High Performance Computing

HPC@LSU will hold the 2025 LONI Scientific Computing Bootcamp on June 2-4, June 9-11 in a hybrid (In-Person + Zoom) form.

Scientific computing is becoming more ubiquitous for all types of research areas. Skills and knowledge that are necessary to take full advantage of the power of computing, however, are often inadequately present in both curricular and extracurricular training. The purpose of this workshop is, by both presentation and hands-on experiences, to help attendants understand the usage of popular scientific computing programming tools and prepare for their future computational study and research career.

In four days, the attendants will learn:

• Introduction to Python programming language with its applications in scientific computing.
  • Day 1, participants will delve into Python's syntax, data structures, control flow mechanisms, and functions through a series of hands-on exercises and pragmatic demonstrations.
  • Day 2, building upon the foundation of Python basics, the second day will focus on NumPy, a powerful library for numerical computing, diving into advanced topics such as array manipulation, mathematical operations, and data analysis techniques using NumPy. Through hands-on activities and demonstrations, participants will learn how to leverage NumPy effectively for scientific computing and data analysis tasks in Python.
  • Day 3, Getting Started with MATLAB: From Python to AI Integration
    MATLAB provides a flexible, two-way integration with many programming languages, including Python. This allows different teams to work together and use MATLAB algorithms within production software and IT systems. If you have functions and objects in Python, you can call them directly from MATLAB. This allows you to work entirely within MATLAB without switching your programming environment. In this workshop we will discuss the different ways you can incorporate Python into MATLAB. We will look at several examples and incorporate the SunPy Python package for solar data analysis. This will be a fun and interactive workshop, so don’t forget to bring your laptop!
    Deep learning is quickly becoming embedded in everyday applications. It’s becoming essential for students and educators to adopt this technology to solve complex real-world problems. MATLAB and Simulink provide a flexible and powerful platform to develop and automate data analysis, deep learning, AI, and simulation workflows in a wide range of domains and industries. In this workshop we will introduce deep learning with MATLAB. We will utilize a previously trained network and modify it, using the MATLAB Deep Network Designer. The Deep Network Designer allows you to interactively build, visualize, and train neural networks. Individuals can generate the code for the neural network and finetune parameters. Users can use popular pre-trained networks or construct their own. We will also look at the MATLAB Classification Learner to run several models on a single data set. These visual approaches create a more efficient workflow.
    Speaker's Bio:
    Jon Loftin is a Senio Customer Success Engineer at MathWorks Jon’s background is in mathematics. More specifically, implementing mathematics in a computer. He holds degrees in mathematics: a BS from Southern Arkansas University, a MS from the University of Arkansas, and a Ph.D. from Texas Tech University. He has had years of teaching experience, from teaching at the Naval Nuclear Power School to teaching as an Assistant Professor. Jon’s research focus is building efficient integration techniques in finite element methods.
• Introduction to Deep Learning
  • Day 4 of our workshop immerses participants in the theoretical underpinnings and background of this transformative field. Through engaging lectures and exercises, attendees will explore the core concepts, architectures, and methodologies that underlie deep learning techniques, providing a solid foundation for further exploration. Topics covered include neural networks, activation functions, optimization algorithms, and common deep learning architectures.
  • Day 5, participants will delve into practical application with an Instructor-Led NVIDIA DLI (Deep Learning Institute) Workshop: Fundamentals of Deep Learning. Guided by experienced instructors, attendees will engage in hands-on exercises and projects designed to reinforce key concepts learned on Day 1. Upon successful completion of the workshop and assessment, participants will be awarded an NVIDIA DLI certificate, recognizing their mastery of deep learning fundamentals and bolstering their professional credentials for career advancement in this dynamic field.
  • Day 6, participants will engage in an instructor-led NVIDIA DLI workshop focused on Large Language Models (LLMs). This technical, beginner-level course will guide learners through building a variety of LLM-based applications using modern prompt engineering techniques. Working with an NVIDIA language model NIM (powered by Llama-3.1) and the LangChain library, attendees will develop a foundational skill set for tasks such as text generation, large-scale document analysis, and chatbot development. Participants will complete skills-based coding projects and, upon successful completion, will receive an NVIDIA DLI certificate.