Matlab Distributed Computing Seminar at PSC
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9:00 a.m. – 12:00 p.m.
Dr. Jiro Doke, Senior MathWorks Application Engineer
Dr. Anirban Jana, Senior Scientific Specialist, Pittsburgh Supercomputing Center
Part I: Parallel Computing with MATLAB
In this session, you will learn how to solve computationally and data-intensive problems using multicore processors, GPUs, and computer clusters. We will introduce you to high-level programming constructs that allow you to parallelize MATLAB applications without CUDA or MPI programming and run them on multiple processors.
We will also show you how to overcome the memory limits of your desktop computer and solve problems that require manipulating very large matrices by distributing your data.
Toolboxes with built-in support for parallel computing
Creating parallel applications to speed up independent tasks
Programming with distributed arrays to work with large data sets
Scaling up to computer clusters, grid environments, or clouds
Tips on developing parallel algorithms
Part II: Running MATLAB jobs on PSC’s Blacklight supercomputer
In this session, you will learn how to use the MATLAB Distributed Computing Server (MDCS) on PSC’s “Blacklight” cluster, an SGI UV 1000 cc-NUMA shared-memory system comprised of 256 blades, each of which has 16 cores and 128 GB of memory.
Scaling from the desktop to MDCS on Blacklight
Configuring your machine to use MDCS on Blacklight
How to submit and retrieve jobs to MDCS on Blacklight
In person (PSC)
11/27/2012 09:00 - 11/27/2012 12:00 EST (SESSION HAS ENDED)View Session Details →
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