Graduate students, post-docs and professionals from academia, government and industry are invited to enroll in two summer school courses offered by the Virtual School of Computational Science and Engineering and presented at the University of Tennessee Knoxville and other sites across the country during July and August.
The course titles and dates are as follows:
- Data-intensive Summer School on July 8 through 10
- Proven Algorithmic Techniques for Many-core Processors Summer School on July 29 through Aug. 2
These Virtual School courses will be delivered to sites nationwide using high-definition videoconferencing technologies. The location for the courses at UT Knoxville will be the virtual classrooms on the lower level of the Communications and University Extension building. Times will be announced (eight hours of instruction will be provided each day).
Data-intensive Summer School
The Data-intensive Summer School focuses on the skills needed to manage, process and gain insight from large amounts of data. It targets researchers from the physical, biological, economic and social sciences who need to deal with large collections of data. The course will cover the nuts and bolts of data-intensive computing, common tools and software, predictive analytics algorithms, data management and non-relational database models.
In addition to UT Knoxville, other participating sites for the Data-intensive Summer School are Louisiana State University, Marshall University, Michigan State University, Northwestern University and the University of Chicago, Princeton University, Purdue University, University of California Los Angeles, University of California San Diego, University of Delaware, the National Center for Supercomputing Applications at the University of Illinois at Urbana–Champaign, University of Oklahoma, University of Texas at Brownsville, University of Texas at El Paso and University of Wisconsin Milwaukee.
More information about the Data-intensive Summer School, including pre-requisites and course topics, can be found here.
Proven Algorithmic Techniques for Many-core Processors Summer School
The Proven Algorithmic Techniques for Many-core Processors Summer School will present students with the seven most common and crucial algorithm and data-optimization techniques to support successful use of GPUs for scientific computing.
Studying many current GPU computing applications, the course instructors have learned that the limits of an application’s scalability are often related to some combination of memory bandwidth saturation, memory contention, imbalanced data distribution or data-structure/algorithm interactions.
Successful GPU application developers often adjust their data structure and problem formulation specifically for massive threading and execute their threads leveraging shared on-chip memory resources for bigger impact.
The techniques presented in the course can improve performance of applicable kernels by 2 to 10X in current processors while enhancing future scalability.
In addition to UT Knoxville, other participating sites for the Proven Algorithmic Techniques for Many-core Processors summer school are Clemson University, Louisiana State University, Marshall University, Michigan State University, Princeton University, Purdue University, University of California Los Angeles, University of Delaware, the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign, University of Texas at Brownsville, University of Texas at El Paso and University of Utah.
Registration fees for each course are $100, with some sites waiving the fees. Registration for the courses at UT Knoxville is free; however, attendees must register two weeks in advance of each summer school.
Registration is accomplished by visiting the user portal for the Extreme Science and Engineering Discovery Environment (XSEDE). First-time users of the XSEDE portal must follow the guidelines to create a free portal account before being able to sign up for the Virtual School courses. Upon creating an XSEDE portal account, users can sign up for Virtual School courses through the XSEDE course calendar.