Call for Participation

Northeastern University and Boston University, together with NVIDIA, are hosting a “GPUs Accelerating Research” Week. As part of this week, Northeastern is hosting a day long workshop on 4/24 focused on how graphics processors are accelerating new and interesting areas of research in novel ways. The goal of this meeting is to provide a venue for both industry and academia to come together to discuss these innovations, and explore what lies ahead in GPU acceleration. The following 4/25, Boston University is hosting a full day developer's workshop targeting CUDA and OpenACC development. More details about it can be found here.

4/24 at Northeastern University

Location: 140 The Fenway Building, 3rd floor. MAP
Register page: Register 4/24 workshop

4/25 at Boston University

Location: Whitaker Computational Simulation Facility, 24 Cummington Mall, Basement Room B03/B04. MAP

Conference Program

Keynote: GPUs Current and Future role in Accelerated Research Computing
Kimberly Powell, NVIDIA

Abstract: Although parallel computing has been considered mainstream for decades, we are still just beginning to teach and employ parallel programming skills. Early indicators from the ACM, NSF and Massive Online Courses point to rapid changes coming in 2013 and beyond. A brief history of how NVIDIA has taken early indicators from the research and academic community to fuel our commitment and investment into industry and how we will continue in today's parallel world.

About the speaker: Kimberly Powell, Higher Education & Healthcare Segment Manager with the primary role of evangelizing GPU computing. Kimberly's passion is healthcare research, connecting researchers, institutions and industry to accelerate science to treatment. Prior to NVIDIA, Kimberly was Product Manager of diagnostic imaging systems and a Hardware Engineer doing FPGA design. A graduate of Northeastern University, Kimberly holds a Bachelor of Science in Electrical Engineering with a concentration in Computer Engineering.

Download full Program HERE

Education Workshop

Teaching Parallel Computing with GPUs
Mark Ebersole, NVIDIA
3:45 - 5:45 PM

Abstract: The rapid expansion of parallel computing, from smart phones to super computers, means we must improve and expand our current pedagogy in science and engineering. Unfortunately, most university students only have access to at most, an elective parallel programming class. Those students and professors who are proficient at parallel computing on hybrid systems have almost all been self-taught. This is not a sustainable solution. In this session, we will cover the need for a robust, pervasive parallel programming curriculum, as well as recommendations for teaching parallel programming algorithms and concepts. We'll also look at how CUDA is quickly becoming the go-to platform at over 600 universities worldwide, and why we feel it's the best tool available to teach massively parallel programming. You'll hear about experiences of those teaching CUDA across a wide spectrum of audiences. Learn what methods and materials work best and how to begin incorporating parallel programming in your curriculum.

Audience: This talk is targeted at anyone in education who is involved with teaching programming or dealing with high-performance computing. Especially those who teach Computer Science and Engineering and want to make sure their students are prepared for the parallel future.

About the speaker: As CUDA Educator at NVIDIA, Mark Ebersole teaches developers the benefits of GPU computing using the NVIDIA CUDA parallel computing platform and programming model, and the benefits of GPU computing. With more than ten years of experience as a systems programmer, Mark has spent much of his time at NVIDIA as a GPU systems diagnostics programmer in which he developed a tool to test, debug, validate, and verify GPUs from pre-emulation through bringup and into production. Before joining NVIDIA, he worked at IBM developing Linux drivers for the IBM iSeries server. Mark holds a BS degree in math and computer science from St. Cloud State University.


Contact David Kaeli at or Jon Saposhnik at for more information regarding this event.