Today, we added four outstanding research and academic leaders to the CUDA Fellows Program, which recognizes individuals committed to championing the adoption and use of the CUDA architecture and GPU computing.
The new Fellows are:
- Lorena Barba, Boston University
- Manuel Ujaldón, University of Malaga
- Scott Le Grand, Amazon.com Inc.
- Takayuki Aoki, Tokyo Tech
These new CUDA Fellows work in fields that include multicore architectures, biomedical image processing, cloud computing, quantum chemistry and fluid dynamics. Each receives the latest NVIDIA Tesla GPUs, a travel stipend, support from NVIDIA technical staff and priority access to NVIDIA GPU hardware and software.
“Each of these individuals has demonstrated a passion and commitment to using CUDA and the power of GPU computing to help solve some of the worlds’ most challenging computational problems,” said Bill Dally, chief scientist at NVIDIA. “We look forward to working with them to continue spreading the word about the industry-changing impact GPU computing offers to developers, researchers and academics worldwide.”
The CUDA Fellows Program was established to recognize, reward and assist researchers who use the CUDA architecture within their disciplines or geographies. CUDA Fellows have demonstrated the benefits of GPU computing to advance their fields of research and have been instrumental in introducing GPU computing to their peers.
The new CUDA Fellows were selected by NVIDIA’s research team and join an exclusive group of current CUDA Fellows: Mike Giles of Oxford University, P.J. Narayanan of IIIT-Hyderabad, Dan Negrut of University of Wisconsin, John Stone of UIUC, and Ross Walker of SD Supercomputing Center.
Here’s a bit of background information on our newest CUDA Fellows:
Lorena Barba, Boston University
Lorena is an assistant professor of mechanical engineering at Boston University. From 2004 to 2008, she was a lecturer in applied mathematics at the University of Bristol, England. She received her Ph.D. in aeronautics from the California Institute of Technology in 2004 and undergraduate degrees (BSc and PEng) in mechanical engineering from Universidad Técnica Federico Santa María in Valparaíso, Chile.
Lorena is a faculty fellow of the Boston University Rafik Hariri Institute for Computing and Computational Science & Engineering and a visiting research professor at the Scientific and Technological Center of Valparaíso (Centro Científico-Tecnológico de Valparaíso) in Chile.
Lorena first got involved with GPU computing in 2007 and has been an advocate of using GPUs in scientifically developing countries in need of high-performance computing. GPU computing presents an opportunity to leverage supercomputers at institutions that may lack larger infrastructures. She personally drove the adoption of GPUs at Universidad Técnica Federico Santa María, which became Chile’s first CUDA Teaching Center in 2011.
Manuel Ujaldón, University of Malaga
Manuel is an associate professor in the Computer Architecture Department at the University of Malaga, Spain, and conjoint senior lecturer in the School of Electrical Engineering and Computer Science at the University of Newcastle, Australia.
He worked on parallelizing compilers, finishing his Ph.D. thesis in 1996 by developing a data-parallel compiler for sparse matrix and irregular applications. During this time, he was part of the HPF and MPI Forums, working as post-doc in the Computer Science Department at the University of Maryland, College Park.
Manuel joined the GPGPU movement in early 2003 using Cg and wrote the first book in Spanish about programming GPUs for general purpose computing. The book described how to map irregular applications and linear algebra algorithms on GPUs.
Manuel adopted CUDA when it was first released in 2006, focusing on image processing and biomedical applications. Over the past five years, he has authored more than 40 papers in journals and international conferences in these two areas. He has taught more than 30 courses on CUDA programming worldwide, including academic programs in European, North American and Australian universities. He has also been honored with NVIDIA Academic Partnership awards from 2008 to 2011, NVIDIA Teaching Center awards from 2011 to 2013 and an NVIDIA Research Center award in 2012.
Scott Le Grand, Amazon
Scott is a principal engineer at Amazon Web Services, where he is developing life science services on Amazon’s Elastic Compute Cloud (EC2).
He developed Genesis as the first molecular modeling system for home computers in 1987, the distributed computing protein folding project Folderol in 2000 and the networkable 3D space shooter BattleSphere for the Atari Jaguar later that year.
More recently, he ported the Folding@Home codebase to CUDA, achieving a 5x speedup over previous efforts and is responsible for approximately 2.6 petaFLOPs of the project’s computational firepower. He is best known for his work porting the AMBER molecular dynamics package to CUDA, achieving record-breaking performance in the process.
He earned a B.S. in biology from Siena College and a Ph.D. in biochemistry from Pennsylvania State University.
Takayuki Aoki, Tokyo Tech
Takayuki is a professor at the Tokyo Institute of Technology and deputy director of the Global Scientific Information and Computing Center. He has been awarded the Computational Mechanics Achievement Award from Japan Society of Mechanical Engineers (JSME), the Achievement Award from the Japan Society for Industrial and Applied Mathematics (JSIAM) and many other awards and honors in visualization.
Takayuki authored the first book in Japanese on CUDA programming and applications. His research covers numerical schemes for computational fluid dynamics, numerical weather prediction, multiphase flow simulation and large-scale high performance computing applications. He was also awarded the Gordon Bell Prize Special Achievements in Scalability and Time-to-Solution in 2011.
Tagged: CUDA, cuda fellow, GPGPU, gpu computing, parallel computing, Supercomputing, Tesla
