Srinivas Sridharan

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Thread Migration to Improve Synchronization Performance

Surendar Chandra, Richard C. Murphy, Srinivas Sridharan, 2006 .

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

Tushar Krishna, Sudarshan Srinivasan, Srinivas Sridharan, 2020, ArXiv.

Optimal control of quantum systems using dynamic programming

Srinivas Sridharan, 2010 .

Training Google Neural Machine Translation on an Intel CPU Cluster

Alexander Heinecke, Kunal Banerjee, Evangelos Georganas, 2019, 2019 IEEE International Conference on Cluster Computing (CLUSTER).

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

Sanket Tavarageri, Bharat Kaul, Srinivas Sridharan, 2019, ArXiv.

Distributed Deep Learning Using Synchronous Stochastic Gradient Descent pdf

Pradeep Dubey, Karthikeyan Vaidyanathan, Dheevatsa Mudigere, 2016, ArXiv.

Extending the BT NAS Parallel Benchmark to exascale computing

Victor W. Lee, Rob F. Van der Wijngaart, Srinivas Sridharan, 2012, 2012 International Conference for High Performance Computing, Networking, Storage and Analysis.

Evaluating synchronization techniques for light-weight multithreaded/multicore architectures

Peter M. Kogge, Arun Rodrigues, Srinivas Sridharan, 2007, SPAA '07.

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

James Dinan, Dhiraj D. Kalamkar, Srinivas Sridharan, 2014, SC14: International Conference for High Performance Computing, Networking, Storage and Analysis.

Using the Parallel Research Kernels to Study PGAS Models

Timothy G. Mattson, Jeff R. Hammond, Abdullah Kayi, 2015, 2015 9th International Conference on Partitioned Global Address Space Programming Models.

Deep Learning at 15PF : Supervised and Semi-Supervised Classification for Scientific Data

Ioannis Mitliagkas, Prabhat, Pradeep Dubey, 2017, SC17: International Conference for High Performance Computing, Networking, Storage and Analysis.

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

Pradeep Dubey, Matt A. Bernstein, Yunhong Shu, 2012, 2012 IEEE 26th International Parallel and Distributed Processing Symposium.

Compiler and Runtime Techniques for Software Transactional Memory in Partitioned Global Address Space Languages and Runtime Libraries

Srinivas Sridharan, 2010 .

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

Tushar Krishna, Sudarshan Srinivasan, Srinivas Sridharan, 2020, 2020 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS).

Comparing Runtime Systems with Exascale Ambitions Using the Parallel Research Kernels

Jacob Nelson, Timothy G. Mattson, Rob F. Van der Wijngaart, 2016, ISC.

Implementing Scalable Locks and Barriers on Large-Scale Light-Weight Multithreaded Systems

Srinivas Sridharan, 2006 .

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

Pradeep Dubey, David E. Keyes, Alexander Heinecke, 2015, 2015 IEEE International Parallel and Distributed Processing Symposium.

Mixed Precision Training of Convolutional Neural Networks using Integer Operations pdf

Pradeep Dubey, Alexander Heinecke, Karthikeyan Vaidyanathan, 2018, ICLR.

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

Pradeep Dubey, Karthikeyan Vaidyanathan, Dheevatsa Mudigere, 2018, ArXiv.

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

Yuchen Hao, Jianyu Huang, Kiran Kumar Matam, 2021, ArXiv.