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Training classes and workshops introduce new and current users to the high-performance computing, data, and visualization resources available at SDSC and provide the programming skills necessary to use SDSC resources effectively and efficiently. Workshops offer experienced users more in-depth instruction, including hands-on assistance with their own codes and collaborative discussions with other users and parallel computing experts.
A brief introduction to fundamental concepts in parallel computing. No programming experience needed.
This event will be held remotely.
This webinar is an introduction to performing machine learning at scale. An overview of approaches for parallelizing R code on HPC will be provided. We will also cover the essentials of Spark and demonstrate how to use Spark for large-scale data analytics and machine learning. Demonstrations will allow participants to gain practical guidance for building and scaling machine learning workflows.
This event will be held remotely.
A survey of intermediate Linux skills for effectively using advanced cyberinfrastructure.
This event will be held remotely.
A brief introduction to the Linux scheduler, how to interact with it, and run your research workloads on your personal computer, a shared workstation, or even a high-performance computing system.
This event will be held remotely.
This webinar is a condensed version of the Performance Tuning session, targeting code developers who want to speed up their calculations. It will cover various optimization techniques, including cache usage, loop optimization, and compiler optimization, with exercises primarily in C but applicable to any language.
This event will be held remotely.
An overview of commonly used Linux tools for searching and manipulating text.
This event will be held remotely.
How to get the data you need for your research to and from high-performance computing systems.
This event will be held remotely.
The talk will highlight the advances in the TAU Performance System(R). The TAU Performance System [http://tau.uoregon.edu] is a versatile performance evaluation toolkit supporting both profiling and tracing modes of measurement. It supports runtime systems such as CUDA (for NVIDIA GPUs), Level Zero (for Intel oneAPI DPC++/SYCL), ROCm (for AMD GPUs), OpenMP with support for OMPT and Target Offload directives, Kokkos, and MPI allow instrumentation at the runtime system layer while using sampling to evaluate statement-level performance data without recompiling or modifying the application binary. It will describe the different instrumentation, measurement and analysis options that are available and how TAU is integrated in the Extreme-scale Scientific Software Stack (E4S). E4S is a curated, Spack based software distribution of 100+ HPC and AI/ML packages. A hands-on demo on AWS with the Extreme-scale Scientific Software Stack (E4S) [https://e4s.io] will be shown.
This event will be held remotely.
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.
This event will be held remotely.
Voyager offers a unique architecture to optimize and scale deep learning applications. In this tutorial we will introduce Voyager and its Gaudi architecture. Then we will take a Pytorch application and port it to the Voyager system. Finally, how to run any Huggingface models to Voyager will be also discussed.
This event will be held remotely.
Online training classes and workshops are recorded to enable the skills development necessary to use SDSC resources. The following list of previously recorded events offers users an opportunity to train at their own pace and schedule.