Entries filed under “HPC Education and Training”

In this video, Professor Wen-Mei Hwu from the University of Illinois at Urbana‐Champaign presents Computer Engineering and the Parallel Computing Revolution.

Modern computers are already heterogeneous parallel systems and will be more so in the near future. The computer of 2016 will have many CPU cores, many GPU cores and many accelerators. While parallel application developers are already reporting 5‐70X speedup over optimized sequential code, this speedup could scale up to over 1,000X by 2016 if we make some important changes in how we do things.

Recorded at the June 1, 2011 at the first annual Technion Computer Engineering (TCE) Conference in Haifa, Israel.

The Swiss National Supercomputer Center (CSCS) will host a three day summer school on parallel programming aimed at graduate students who are new to the world of HPC August 17-19, 2011 in Manno.

The school will cover topics such as the principles of parallel programming, distributed memory programming with MPI, shared memory programming using OpenMP, hybrid programming with MPI/OpenMP and performance tools for parallel applications, as well as some advanced topics. The purpose of the summer school is to teach programming skills and therefore a large proportion of the course will be dedicated to practical exercises.

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TACC’s Victor Eijkhout, Edmond Chow, and Robert van de Geij have posted an excellent eBook entitled: Introduction to High-Performance Scientific Computing. While currently in a Public Draft form that is open for comments, the book features topics such as Sequential and Parallel Computer Architecture, Programming strategies for high performance, Numerical treatment of differential equations, High performance linear algebra, Monte Carlo Methods, and much more.

The field of high performance scientific computing lies at the crossroads of a number of disciplines and skill sets, and correspondingly, for someone to be successful at using high performance computing in science requires at least elementary knowledge of and skills in all these areas. Computations stem from an application context, so some acquaintance with physics and engineering sciences is desirable. Then, problems in these application areas are typically translated into linear algebraic, and sometimes combinatorial, problems, so a computational scientist needs knowledge of several aspects of numerical analysis, linear algebra, and discrete mathematics. An efficient implementation of the practical formulations of the application problems requires some understanding of computer architecture, both on the CPU level and on the level of parallel computing. Finally, in addition to mastering all these sciences, a computational sciences needs some specific skills of software management.

While good texts exist on applied physics, numerical linear algebra, computer architecture, parallel computing, performance optimization, no book brings together these strands in a unified manner. The need for a book such as the present was especially apparent at the Texas Advanced Computing Center: users of the facilities there often turn out to miss crucial parts of the background that would make them efficient computational scientists. This book, then, comprises those topics that seem indispensible for scientists engaging in large-scale computations.

In this interview from the Education Technology & Change blog, Henry Neeman from the University of Oklahoma describes the increasing accessibility of HPC.

“You may not see the supercomputers, but every single day supercomputing is making our lives better. Everything from the cars we drive to the weather forecast on TV to the movies we watch to the detergent bottles in our laundry rooms are made, or made better, by supercomputing. Today, there are a number of ways for citizens to access supercomputing. Often, these are known as “science gateways,” and they provide a simple interface to a complicated back end. An example is nanoHUB, which K-12 and postsecondary students can use to do nanotechnology simulations. In fact, the nanoHUB website has curricula and teaching materials that any teacher can put to work in their classroom.”

The Microsoft TechNet WIKI has posted a Do It Yourself guide to building an HPC cluster that consists of three or more nodes.

“This guide describes how to build a small Windows HPC cluster that you can use to run your parallel software applications, cluster-enabled Microsoft Excel workbooks, or service-oriented architecture (SOA) based applications. This guide is intended for those of you out there who do not have an IT department to set up a cluster for you, and so you need to do it yourself. After you complete the steps in this guide, you will have a cluster that is ready for you to install applications and start running jobs. Many parallel computing software applications provide documentation about how to install their software on a Windows HPC cluster.”