About the GPU Research Center at University of Torino
The GPU Research Center at University of Torino (UniTo) was established to support a variety of research activities employing the CUDA technology. In particular, two key research thrusts are: 1) the abstraction of GPGPU programming features and their integration into the FastFlow pattern-based/lock-free parallel programming library. 2) The evaluation of the expressiveness and of the effectiveness of parallel pattern-based languages for the porting of MonteCarlo simulations for high-energy physics onto GPGPU, and high-frequency streaming applications (e.g. signal processing, video filtering, high frequency trading). Aldinucci believes that, developers of GPU-enabled application may benefit from a further abstraction of the state-of-the-art GPU programming tools, such as CUDA, and advocates parallel patterns, e.g. farm, pipeline, map, reduce, mapreduce, as vehicles able to bridge this abstraction gap. These patterns are not currently available as first-class abstractions neither in CUDA nor in OpenCL, and have the potentiality to improve the portability of parallel code onto GPGPU and its performance portability.
About the PI
Marco Aldinucci is an assistant professor in the Department of Computer Science of the University of Torino since 2008, where he leads the parallel computing research group. Previously, he has been researcher at University of Pisa and at Italian National Research Agency. He is the author of over a hundred papers in international journals and conference proceeding. He has been participating in over 20 national and international research projects concerning parallel and autonomic computing. He is the recipient of the HPC Advisory Council University Award 2011. He has serving as work-package leader in the EU-STREP FP7 ParaPhrase project and in the IMPACT project, and he is the contact person for University of Torino in the European Network of Excellence HiPEAC. He is the co-designer of the FastFlow parallel programming framework and several other libraries for parallel computing. His research is focused on programming models for parallel and distributed computing, lock-free algorithms, and high-performance applications.