, Chunqiang Tang, Yuchen Hao, Jianyu Huang, Mustafa Ozdal, Jun Wang, Vedanuj Goswami, Naman Goyal, Abhishek Kadian, Andrew Gu, Chris Cai, Feng Tian, Xiaodong Wang, Min Si, Pavan Balaji, Ching-Hsiang Chu, Jongsoo Park
2024	A	`conf`	Blox: A Modular Toolkit for Deep Learning Schedulers. EuroSys Saurabh Agarwal, Amar Phanishayee, Shivaram Venkataraman
2024	J	`jnl`	Data-driven Forecasting of Deep Learning Performance on GPUs. CoRR Seonho Lee, Amar Phanishayee, Divya Mahajan
2024	A*	`conf`	DéjàVu: KV-cache Streaming for Fast, Fault-tolerant Generative LLM Serving. ICML Foteini Strati, Sara McAllister, Amar Phanishayee, Jakub Tarnawski, Ana Klimovic
2024	J	`jnl`	DéjàVu: KV-cache Streaming for Fast, Fault-tolerant Generative LLM Serving. CoRR Foteini Strati, Sara McAllister, Amar Phanishayee, Jakub Tarnawski, Ana Klimovic
2024	A*	`conf`	Integrated Hardware Architecture and Device Placement Search. ICML Irene Wang, Jakub Tarnawski, Amar Phanishayee, Divya Mahajan
2024	J	`jnl`	Integrated Hardware Architecture and Device Placement Search. CoRR Irene Wang, Jakub Tarnawski, Amar Phanishayee, Divya Mahajan
2024	A*	`conf`	MGit: A Model Versioning and Management System. ICML Wei Hao, Daniel Mendoza, Rafael Mendes, Deepak Narayanan, Amar Phanishayee, Asaf Cidon, Junfeng Yang
2024	J	`jnl`	Workload-Aware Hardware Accelerator Mining for Distributed Deep Learning Training. CoRR Muhammad Adnan, Amar Phanishayee, Janardhan Kulkarni, Prashant J. Nair, Divya Mahajan
2023	J	`jnl`	Blox: A Modular Toolkit for Deep Learning Schedulers. CoRR Saurabh Agarwal, Amar Phanishayee, Shivaram Venkataraman
2023	J	`jnl`	MGit: A Model Versioning and Management System. CoRR Wei Hao, Daniel Mendoza, Rafael da Silva, Deepak Narayanan, Amar Phanishayee
2023	J	`jnl`	Packrat: Automatic Reconfiguration for Latency Minimization in CPU-based DNN Serving. CoRR Ankit Bhardwaj, Amar Phanishayee, Deepak Narayanan, Mihail Tarta, Ryan Stutsman
2022	Misc	`ed.`	19th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2022, Renton, WA, USA, April 4-6, 2022 NSDI Amar Phanishayee, Vyas Sekar
2022	J	`jnl`	A Study on the Intersection of GPU Utilization and CNN Inference. CoRR Jack Kosaian, Amar Phanishayee
2022	J	`jnl`	Harmony: Overcoming the hurdles of GPU memory capacity to train massive DNN models on commodity servers. CoRR Youjie Li, Amar Phanishayee, Derek Murray, Jakub Tarnawski, Nam Sung Kim
2022	J	`jnl`	Harmony: Overcoming the hurdles of GPU memory capacity to train massive DNN models on commodity servers. Proc. VLDB Endow. Youjie Li, Amar Phanishayee, Derek Murray, Jakub Tarnawski, Nam Sung Kim
2022	A*	`conf`	Looking Beyond GPUs for DNN Scheduling on Multi-Tenant Clusters. OSDI Jayashree Mohan, Amar Phanishayee, Janardhan Kulkarni, Vijay Chidambaram
2021	J	`jnl`	Analyzing and Mitigating Data Stalls in DNN Training. Proc. VLDB Endow. Jayashree Mohan, Amar Phanishayee, Ashish Raniwala, Vijay Chidambaram
2021	A*	`conf`	Boosting the Throughput and Accelerator Utilization of Specialized CNN Inference Beyond Increasing Batch Size. ICML Jack Kosaian, Amar Phanishayee, Matthai Philipose, Debadeepta Dey, Rashmi Vinayak
2021	A	`conf`	CheckFreq: Frequent, Fine-Grained DNN Checkpointing. FAST Jayashree Mohan, Amar Phanishayee, Vijay Chidambaram
2021	A	`conf`	Doing more with less: training large DNN models on commodity servers for the masses. HotOS Youjie Li, Amar Phanishayee, Derek Murray, Nam Sung Kim
2021	J	`jnl`	Efficient Large-Scale Language Model Training on GPU Clusters. CoRR Deepak Narayanan, Mohammad Shoeybi, Jared Casper, Patrick LeGresley, Mostofa Patwary, Vijay Korthikanti, Dmitri Vainbrand, Prethvi Kashinkunti, Julie Bernauer, Bryan Catanzaro, Amar Phanishayee, Matei Zaharia
2021	A	`conf`	Efficient large-scale language model training on GPU clusters using megatron-LM. SC Deepak Narayanan, Mohammad Shoeybi, Jared Casper, Patrick LeGresley, Mostofa Patwary, Vijay Korthikanti, Dmitri Vainbrand, Prethvi Kashinkunti, Julie Bernauer, Bryan Catanzaro, Amar Phanishayee, Matei Zaharia
2021	A*	`conf`	Memory-Efficient Pipeline-Parallel DNN Training. ICML Deepak Narayanan, Amar Phanishayee, Kaiyu Shi, Xie Chen, Matei Zaharia
2021	A*	`conf`	Piper: Multidimensional Planner for DNN Parallelization. NeurIPS Jakub Tarnawski, Deepak Narayanan, Amar Phanishayee
2021	J	`jnl`	Synergy: Resource Sensitive DNN Scheduling in Multi-Tenant Clusters. CoRR Jayashree Mohan, Amar Phanishayee, Janardhan Kulkarni, Vijay Chidambaram
2020	—	`ed.`	12th USENIX Workshop on Hot Topics in Cloud Computing, HotCloud 2020, July 13-14, 2020 HotCloud Amar Phanishayee, Ryan Stutsman
2020	J	`jnl`	Analyzing and Mitigating Data Stalls in DNN Training. CoRR Jayashree Mohan, Amar Phanishayee, Ashish Raniwala, Vijay Chidambaram
2020	—	`conf`	Blink: Fast and Generic Collectives for Distributed ML. MLSys Guanhua Wang, Shivaram Venkataraman, Amar Phanishayee, Jorgen Thelin, Nikhil R. Devanur, Ion Stoica
2020	—	`conf`	Daydream: Accurately Estimating the Efficacy of Optimizations for DNN Training. USENIX ATC Hongyu Zhu, Amar Phanishayee, Gennady Pekhimenko
2020	J	`jnl`	Daydream: Accurately Estimating the Efficacy of Optimizations for DNN Training. CoRR Hongyu Zhu, Amar Phanishayee, Gennady Pekhimenko
2020	A*	`conf`	Efficient Algorithms for Device Placement of DNN Graph Operators. NeurIPS Jakub Tarnawski, Amar Phanishayee, Nikhil R. Devanur, Divya Mahajan, Fanny Nina Paravecino
2020	J	`jnl`	Efficient Algorithms for Device Placement of DNN Graph Operators. CoRR Jakub Tarnawski, Amar Phanishayee, Nikhil R. Devanur, Divya Mahajan, Fanny Nina Paravecino
2020	A*	`conf`	Heterogeneity-Aware Cluster Scheduling Policies for Deep Learning Workloads. OSDI Deepak Narayanan, Keshav Santhanam, Fiodar Kazhamiaka, Amar Phanishayee, Matei Zaharia
2020	J	`jnl`	Heterogeneity-Aware Cluster Scheduling Policies for Deep Learning Workloads. CoRR Deepak Narayanan, Keshav Santhanam, Fiodar Kazhamiaka, Amar Phanishayee, Matei Zaharia
2020	J	`jnl`	Memory-Efficient Pipeline-Parallel DNN Training. CoRR Deepak Narayanan, Amar Phanishayee, Kaiyu Shi, Xie Chen, Matei Zaharia
2020	A*	`conf`	The Non-IID Data Quagmire of Decentralized Machine Learning. ICML Kevin Hsieh, Amar Phanishayee, Onur Mutlu, Phillip B. Gibbons
2020	Misc	`conf`	Themis: Fair and Efficient GPU Cluster Scheduling. NSDI Kshiteej Mahajan, Arjun Balasubramanian, Arjun Singhvi, Shivaram Venkataraman, Aditya Akella, Amar Phanishayee, Shuchi Chawla
2019	—	`conf`	Analysis of Large-Scale Multi-Tenant GPU Clusters for DNN Training Workloads. USENIX ATC Myeongjae Jeon, Shivaram Venkataraman, Amar Phanishayee, Junjie Qian, Wencong Xiao, Fan Yang
2019	J	`jnl`	Analysis of Large-Scale Multi-Tenant GPU Clusters for DNN Training Workloads. CoRR Myeongjae Jeon, Shivaram Venkataraman, Amar Phanishayee, Junjie Qian, Wencong Xiao, Fan Yang
2019	J	`jnl`	Blink: Fast and Generic Collectives for Distributed ML. CoRR Guanhua Wang, Shivaram Venkataraman, Amar Phanishayee, Jorgen Thelin, Nikhil R. Devanur, Ion Stoica
2019	A*	`conf`	PipeDream: generalized pipeline parallelism for DNN training. SOSP Deepak Narayanan, Aaron Harlap, Amar Phanishayee, Vivek Seshadri, Nikhil R. Devanur, Gregory R. Ganger, Phillip B. Gibbons, Matei Zaharia
2019	—	`conf`	The Case for Unifying Data Loading in Machine Learning Clusters. HotCloud Aarati Kakaraparthy, Abhay Venkatesh, Amar Phanishayee, Shivaram Venkataraman
2019	J	`jnl`	The Non-IID Data Quagmire of Decentralized Machine Learning. CoRR Kevin Hsieh, Amar Phanishayee, Onur Mutlu, Phillip B. Gibbons
2019	J	`jnl`	Themis: Fair and Efficient GPU Cluster Scheduling for Machine Learning Workloads. CoRR Kshiteej Mahajan, Arjun Singhvi, Arjun Balasubramanian, Varun Batra, Surya Teja Chavali, Shivaram Venkataraman, Aditya Akella, Amar Phanishayee, Shuchi Chawla
2018	—	`conf`	Benchmarking and Analyzing Deep Neural Network Training. IISWC Hongyu Zhu, Mohamed Akrout, Bojian Zheng, Andrew Pelegris, Anand Jayarajan, Amar Phanishayee, Bianca Schroeder, Gennady Pekhimenko
2018	J	`jnl`	Compositional programming and testing of dynamic distributed systems. Proc. ACM Program. Lang. Ankush Desai, Amar Phanishayee, Shaz Qadeer, Sanjit A. Seshia
2018	A*	`conf`	Gist: Efficient Data Encoding for Deep Neural Network Training. ISCA Animesh Jain, Amar Phanishayee, Jason Mars, Lingjia Tang, Gennady Pekhimenko
2018	J	`jnl`	Parameter Hub: High Performance Parameter Servers for Efficient Distributed Deep Neural Network Training. CoRR Liang Luo, Jacob Nelson, Luis Ceze, Amar Phanishayee, Arvind Krishnamurthy
2018	—	`conf`	Parameter Hub: a Rack-Scale Parameter Server for Distributed Deep Neural Network Training. SoCC Liang Luo, Jacob Nelson, Luis Ceze, Amar Phanishayee, Arvind Krishnamurthy
2018	J	`jnl`	Parameter Hub: a Rack-Scale Parameter Server for Distributed Deep Neural Network Training. CoRR Liang Luo, Jacob Nelson, Luis Ceze, Amar Phanishayee, Arvind Krishnamurthy
2018	J	`jnl`	PipeDream: Fast and Efficient Pipeline Parallel DNN Training. CoRR Aaron Harlap, Deepak Narayanan, Amar Phanishayee, Vivek Seshadri, Nikhil R. Devanur, Gregory R. Ganger, Phillip B. Gibbons
2018	J	`jnl`	TBD: Benchmarking and Analyzing Deep Neural Network Training. CoRR Hongyu Zhu, Mohamed Akrout, Bojian Zheng, Andrew Pelegris, Amar Phanishayee, Bianca Schroeder, Gennady Pekhimenko
2017	A	`conf`	Atomic In-place Updates for Non-volatile Main Memories with Kamino-Tx. EuroSys Amir Saman Memaripour, Anirudh Badam, Amar Phanishayee, Yanqi Zhou, Ramnatthan Alagappan, Karin Strauss, Steven Swanson
2017	Misc	`conf`	RAIL: A Case for Redundant Arrays of Inexpensive Links in Data Center Networks. NSDI Danyang Zhuo, Monia Ghobadi, Ratul Mahajan, Amar Phanishayee, Xuan Kelvin Zou, Hang Guan, Arvind Krishnamurthy, Thomas E. Anderson
2016	—	`conf`	Beam: Ending Monolithic Applications for Connected Devices. USENIX ATC Chenguang Shen, Rayman Preet Singh, Amar Phanishayee, Aman Kansal, Ratul Mahajan
2016	—	`conf`	Evaluation of elastic modulation gains in microsoft's optical backbone in North America. OFC Monia Ghobadi, Jamie Gaudette, Ratul Mahajan, Amar Phanishayee, Buddy Klinkers, Daniel C. Kilper
2016	A*	`conf`	ProjecToR: Agile Reconfigurable Data Center Interconnect. SIGCOMM Monia Ghobadi, Ratul Mahajan, Amar Phanishayee, Nikhil R. Devanur, Janardhan Kulkarni, Gireeja Ranade, Pierre-Alexandre Blanche, Houman Rastegarfar, Madeleine Glick, Daniel C. Kilper
2015	A	`conf`	A Case for Ending Monolithic Apps for Connected Devices. HotOS Rayman Preet Singh, Chenguang Shen, Amar Phanishayee, Aman Kansal, Ratul Mahajan
2015	J	`jnl`	It's Time to End Monolithic Apps for Connected Devices. login Usenix Mag. Rayman Preet Singh, Chenguang Shen, Amar Phanishayee, Aman Kansal, Ratul Mahajan
2014	Misc	`conf`	Bolt: Data Management for Connected Homes. NSDI Trinabh Gupta, Rayman Preet Singh, Amar Phanishayee, Jaeyeon Jung, Ratul Mahajan
2013	A*	`conf`	HomeLab: a platform for conducting experiments with connected devices in the home. SIGCOMM Rayman Preet Singh, A. J. Bernheim Brush, Evgeni Filippov, Danny Huang, Ratul Mahajan, Khurshed Mazhar, Amar Phanishayee, Arjmand Samuel
2013	—	`conf`	Lab of things: a platform for conducting studies with connected devices in multiple homes. UbiComp (Adjunct Publication) A. J. Bernheim Brush, Evgeni Filippov, Danny Huang, Jaeyeon Jung, Ratul Mahajan, Frank Martinez, Khurshed Mazhar, Amar Phanishayee, Arjmand Samuel, James Scott, Rayman Preet Singh
2011	J	`jnl`	FAWN: a fast array of wimpy nodes. Commun. ACM David G. Andersen, Jason Franklin, Michael Kaminsky, Amar Phanishayee, Lawrence Tan, Vijay Vasudevan
2009	A*	`conf`	FAWN: a fast array of wimpy nodes. SOSP David G. Andersen, Jason Franklin, Michael Kaminsky, Amar Phanishayee, Lawrence Tan, Vijay Vasudevan
2009	A	`conf`	FAWNdamentally Power-efficient Clusters. HotOS Vijay Vasudevan, Jason Franklin, David G. Andersen, Amar Phanishayee, Lawrence Tan, Michael Kaminsky, Iulian Moraru
2009	A*	`conf`	Safe and effective fine-grained TCP retransmissions for datacenter communication. SIGCOMM Vijay Vasudevan, Amar Phanishayee, Hiral Shah, Elie Krevat, David G. Andersen, Gregory R. Ganger, Garth A. Gibson, Brian Mueller
2009	A	`conf`	Scaling all-pairs overlay routing. CoNEXT David A. Sontag, Yang Zhang, Amar Phanishayee, David G. Andersen, David R. Karger
2008	A*	`conf`	Ditto: a system for opportunistic caching in multi-hop wireless networks. MobiCom Fahad R. Dogar, Amar Phanishayee, Himabindu Pucha, Olatunji Ruwase, David G. Andersen
2008	A	`conf`	Measurement and Analysis of TCP Throughput Collapse in Cluster-based Storage Systems. FAST Amar Phanishayee, Elie Krevat, Vijay Vasudevan, David G. Andersen, Gregory R. Ganger, Garth A. Gibson, Srinivasan Seshan
2007	—	`conf`	On application-level approaches to avoiding TCP throughput collapse in cluster-based storage systems. PDSW Elie Krevat, Vijay Vasudevan, Amar Phanishayee, David G. Andersen, Gregory R. Ganger, Garth A. Gibson, Srinivasan Seshan
2007	Misc	`conf`	Ricochet: Lateral Error Correction for Time-Critical Multicast. NSDI Mahesh Balakrishnan, Kenneth P. Birman, Amar Phanishayee, Stefan Pleisch
2007	—	`conf`	Scalable Multicast Platforms for a New Generation of Robust Distributed Applications. COMSWARE Ken Birman, Mahesh Balakrishnan, Danny Dolev, Tudor Marian, Krzysztof Ostrowski, Amar Phanishayee
2006	B	`conf`	PLATO: Predictive Latency-Aware Total Ordering. SRDS Mahesh Balakrishnan, Ken Birman, Amar Phanishayee