HPC

Saverio Pasqualoni

M.S. Student, Computer Science
Saverio is a Master’s student pursuing graduate studies (M.S. and Ph.D.) in Computer Science at KAUST, working in the SANDS research group on high-performance computing and collective communications, with research interests that bridge systems-level computer science and large-scale simulation through a strong mathematical foundation.
ACM Gordon Bell Prize for Climate Modelling

KAUST wins the “Nobel” of high-performance computing for climate modeling

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KAUST has been awarded the “Nobel" prize of high-performance computing—the ACM Gordon Bell Prize for Climate Modelling—in partnership with the NSF National Center for Atmospheric Research, U.S. and other partner institutions.

SIAM CSE21 (VIRTUAL) - Minisymposium on HPC Response to the COVID19 Pandemic

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KAUST

Abstract This minisymposium brings together experts in numerical simulation that have developed HPC software tools toward a better understanding coronavirus and the global COVID19 pandemic. Their recent results highlight the importance of computational science as a guiding tool that helps in uncovering the structure and mechanics of the viral spread as well as drastically reduces the number of candidate treatments that need laborious laboratory testing. From transformative medical advances to drug discovery driven by massively parallel supercomputing, this minisymposium will span a range of

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 Activities at SC22!

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Dallas TX USA

HPC accelerates! This year's motto of the Supercomputing conference...

KAUST scientists win prestigious Gauss Award for supercomputing excellence

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KAUST Ph.D. graduate Dr. Noha Al-Harthi and doctoral student Rabab Alomairy, have won the German Gauss Center for Supercomputing (GCS) Award for original research that best advances high-performance computing. This makes KAUST the first Middle Eastern institution to receive this prestigious award.

PhD Defense of Tariq AlTurkestani

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Maximizing I/O Bandwidth for Out-of-Core HPC Applications on Heterogeneous Large-Scale Systems PhD Dissertation Defense by Tariq Alturkestani PhD Student, Computer Science Thursday, July 9, 16:00 - 17:00, https://kaust.zoom.us/j/94054511362 Contact Person: Tariq Alturkestani The execution rate of floating-point operations has typically increased by an order of magnitude every four years during the last 30 years of modern comput ing. This exponential growth in terms of computational power has benefited from the hardware technology scaling. However, memory and storage systems have not maintained

Turning your desktop to a Supercomputer with ExaGeoStatR

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Turning your desktop to a Supercomputer with ExaGeoStatR Download at https://github.com/ecrc/exageostatR. Remember the old times where you had to leave your R simulations running for the whole night on your desktop due to a large climate/weather dataset? ExaGeoStatR combines the user productivity of R with high performance computing linear algebra software libraries to deliver supercomputing-style environment right below your desk. ExaGeoStatR enables computing the maximum likelihood using large environmental datasets on R, while extracting performance from the underlying hardware resources

ECRC contributions to SIAM CSE21

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ECRC @ SIAM CSE21! Follow us @KAUST_ECRC As in previous SIAM conferences on Parallel Processing (PP) and Computational Science and Engineering (CSE), ECRC members and their collaborators will have a strong presence at SIAM CSE21, nominally in Fort Worth, Texas, but held virtually due to the pandemic. ************************************************** SIAM CSE21 will run virtually with live sessions. ************************************************** Registration to SIAM CSE is required to gain access to the online platform and attend live sessions. Once registered, please use your personal

Designing Tomorrow's Algorithms on Today's Architectures: a Case Study with Stencil Computations Using AMD 3D V-Cache™ Technology

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Regular stencil computations constitute the main core kernel in many temporally explicit approaches for structured grid finite-difference, finite-volume, and finite-element discretizations of partial differential equation conservation laws. For various blocking dimensions, the Spatial Blocking (SB) approach enables data reuse within multiple cache levels. However, the straightforward generalization of SB to manycore architectures, with each core owning an exclusive share of cache may leave performance on the table. The next two figures show the typical 25-point 3D star stencil used in seismic

Steering Customized AI Architectures for HPC Scientific Workloads: A Bird of Feather at SC22!

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Abstract: We explore the possibilities of a hybrid system capable of solving both HPC and AI scientific problems. Such a hybrid architecture combines the synergism between classical HPC platforms and dedicated AI chip systems, which is important due to the computational challenges brought to the fore by massively parallel Exascale systems. We discuss the system functionality, the algorithmic software adaptations, and performance considerations. We present efforts in supporting AI/ML applications in addition to seismic imaging, climate/weather prediction, and computational astronomy on hybrid

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

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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!

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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

Esmail Abdul Fattah

Ph.D., Statistics

HPC

Introduction I am currently serving as a Postdoctoral Researcher at the Extreme Computing Research Center at KAUST, where I have the privilege of working under the leadership of the center's director, Professor David Keyes. My research journey here is further enriched by the close collaboration and guidance I receive from Dr. Hatem Ltaief, whose expertise significantly contributes to my professional growth and research endeavors in this dynamic field. My academic journey led me to earn a Ph.D. in Statistics under the mentorship of Professor Håvard Rue, working within his esteemed research