posted on May 6, 2014
The Virtual School of Computational Science and Engineering (VSCSE) is hosting two courses this summer. These courses are open to graduate students, post-docs, and young professionals who want to expand their skills with advanced computational resources. The courses are offered at institutions around the country, allowing participants to go to the most convenient location.
Descriptions of the courses are shown below. You can register at the XSEDE portal. Questions can be mailed to sent to the VSCSE organizing team at meags@umich.edu.
Summer 2014 VSCSE Courses
Harness the Power of GPUs: Introduction to GPGPU Programming (June 16 - 20, 2014)
From the VSCSE website: GPGPU Programming is a mixture of lectures and labs and introduces all levels of parallelism as well as common approaches for parallelization in order to achieve the following goals: Better utilization of the GPUs by enabling more scientists to use them, better understanding of the efficiency in the GPU utilization by the application developers and a higher job throughput by enabling more resources and shortening job runtimes. In addition, participants will understand and avoid the common pitfalls of parallel computing, learn CUDA and OpenACC, understand the basic principles of data parallel computing, tap into enormous computing power, even on a laptop, and speed up research.
Data Intensive Summer School (June 30 - July 2, 2014)
From the VSCSE website: The Data Intensive Summer School focuses on the skills needed to manage, process and gain insight from large amounts of data. It is targeted at researchers from the physical, biological, economic and social sciences that are beginning to drown in data. We will cover the nuts and bolts of data intensive computing, common tools and software, predictive analytics algorithms, data management and non-relational database models. Given the short duration of the summer school, the emphasis will be on providing a solid foundation that the attendees can use as a starting point for advanced topics of particular relevance to their work.