In this workshop, we will use Python to introduce parallel processing and cover a selection of Python modules, including multithreading, Dask, and mpi4py, that enable better utilization of multi-core processors and the YCRC HPC environments.
This workshop is intended to give C and Fortran programmers a hands-on introduction to OpenMP programming. Attendees will leave with a working knowledge of how to write scalable codes using OpenMP.
This two-day workshop will focus on the parallel constructs in MATLAB, their capabilities, and some of the common hurdles that you’ll encounter when using them. You’ll also learn how to run your MATLAB code on local HPC resources.
This two-day workshop will focus on the parallel constructs in MATLAB, their capabilities, and some of the common hurdles that you’ll encounter when using them. You’ll also learn how to run your MATLAB code on local HPC resources.
This workshop will introduce scalable data analytics and machine learning. It is a two-day, hands-on workshop using Hadoop, Spark and TensorFlow.
This workshop will introduce scalable data analytics and machine learning. It is a two-day, hands-on workshop using Hadoop, Spark and TensorFlow.
This workshop follows our “Intro to HPC” workshop, expanding on parallelism and efficiency considerations. The workshop will review compute cluster architecture and proper job allocation. It will also cover a number of ways to make use of parallelism to improve performance of programs running on the cluster including:
- SimpleQueue
- High level parallelism in languages like R and Python
- Multi-threaded C programs
- MPI
Monitoring your jobs to understand their resource requirements and to make sure they are running efficiently, will also be covered.