IDRE

Institute for Digital Research and Education

Institute for Digital Research and Education

HPC

Code Profilers: Measuring Performance and Resource Usage

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Learn to use code profilers (software) to analyze a program’s performance and resource usage, and to use the measurement data to guide tuning methodologies and workflows, in the context of scientific computing. Any questions about this workshop can be emailed to Shao-Ching Huang at sch@ucla.edu.  Presented by the Office of Advanced Research Computing (OARC). Register here:…
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Parallel Parallel Computing 4: Solving Partial Differential Equations on Parallel Computers

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MPI (Message Passing Interface) is a standardized interface for writing portable distributed-memory parallel scientific code. The portability of MPI ensures the same MPI program works the same way on different platforms, ranging from laptop computers to massively parallel supercomputers. MPI has been widely used in advanced simulations, data analysis and visualization in the last three…
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Parallel Parallel Computing 3: Introduction to PETSc

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MPI (Message Passing Interface) is a standardized interface for writing portable distributed-memory parallel scientific code. The portability of MPI ensures the same MPI program works the same way on different platforms, ranging from laptop computers to massively parallel supercomputers. MPI has been widely used in advanced simulations, data analysis and visualization in the last three…
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Parallel Parallel Computing 1: Running MPI programs

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MPI (Message Passing Interface) is a standardized interface for writing portable distributed-memory parallel scientific code. The portability of MPI ensures the same MPI program works the same way on different platforms, ranging from laptop computers to massively parallel supercomputers. MPI has been widely used in advanced simulations, data analysis and visualization in the last three…
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Big Data on HPC

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This workshop will go over using Big Data techniques on HPC resources. Big Data methods are used when data size because so large, it becomes challenging to compute. Also, when machine learning models become so complex, it can also be challenging to train. In this workshop, we will go over examples of solving Big Data…
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Hoffman2 Happy Hour: RStudio on Hoffman2

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The Hoffman2 Happy Hours Series: Using Rstudio on Hoffman2 is best with a Rstudio Server app. This Happy Hour shows an example of using a Rstudio Server with Singularity/Apptainer. Any questions about this workshop can be emailed to Charles Peterson at cpeterson@oarc.ucla.edu.  Presented by the Office of Advanced Research Computing (OARC). Register here: https://ucla.zoom.us/meeting/register/tJMqfu6vpjsrGNJrFbMEK_wiVH2gZy_Fztse

Hoffman2 Happy Hour: Anaconda on Hoffman2

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Anaconda (https://www.anaconda.com/) is a distribution of R and Python that can be used to easily install many popular data science, biostats, and other packages. This Hoffman2 Happy Hour will go discus using Anaconda on Hoffman2. This can be applied to using Anaconda on various other HPC resources. We will go over creating conda environments and…
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Building Containers for HPC

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This workshop is a follow-up to a previous workshop on “Using Containers on HPC Resources” (https://github.com/ucla/hpc_workshops). This workshop will focus on creating containers to be ran on HPC resources. We will go over building containers using Docker/podman and Apptainer/Singularity. We will also use Hoffman2 to run our newly built containers. To follow along, users will…
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