Update: Due to a high demand for this activity only selected participants will be contacted
Dates: 27th-29th of january 2016, 9:30-16:00 hrs.
Place: Pontificia Universidad Católica de Chile, Linux Room (ex Carlos Rivera Cruchaga)Departamento de Ciencias de la Computación- Universidad de Chile
After a very successful decade being used as hardware accelerators, the GPUs constitute today an attractive alternative for low cost high performance computing. In this context CUDA is a parallel calculation architecture of NVIDIA that makes the most out of the GPU potential to provide an extraordinary increment of the system’s performance.
Programming GPUs with CUDA
The NLHPC and Pontificia Universidad Católica de Chile invite students and researchers with basic C and parallelism knowledge that would like to initiate themselves in GPGPU programming to this workshop, which will be given by Manuel Ujaldón, Nvidia CUDA Fellow.
Programación de GPUs con CUDA (PDF)
Program
27th january
09:30 – 11:00 GPU Architecture and many-core designs.
11:00 – 11:30 Break.
11:30 – 13:00 CUDA Programing: Threads, blocks, nodes, nets.
13:00 – 14:30 Lunch time.
14:30 – 16:00 CUDA Tools: Compiler, occupation calculator, …
28th january
09:30 – 11:00 CUDA Examples: VectorAdd, Stencils, ReverseArray, Matrix Multiply.
11:00 – 11:30 Break.
11:30 – 13:00 Kepler and Maxwell: Hyper-Q, dynamic parallelism, unified memory.
13:00 – 14:30 Lunch time.
14:30 – 16:00 OpenACC and other alternatives for GPGPU programing.
29th january
09:30 – 12:30 Individual practices (1): Programming GPUs in the cloud.
12:30 – 14:00 Lunch time.
14:00 – 16:00 Individual practices (2): Programming GPUs in the cloud.
Organizing Committee
Ginés Guerrero, NLHPC Deputy Director
Juan Acuña, Systems Administrator at PUC Physics Institute
Register
About Manuel Ujaldón
Manuel has worked in semi automatic parallelization and compilers of data parallelism for irregular applications during the development of his doctoral thesis, that concluded in 1996. During this period, formed part of the committees of specification of HPF and MPI, working as a postdoc at the Department of Computing Sciences at Maryland University in College Park (EEUU). In 2003, joined the GPGPU initiative using Cg, writing the first book in spanish on GPU programming for general purpose computing, focused on how to implement irregular applications and linear algebra algorithms in GPUs. Manuel substituted Cg for CUDA after its irruption, focusing from then on on applications of image processing and related to bioinformatics and data mining.
In the last 5 years has been co-author of more than 40 publications in journals and international congresses related to this thematics. Additionally, he has imparted more than 30 workshops on CUDA programming in universities all over the world, including european, american and australian centers of prestige. His work has been recognized by Nvidia with the Nvidia Academic Partnership award between 2008 and 2011, the Nvidia Teaching Center award between 2011 and 2013 in the Universidad de Málaga (Spain) and Newcastle University (Australia), the Nvidia Research Center award in 2012 as main researcher in the Universidad de Málaga, and finally the CUDA Fellow award in 2012.
More information available in his personal website: :http://cms.ac.uma.es/ujaldon/index.php/en
For more information please write to Ginés Guerrero at gguerrero@nlhpc.cl