Srinivas Sridharan, Phd
Srinivas Sridharan, Phd
Distinguished Engineer, NVIDIA
Verified email at - Homepage
Cited by
Cited by
Distributed deep learning using synchronous stochastic gradient descent
D Das, S Avancha, D Mudigere, K Vaidynathan, S Sridharan, D Kalamkar, ...
arXiv preprint arXiv:1602.06709, 2016
Mixed precision training of convolutional neural networks using integer operations
D Das, N Mellempudi, D Mudigere, D Kalamkar, S Avancha, K Banerjee, ...
arXiv preprint arXiv:1802.00930, 2018
Deep learning at 15pf: supervised and semi-supervised classification for scientific data
T Kurth, J Zhang, N Satish, E Racah, I Mitliagkas, MMA Patwary, T Malas, ...
Proceedings of the International Conference for High Performance Computing …, 2017
Deep learning training in facebook data centers: Design of scale-up and scale-out systems
M Naumov, J Kim, D Mudigere, S Sridharan, X Wang, W Zhao, S Yilmaz, ...
arXiv preprint arXiv:2003.09518, 2020
Machine learning accelerator mechanism
A Bleiweiss, A Ramesh, A Mishra, D Marr, J Cook, S Sridharan, ...
US Patent 11,373,088, 2022
Software-hardware co-design for fast and scalable training of deep learning recommendation models
D Mudigere, Y Hao, J Huang, Z Jia, A Tulloch, S Sridharan, X Liu, ...
Proceedings of the 49th Annual International Symposium on Computer …, 2022
Abstraction layers for scalable distributed machine learning
DD Kalamkar, K Vaidyanathan, S Sridharan, D Das
US Patent 11,094,029, 2021
Fine-grain compute communication execution for deep learning frameworks
S Sridharan, D Mudigere
US Patent App. 15/869,502, 2018
Enabling efficient multithreaded MPI communication through a library-based implementation of MPI endpoints
S Sridharan, J Dinan, DD Kalamkar
SC'14: Proceedings of the International Conference for High Performance …, 2014
Communication optimizations for distributed machine learning
S Sridharan, K Vaidyanathan, D Das, C Sakthivel, ME Smorkalov
US Patent 11,270,201, 2022
High-performance, distributed training of large-scale deep learning recommendation models
D Mudigere, Y Hao, J Huang, A Tulloch, S Sridharan, X Liu, M Ozdal, ...
arXiv preprint arXiv:2104.05158, 2021
Dynamic precision management for integer deep learning primitives
N Mellempudi, D Mudigere, D Das, S Sridharan
US Patent 10,643,297, 2020
Thread migration to improve synchronization performance
S Sridharan, B Keck, R Murphy, S Chandra, P Kogge
Workshop on Operating System Interference in High Performance Applications, 2006
On scale-out deep learning training for cloud and hpc
S Sridharan, K Vaidyanathan, D Kalamkar, D Das, ME Smorkalov, ...
arXiv preprint arXiv:1801.08030, 2018
Astra-sim: Enabling sw/hw co-design exploration for distributed dl training platforms
S Rashidi, S Sridharan, S Srinivasan, T Krishna
2020 IEEE International Symposium on Performance Analysis of Systems and …, 2020
Data parallelism and halo exchange for distributed machine learning
D Das, K Vaidyanathan, S Sridharan
US Patent 11,373,266, 2022
Mahmoud khorashadi, Pallab Bhattacharya, Petr Lapukhov, Maxim Naumov, Ajit Mathews, Lin Qiao, Mikhail Smelyanskiy, Bill Jia, and Vijay Rao. 2021. Software-Hardware Co-design …
D Mudigere, Y Hao, J Huang, Z Jia, A Tulloch, S Sridharan, X Liu, ...
arXiv preprint arXiv:2104.05158, 2022
Memory in processor: A novel design paradigm for supercomputing architectures
N Venkateswaran, WR Foundation, A Krishnan, SN Kumar, A Shriraman, ...
ACM SIGARCH Computer Architecture News 32 (3), 19-26, 2003
Enabling compute-communication overlap in distributed deep learning training platforms
S Rashidi, M Denton, S Sridharan, S Srinivasan, A Suresh, J Nie, ...
2021 ACM/IEEE 48th Annual International Symposium on Computer Architecture …, 2021
Comparing runtime systems with exascale ambitions using the parallel research kernels
RF Van der Wijngaart, A Kayi, JR Hammond, G Jost, T St. John, ...
High Performance Computing: 31st International Conference, ISC High …, 2016
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