GPU Computing

Vecchia Approximations of Gaussian Processes on GPUs for Scalable Spatial Modeling and Computer Model Emulation

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B9 L2 R2325

This seminar introduces GPU-accelerated Vecchia approximations to overcome Gaussian Process computational limits, enabling scalable applications for large geospatial datasets and high-dimensional computer model emulations.

ISC21 Workshop: Numerical Algorithms and Libraries for Exascale (NAL-X)

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ISC21 KAUST Frankfurt Germany Time CET

Abstract With the hardware technology scaling and the trend on heterogeneous chip design, the existing numerical algorithms and software framework may break down due to load imbalance. There is currently a fundamental mismatch between the underlying hardware architecture with high thread concurrency and the software deployment of numerical libraries, which relies on the traditional bulk synchronous programming model. Numerical software should first squeeze performance out of single node by efficiently running on manycore architectures with processor counts sharing a common memory in the

Heterogeneity in Hardware: Opportunities and Challenges for Software and Applications (SC21 Panel)

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SC21 Saint Louis MO USA

Heterogeneity in Hardware: Opportunities and Challenges for Software and Applications SC21 Panel Time: Tuesday, 16 November 2021, 10:30am - 12pm CST Location: 225-226 (America's Center, St. Louis, MO USA) Abstract With the end of Moore’s Law, the community has witnessed new hardware trends to increase performance. Today, it is not only the traditional x86 and accelerators that are part of computing systems, but also ARM, FPGAs and dedicated processors for DL workloads that equip now pioneering HPC systems. By the end of this decade, we are moving towards an era of extreme scale with “extreme

ECRC brings astronomy back home

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Astronomy research excellence is coming back home to the Middle East, where it took its first steps around 1200 BC. Custome new software developed by the KAUST Extreme Computing Research Center (ECRC) was released at the end of 2017. Named MOAO - Multiple Object Adaptive Optics – the software will contribute to the activities of the world's largest future optical telescope to be deployed in Chile in 2024.

H2Opus: a Performance-Oriented Library for Hierarchical Matrices

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H2Opus: a Performance-Oriented Library for Hierarchical Matrices Download at https://github.com/ecrc/h2opus. Experience our latest HPC software release that implements H 2-Matrix operations on shared-memory systems, possibly equipped with GPU hardware accelerators. The prime target applications for H2Opus are PDE-constrained optimizations. The features of H2Opus include: Generation of matrix structure from a point set and admissibility condition, Construction of a hierarchical matrix given a kernel function, Matrix-vector and matrix-multiple-vector multiplication, Basis orthogonalization

Mixed Feelings About Mixed Precisions: Birds of a Feather at SC22!

1 min read ·
Abstract: Come and share your experiences with the state-of-the-art of mixed-precision techniques! By wisely trading off accuracy, we can mitigate data movement overheads and increase performance of applications, including real-time adaptive optics simulations on ground-based telescopes and genome-wide association study for agricultural genomics. No free lunch, however: these optimizations require support from the software/hardware ecosystem and strong numerical validation. For instance, the tile Cholesky factorization is a fundamental matrix algorithm in solving covariance problems that

Mixed Feelings About Mixed Precisions: Birds of a Feather at SC23!

1 min read ·
Abstract What if we have been oversolving in computational science and engineering for decades? Are low precision arithmetic formats only for AI workloads? How can HPC applications exploit mixed-precision hardware features? This BoF invites the HPC community at large interested in applying mixed precisions into their workflows and discussing the impact on time-to-solution, memory footprint, data motion, and energy consumption. Experts from scientific applications/software libraries/hardware architectures will briefly provide the context on this trendy topic, share their own perspectives, and

Wajih Halim Boukaram

Ph.D. Student, Computer Science
Wajih Halim Boukaram is a PhD candidate in Computer Science. He is studying under the supervision of Professor David E. Keyes.

Peter Rautek

Research Scientist, Computer Science
Peter Rautek is a Research Scientist in the High-Performance Visualization Group working with Professor Markus Hadwiger at King Abdullah University of Science and Technology (KAUST).

Nicolas Doucet

Nicolas Doucet is a PhD student in Computer Science, working under the supervision of Professor David Keyes.

Marcin Rogowski

Ph.D. Student, Computer Science

Jens Schneider

Research Scientist, Computer Science
Jens Schneider was a Staff Scientist at the Visual Computing Center in King Abdullah University of Science and Technology (KAUST). Currently, he’s an Assistant Professor in College of Science and Engineering, Hamad Bin Khalifa University (HBKU), Qatar. Education and Early Career Jens Schneider received a diploma equivalent to Master degree in Computer Science from RWTH Aachen in Germany, 2004. He earned his Ph.D. in Computer Science from Technical University Munich, Germany, in 2009 Dr. Schneider joined KAUST in 2009 as a Postdoctoral Research Fellow. Later on, he was promoted to Research

Amani Alonazi

Amani Alonazi is a Visiting Researcher in the Image and Viedo Understanding Lab (IVUL) Research Group working with Professor Bernard Ghanem. Previously, she was a Ph.D. candidate in Computer Science at CEMSE, KAUST, and a member of KAUST's Extreme Computing Research Center, ACM, and SIAM. Areas of expertise and current scientific interests Amani's research focuses on developing novel asynchronous task-based algorithms of solvers in scientific simulations. The core of her work lies within the domain of high-performance computing, which combines performance optimizations, modeling, and

Ali Charara

Ali Charara obtained both, his MS Degree and PhD Degree from Computer Science at KAUST in 2011 and 2018 respectively. His master thesis supervisor was Alyn Rockwood and his PhD thesis supervisor was David Keyes. Ali's research interests were in High Performance Computing with a focus on parallel computing and algorithms using multicore and manycore Computer Graphics Units. Education Profile MS Degree, Computer Science, KAUST (2011) PhD Degree, Computer Science, KAUST (2018)