Manuel Ujaldon

Computer Architecture Department
University of Malaga
Spain

ujaldon <at> uma.es

HPC Accelerators with 3D Memory

Abstract:

After a decade evolving in the High Performance Computing arena, GPU-equipped supercomputers have conquered the top500 and green500 lists.

This year, major vendors have introduced new platforms based on 3D memory, like the Xeon Phi Knights Landing by Intel and the GPU Pascal by Nvidia.

This talk will review hardware features of those new HPC accelerators and potential performance for scientific applications, with an emphasis on the new

High Bandwidth Memory (HBM2) technology used by Nvidia in its future roadmap.

Bio

Manuel Ujaldon is Prof. of Computer Architecture at the Univ. of Malaga (Spain) and CUDA Fellow at Nvidia.

He worked in the 90’s on parallelizing compilers, finishing his PhD in 1996 by developing a data-parallel compiler for sparse matrix and irregular applications. Over this period, he was part of the HPF and MPI Forums, working as post-doc in the CS Dept. of the Univ. of Maryland (USA).

Last decade he started working on the GPGPU movement early in 2003 using Cg, and wrote the first book in spanish about programming GPUs for general purpose computing. He adopted CUDA when it was first released, then focusing on image processing and biomedical applications. Over the past five years, he has published more than 50 papers in journals and international conferences in these two areas.

Dr. Ujaldon has been awarded as NVIDIA Academic Partnership 2008-2011, NVIDIA Teaching Center since 2011, NVIDIA Research Center since 2012, and finally CUDA Fellow. Over the past four years, he has taught around 60 courses on CUDA programming worldwide sponsored by Nvidia, including keynotes and tutorials in ACM/IEEE conferences and academic programs in universities of 18 different countries.

For more information, you can visit:

His web page at Computer Architecture Department, Univ. of Malaga: https://cms.ac.uma.es/ujaldon/index.php/en
His web page as Nvidia CUDA Fellow: https://developer.nvidia.com/academia/fellows/manuel-ujaldon

Research interests:

GPGPU Computing on Image Processing (features extraction, segmentation, classifiers).
Biomedical Applications (large-scale image analysis, biomarkers, bio-inspired algorithms and genomic wide association studies).
Evolutionary Computation (Ant Colony Optimization).

List of publications: https://cms.ac.uma.es/ujaldon/index.php/en/research-papers