Srinivas Sridharan

According to our database, Srinivas Sridharan authored at least 28 papers between 2007 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Towards a Standardized Representation for Deep Learning Collective Algorithms.

Jinsun Yoo, William Won, Meghan Cowan, Nan Jiang, Benjamin Klenk, Srinivas Sridharan, Tushar Krishna

Proceedings of the IEEE Symposium on High-Performance Interconnects, 2024

2023

Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces.

Srinivas Sridharan, Taekyung Heo, Louis Feng, Zhaodong Wang, Matt Bergeron, Wenyin Fu, Shengbao Zheng, Brian Coutinho, Saeed Rashidi, Changhai Man, Tushar Krishna

CoRR, 2023

Better Together: Jointly Optimizing ML Collective Scheduling and Execution Planning using SYNDICATE.

Kshiteej Mahajan, Ching-Hsiang Chu, Srinivas Sridharan, Aditya Akella

Proceedings of the 20th USENIX Symposium on Networked Systems Design and Implementation, 2023

ASTRA-sim2.0: Modeling Hierarchical Networks and Disaggregated Systems for Large-model Training at Scale.

William Won, Taekyung Heo, Saeed Rashidi, Srinivas Sridharan, Sudarshan Srinivasan, Tushar Krishna

Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2023

2022

Themis: a network bandwidth-aware collective scheduling policy for distributed training of DL models.

Saeed Rashidi, William Won, Sudarshan Srinivasan, Srinivas Sridharan, Tushar Krishna

Proceedings of the ISCA '22: The 49th Annual International Symposium on Computer Architecture, New York, New York, USA, June 18, 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, 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

Proceedings of the ISCA '22: The 49th Annual International Symposium on Computer Architecture, New York, New York, USA, June 18, 2022

Impact of RoCE Congestion Control Policies on Distributed Training of DNNs.

Tarannum Khan, Saeed Rashidi, Srinivas Sridharan, Pallavi Shurpali, Aditya Akella, Tushar Krishna

Proceedings of the IEEE Symposium on High-Performance Interconnects, 2022

2021

High-performance, Distributed Training of Large-scale Deep Learning Recommendation Models.

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

CoRR, 2021

Enabling Compute-Communication Overlap in Distributed Deep Learning Training Platforms.

Saeed Rashidi, Matthew Denton, Srinivas Sridharan, Sudarshan Srinivasan, Amoghavarsha Suresh, Jade Nie, Tushar Krishna

Proceedings of the 48th ACM/IEEE Annual International Symposium on Computer Architecture, 2021

2020

Efficient Communication Acceleration for Next-Gen Scale-up Deep Learning Training Platforms.

Saeed Rashidi, Srinivas Sridharan, Sudarshan Srinivasan, Matthew Denton, Tushar Krishna

CoRR, 2020

Deep Learning Training in Facebook Data Centers: Design of Scale-up and Scale-out Systems.

Maxim Naumov, John Kim, Dheevatsa Mudigere, Srinivas Sridharan, Xiaodong Wang, Whitney Zhao, Serhat Yilmaz, Changkyu Kim, Hector Yuen, Mustafa Ozdal, Krishnakumar Nair, Isabel Gao, Bor-Yiing Su, Jiyan Yang, Mikhail Smelyanskiy

CoRR, 2020

ASTRA-SIM: Enabling SW/HW Co-Design Exploration for Distributed DL Training Platforms.

Saeed Rashidi, Srinivas Sridharan, Sudarshan Srinivasan, Tushar Krishna

Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2020

Scalable Distributed Training of Recommendation Models: An ASTRA-SIM + NS3 case-study with TCP/IP transport.

Saeed Rashidi, Pallavi Shurpali, Srinivas Sridharan, Naader Hassani, Dheevatsa Mudigere, Krishnakumar Nair, Misha Smelyanski, Tushar Krishna

Proceedings of the IEEE Symposium on High-Performance Interconnects, 2020

2019

Planning for performance: Enhancing achievable performance for MPI through persistent collective operations.

Daniel J. Holmes, Bradley Morgan, Anthony Skjellum, Purushotham V. Bangalore, Srinivas Sridharan

Parallel Comput., 2019

Automatic Model Parallelism for Deep Neural Networks with Compiler and Hardware Support.

Sanket Tavarageri, Srinivas Sridharan, Bharat Kaul

CoRR, 2019

TensorFlow at Scale: Performance and productivity analysis of distributed training with Horovod, MLSL, and Cray PE ML.

Thorsten Kurth, Mikhail Smorkalov, Peter Mendygral, Srinivas Sridharan, Amrita Mathuriya

Concurr. Comput. Pract. Exp., 2019

Training Google Neural Machine Translation on an Intel CPU Cluster.

Dhiraj D. Kalamkar, Kunal Banerjee, Sudarshan Srinivasan, Srinivas Sridharan, Evangelos Georganas, Mikhail E. Smorkalov, Cong Xu, Alexander Heinecke

Proceedings of the 2019 IEEE International Conference on Cluster Computing, 2019

2018

On Scale-out Deep Learning Training for Cloud and HPC.

Srinivas Sridharan, Karthikeyan Vaidyanathan, Dhiraj D. Kalamkar, Dipankar Das, Mikhail E. Smorkalov, Mikhail Shiryaev, Dheevatsa Mudigere, Naveen Mellempudi, Sasikanth Avancha, Bharat Kaul, Pradeep Dubey

CoRR, 2018

Mixed Precision Training of Convolutional Neural Networks using Integer Operations.

Dipankar Das, Naveen Mellempudi, Dheevatsa Mudigere, Dhiraj D. Kalamkar, Sasikanth Avancha, Kunal Banerjee, Srinivas Sridharan, Karthik Vaidyanathan, Bharat Kaul, Evangelos Georganas, Alexander Heinecke, Pradeep Dubey, Jesús Corbal, Nikita Shustrov, Roman Dubtsov, Evarist Fomenko, Vadim O. Pirogov

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Deep learning at 15PF: supervised and semi-supervised classification for scientific data.

Thorsten Kurth, Jian Zhang, Nadathur Satish, Evan Racah, Ioannis Mitliagkas, Md. Mostofa Ali Patwary, Tareq M. Malas, Narayanan Sundaram, Wahid Bhimji, Mikhail Smorkalov, Jack Deslippe, Mikhail Shiryaev, Srinivas Sridharan, Prabhat, Pradeep Dubey

Proceedings of the International Conference for High Performance Computing, 2017

Planning for performance: persistent collective operations for MPI.

Bradley Morgan, Daniel J. Holmes, Anthony Skjellum, Purushotham V. Bangalore, Srinivas Sridharan

Proceedings of the 24th European MPI Users' Group Meeting, 2017

2016

Distributed Deep Learning Using Synchronous Stochastic Gradient Descent.

Dipankar Das, Sasikanth Avancha, Dheevatsa Mudigere, Karthikeyan Vaidyanathan, Srinivas Sridharan, Dhiraj D. Kalamkar, Bharat Kaul, Pradeep Dubey

CoRR, 2016

Comparing Runtime Systems with Exascale Ambitions Using the Parallel Research Kernels.

Rob F. Van der Wijngaart, Abdullah Kayi, Jeff R. Hammond, Gabriele Jost, Tom St. John, Srinivas Sridharan, Timothy G. Mattson, John Abercrombie, Jacob Nelson

Proceedings of the High Performance Computing - 31st International Conference, 2016

2015

Exploring Shared-Memory Optimizations for an Unstructured Mesh CFD Application on Modern Parallel Systems.

Dheevatsa Mudigere, Srinivas Sridharan, Anand M. Deshpande, Jongsoo Park, Alexander Heinecke, Mikhail Smelyanskiy, Bharat Kaul, Pradeep Dubey, Dinesh K. Kaushik, David E. Keyes

Proceedings of the 2015 IEEE International Parallel and Distributed Processing Symposium, 2015

2014

Enabling Efficient Multithreaded MPI Communication through a Library-Based Implementation of MPI Endpoints.

Srinivas Sridharan, James Dinan, Dhiraj D. Kalamkar

Proceedings of the International Conference for High Performance Computing, 2014

2012

Extending the BT NAS parallel benchmark to exascale computing.

Rob F. Van der Wijngaart, Srinivas Sridharan, Victor W. Lee

Proceedings of the SC Conference on High Performance Computing Networking, 2012

High Performance Non-uniform FFT on Modern X86-based Multi-core Systems.

Dhiraj D. Kalamkar, Joshua D. Trzasko, Srinivas Sridharan, Mikhail Smelyanskiy, Daehyun Kim, Armando Manduca, Yunhong Shu, Matt A. Bernstein, Bharat Kaul, Pradeep Dubey

Proceedings of the 26th IEEE International Parallel and Distributed Processing Symposium, 2012

2007

Evaluating synchronization techniques for light-weight multithreaded/multicore architectures.

Srinivas Sridharan, Arun Rodrigues, Peter M. Kogge

Proceedings of the SPAA 2007: Proceedings of the 19th Annual ACM Symposium on Parallelism in Algorithms and Architectures, 2007