E-LIB Suche - Ergebnisse für: Shankar, Mallikarjun Arjun

1

DeepThermo: Deep Learning Accelerated Parallel Monte Carlo ..:

, In: 2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS),

Yin, Junqi ; Wang, Feiyi ; Shankar, Mallikarjun Arjun - p. 333-343 , 2023

Link: https://doi.org/10.1109/..

2

FORGE: Pre-Training Open Foundation Models for Science:

, In: SC23: International Conference for High Performance Computing, Networking, Storage and Analysis,

Yin, Junqi ; Dash, Sajal ; Wang, Feiyi. - p. 1-13 , 2023

Link: https://doi.org/10.1145/..

3

Comparative evaluation of deep learning workloads for leade..:

Yin, Junqi ; Tsaris, Aristeidis ; Dash, Sajal...
BenchCouncil Transactions on Benchmarks, Standards and Evaluations. 1 (2021) 1 - p. 100005 , 2021

Link: https://doi.org/10.1016/..

4

Comparative evaluation of deep learning workloads for leade..:

Junqi Yin ; Aristeidis Tsaris ; Sajal Dash...
http://www.sciencedirect.com/science/article/pii/S2772485921000053. , 2021

Link: https://doi.org/10.1016/..

5

Zero coordinate shift: Whetted automatic differentiation fo..:

Leng, Kuangdai ; Shankar, Mallikarjun ; Thiyagalingam, Jeyan
Journal of Computational Physics. 505 (2024) - p. 112904 , 2024

Link: https://doi.org/10.1016/..

6

FORGE: Pre-Training Open Foundation Models for Science:

, In: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis,

Yin, Junqi ; Dash, Sajal ; Wang, Feiyi. - p. 1-13 , 2023

Link: https://dl.acm.org/doi/1..

7

Strategies for Integrating Deep Learning Surrogate Models w..:

, In: 2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW),

Yin, Junqi ; Wang, Feiyi ; Shankar, Mallikarjun - p. 01-10 , 2022

Link: https://doi.org/10.1109/..

8

WfBench: Automated Generation of Scientific Workflow Benchm..:

, In: 2022 IEEE/ACM International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS),

Coleman, Taina ; Casanova, Henri ; Maheshwari, Ketan... - p. 100-111 , 2022

Link: https://doi.org/10.1109/..

9

Scientific machine learning benchmarks:

Thiyagalingam, Jeyan ; Shankar, Mallikarjun ; Fox, Geoffrey.
Nature Reviews Physics. 4 (2022) 6 - p. 413-420 , 2022

Link: https://doi.org/10.1038/..

10

AI Benchmarking for Science: Efforts from the MLCommons Sci..:

, In: Lecture Notes in Computer Science; High Performance Computing. ISC High Performance 2022 International Workshops,

Thiyagalingam, Jeyan ; von Laszewski, Gregor ; Yin, Junqi... - p. 47-64 , 2022

Link: https://doi.org/10.1007/..

11

Mitigating Catastrophic Forgetting in Deep Learning in a St..:

, In: 2021 7th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD-7),

Dash, Sajal ; Yin, Junqi ; Shankar, Mallikarjun.. - p. 11-18 , 2021

Link: https://doi.org/10.1109/..

12

GPU lifetimes on titan supercomputer : survival analysis..:

, In: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis,

Ostrouchov, George ; Maxwell, Don ; Ashraf, Rizwan A.... - p. 1-14 , 2020

Link: https://dl.acm.org/doi/1..

13

A Systemic Approach to Facilitating Reproducibility via Fed..:

, In: Communications in Computer and Information Science; Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI,

Stansberry, Dale ; Somnath, Suhas ; Shutt, Gregory. - p. 83-98 , 2020

Link: https://doi.org/10.1007/..

14

Strategies to Deploy and Scale Deep Learning on the Summit ..:

, In: 2019 IEEE/ACM Third Workshop on Deep Learning on Supercomputers (DLS),

Yin, Junqi ; Gahlot, Shubhankar ; Laanait, Nouamane... - p. 84-94 , 2019

Link: https://doi.org/10.1109/..

15

DataFed: Towards Reproducible Research via Federated Data M..:

, In: 2019 International Conference on Computational Science and Computational Intelligence (CSCI),

Stansberry, Dale ; Somnath, Suhas ; Breet, Jessica.. - p. 1312-1317 , 2019

Link: https://doi.org/10.1109/..