Containers provide a lightweight, portable way to package and run applications consistently across different computing environments. In HPC and research workflows, they simplify software deployment and ensure reproducibility.
Remote event
Applications closed - The San Diego Supercomputer Center (SDSC) Cyberinfrastructure-Enabled Machine Learning (CIML) is focused on teaching researchers and students the best practices for effectively running artificial intelligence (AI), machine learning (ML), and deep learning (DL) applications on advanced cyberinfrastructure (CI) and high-performance computing (HPC) systems. The National Artificial Intelligence Research Resource (NAIRR) pilot is an NSF-led initiative designed to democratize access to AI research by providing U.S. researchers and educators with crucial infrastructure, including computational power, datasets, and training tools.
San Diego Supercomputer Center
Linux command line interface (CLI) skills are essential for advanced cyberinfrastructure (CI). This session covers filesystem hierarchy, permissions, links, wildcards, finding files, environment variables, modules, config files, aliases, history & Bash scripting tips.
Remote event
Applications closed - The SDSC Summer Institute is a week-long workshop hosted annually by the San Diego Supercomputer Center (SDSC) at UC San Diego, focusing on introductory-to-intermediate topics in High Performance Computing (HPC), Data Science, and Artificial Intelligence (AI). Designed for researchers and educators in academia and industry, the program equips participants to solve scientific challenges exceeding local computing capabilities.
San Diego Supercomputer Center
High-performance computing (HPC) systems rely on batch job schedulers like Slurm to efficiently and fairly manage shared computing resources through scripted job submissions. Here, we introduce new users to distributed batch job schedulers, guiding them through writing and submitting their first Slurm job scripts while covering best practices, resource requests, and useful environment variables.
Remote event
Registration and Abstract Submission for Fast ML for Science Conference 2026 Now Open - As experimental methods continue to evolve, generating increasingly complex and high-resolution datasets, machine learning (ML) is becoming an essential tool across numerous scientific disciplines. This conference will explore emerging ML methods and their applications in scientific discovery, focusing on processing technologies and strategies to accelerate deep learning and inference.
UC San Diego
An overview of commonly used Linux tools for searching and manipulating text. We progress from the simplest tools, such as head, tail, cut, paste, to more complex tools grep, awk and sed.
Remote event
Efficiently transferring data is a critical part of building research workflows, whether working with experimental or simulated data on local or high-performance computing (HPC) systems. Here, we introduce key concepts and command-line tools for data transfer, including how to verify data integrity, use compression, and select appropriate transfer methods based on data size, location, and organization.
Remote event
Interactive high-performance computing (HPC) involves real-time user inputs that result in actions being performed on HPC compute nodes. This session presents an overview of interactive computing tools and methods.
Remote event
Shell scripting improves productivity and reduces errors in HPC workflows by automating tasks like data processing, backups, and system monitoring. This session builds on basic Linux command-line skills to teach Bash scripting syntax, constructs, and best practices for effective automation.
Remote event
Essentials of using regular expressions (regexes) with the Linux tools grep, awk and sed. Topics include quantifiers, wildcards, grouping, alternation, word boundaries, lazy and greedy matching and regex flavors. Attendees should at least be familiar with grep.
Remote event
Many research problems on high-performance computing (HPC) systems benefit more from high-throughput computing (HTC) or many-task computing (MTC) models, which focus on completing numerous smaller tasks over time rather than using large, parallel applications. Here, we introduce how to build such structured workflows using the Slurm Workload Manager, including job arrays, dependencies, and job bundling strategies, while addressing common challenges in managing HTC/MTC workloads.
Remote event