Past Events

When you need support from the Anvil team for a complex workflow, or want to discuss your ideas directly with our team, please consider registering for Anvil Support Hour! We will be available every Thursday from 2:00pm-3:00pm EST via Zoom. Reserve your 20-minute slot for our discussion! Topics for our conversation can be about:

This workshop will include two talks about optimizing, profiling, and benchmarking input/output operations using HDF5 and DLIO.

Hosted by our development team, Zoom open office hours are the perfect opportunity to ask questions or make a suggestion. They are held on the second Tuesday of every month from 11:15 a.m. to 12:45 p.m. ET.

More information and Zoom coordinates are available on the Open OnDemand Discourse forum.

In this initial RCAC Generative AI Series workshop, attendees will explore the art and science of prompt engineering in the realm of generative AI. This session is designed to provide practical insights into crafting effective prompts to generate more relevant and accurate results. While prior knowledge of deep learning fundamentals will be beneficial, the workshop will offer a broad overview suitable for various participants, from students to faculty.

During office hours you can ask questions about running workflows or bags of tasks on ACCESS resources. These sessions are an excellent opportunity for both new and existing users to learn and engage. You can expect:

This webinar in the ByteBoost program https://www.stonybrook.edu/ookami/ByteBoost.php will present  https://hprc.tamu.edu/aces/ , an innovative composable hardware platform that helps accelerate transformative changes in multiple scientific research areas. ACES offers a rich accelerator testbed consisting of five different cutting edge accelerators including NVIDIA and Intel Ponte Vecchio GPUs (Graphics Processing Units) and Graphcore IPUs (Intelligence Processing Units).

We will cover typical approaches to moving your computations to HPC resources – use of applications/software packages already available on the system through Linux environment modules; compiling code from source with information on compilers, libraries, and optimization flags to use; setting up Python & R environments; use of conda based environments; managing workflows; and use of containerized solutions via Singularity. The session covers general principles, with hands-on activities on SDSC resources.

Open OnDemand, an intuitive, innovative, and interactive interface to remote computing resources, is now available on Ookami. Open OnDemand helps computational researchers and students efficiently utilize remote computing resources by making them easy to access from any device. In this webinar we will show you how to use Open OnDemand on Ookami.

Hosted by the community, tips and tricks webinars share best practices of all things Open OnDemand. They take place on the first Thursday of every month at 1 p.m. ET.  

Recordings of previous events are available.

More information and Zoom coordinates are available on the Open OnDemand Discourse forum.

This short course (2.5 hours) will allow users to work through a hands-on tutorial covering how to run AlphaFold utilizing NVIDIA GPUs on the ACES cluster, a composable accelerator testbed at Texas A&M High Performance Research Computing.

Read more at https://hprc.tamu.edu/training/aces_alphafold.html 

This short course (2.5 hours) introduces researchers to Graphcore Intelligence Processing Units (IPUs) on the ACES cluster, a composable accelerator testbed at Texas A&M High Performance Research Computing. The instructor will demonstrate the execution of models from different frameworks on the IPU system, and participants will gain practical experience in converting TensorFlow and PyTorch code into IPU code through hands-on exercises.

Software Installation 101 is for anyone looking to learn the fundamentals of software installation on Linux/Unix-based high-performance computing systems. Prior experience with the command line and cluster computing will be helpful. Topics covered will include the following:

• Foundations
• Unpacking
• Compiling from Source
• Compiling from Source with Dependencies
• QA

During office hours you can ask questions about running workflows or bags of tasks on ACCESS resources. These sessions are an excellent opportunity for both new and existing users to learn and engage. You can expect:

Whether you are interested in Ookami and consider getting an account, a new user, or a longtime user, who wants to optimize their usage, this webinar is for you! It will cover the basics of the system, how to get an account, and for existing users also a lot of tips and tricks on how to use it efficiently for your research.

Ookami has available cycles (CPU only) and is welcoming new users.

Modern deep learning challenges leverage increasingly larger datasets and more complex models. As a result, significant computational power is required to train models effectively and efficiently. Learning to distribute data across multiple GPUs during deep learning model training makes possible an incredible wealth of new applications utilizing deep learning.

This is a practical introductory workshop for using the Classiq platform to model quantum algorithms using a high-level modeling language, optimizing quantum circuits using a hardware-aware approach and smart synthesis, and running your optimized quantum circuits on various real quantum hardware and simulators. No previous quantum computing knowledge is required, and we encourage participation from everyone interested in learning more about quantum computing. After the workshop, attendees will be able to use the 

Large language models (LLMs) and deep neural networks (DNNs), whether applied to natural language processing (e.g., GPT-3), computer vision (e.g., huge Vision Transformers), or speech AI (e.g., Wave2Vec 2), have certain properties that set them apart from their smaller counterparts. As LLMs and DNNs become larger and are trained on progressively larger datasets, they can adapt to new tasks with just a handful of training examples, accelerating the route toward general artificial intelligence.

This course is an introduction to the R programming language and covers the fundamental concepts needed to operate in the R environment with a particular focus on data science. This course assumes no prior experience with R.

Includes a 1-hour lunch break.

More information about this Short Course at https://hprc.tamu.edu/training/aces_intro_r.html
 

During office hours you can ask questions about running workflows or bags of tasks on ACCESS resources. These sessions are an excellent opportunity for both new and existing users to learn and engage. You can expect:

Applications for natural language processing (NLP) and generative AI have exploded in the past decade. With the proliferation of applications like chatbots and intelligent virtual assistants, organizations are infusing their businesses with more interactive human-machine experiences. Understanding how transformer-based large language models (LLMs) can be used to manipulate, analyze, and generate text-based data is essential.