Bridges-2 Webinar Series
2024 Webinars
Past webinars
Utilizing Bridges-2 for State-of-the-art Open Source Large Language Models
Date: May 24, 2024, 1 pm – 2 pm Eastern time
This webinar will demonstrate how to deploy DL applications with popular large language models, including creating environments, running Jupyter notebooks, and enabling fine-tuning/inference with single or multiple GPUs.
A Hands-On Introduction to Quantum Computing with NVIDIA’s CUDA Quantum
Date: April 19, 2024, 1 pm – 2 pm Eastern time
In this hands-on workshop, we will explore the fundamentals of quantum computing and apply them to construct quantum applications. The workshop will also introduce tools for interfacing quantum and classical components through a commonly used machine learning workflow.
2023 Webinars
Parallel Physics-informed Neural Networks via Domain Decomposition
Date: January 25, 2023, 1 pm – 2 pm Eastern time
During this webinar, a team from Brown University presented a parallel algorithm for conservative PINNs and extended PINNs constructed with a hybrid programming model described by MPI + X, where X ∈{CPUs ,GPUs}.
Multi-GPU MuST
Date: April 19, 2023, 1 pm – 2 pm Eastern time
The MuST package is computational software designed for ab-initio electronic structure calculations for solids. This webinar will describe how to accelerate electronic structure calculations using MuST on multiple GPUs on Bridges-2.
GROMACS on Bridges-2: Optimizing Job Scripts for Performance and Efficiency
Date: June 9, 2 pm – 3 pm Eastern time
This webinar will discuss the run-time options that can affect the performance of a GROMACS job on Bridges-2.
Data-driven computational pipelines
Date: June 26, 2023, 2 pm – 3 pm Eastern time
This webinar reviews frameworks which can empower researchers to build robust and scalable data-driven computational pipelines on Bridges-2.
Utilizing Bridges-2 for Deep Learning Distributed Training
Date: September 26, 2023, 1 pm – 2 pm Eastern time
We will show how to deploy multi-GPU training for deep learning applications, such as with Pytorch and Tensorflow frameworks, using Bridges-2. Topics include how to modify code to run training on a single node or multiple nodes, how to set up an environment, how to run jobs in either interactive or batch mode or with a Jupyter notebook, and factors that affect performance.