Sep 10, 2023 · We study the applicability and performance of deep learning workloads on GPU-enabled composable and traditional HPC computing platforms.
We study the applicability and performance of deep learning workloads on GPU-enabled composable and traditional HPC computing platforms.
The applicability and performance of deep learning workloads on GPU-enabled composable and traditional HPC computing platforms are studied, and the Horovod ...
Request PDF | On Sep 10, 2023, Zhenhua He and others published Performance of Distributed Deep Learning Workloads on a Composable Cyberinfrastructure | Find ...
Performance of Distributed Deep Learning Workloads on a ...
par.nsf.gov › biblio › 10465985-perfor...
"Performance of Distributed Deep Learning Workloads on a Composable Cyberinfrastructure". Practice and Experience in Advanced Research Computing (PEARC '23), ...
The recent advancement of technology in both software and hardware enables us to revisit the concept of the composable architecture in the system design.
Developing Synthetic Applications Benchmarks on Composable Cyberinfrastructure: A Study of Scaling Molecular Dynamics Applications on GPUs. Conference Paper.
Mar 19, 2021 · This paper details the design of an enterprise composable infrastructure that we have implemented and made available to our partners in the IBM Research AI ...
Missing: Cyberinfrastructure. | Show results with:Cyberinfrastructure.
This project funds the development of a dynamically composable high-performance data analysis and computing platform, named ACES. AI and ML are integrated ...
People also ask
What is your experience with distributed systems and deep learning?
What are the methods of distributed deep learning?
PEARC23 Talk: Performance of Distributed Deep Learning Workloads on a Composable Cyberinfrastructure (DOI). Date: July 25 2023, Tuesday (11:00-11:30)