High Performance Computing

Keynote Speaker | The 8th BEAR PGR Conference & Users Forum 2018

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The University of Birmingham in the United Kingdom

Abstract KAUST Assistant Professor Robert Hoehndorf will be a keynote speaker at the 8th BEAR PGR Conference & Users Forum​ at the University of Birmingham in the United Kingdom. This event focuses on, but not limited to, computational analysis and numerical modeling the conference will cater to researchers of all schools interested in BEAR facilities. Such as the use of the high-performance computing (HPC) system, BlueBEAR, cloud storage or data visualization.​

Contributions to Computational Methods for Association Extraction from Biomedical Data: Applications to Text Mining and In Silico Toxicology

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B2 L5 R5220

Abstract The task of association extraction involves identifying links between different entities. Here, we make contributions to two applications related to the biomedical field. The first application is in the domain of text mining aiming at extracting associations between methylated genes and diseases from biomedical literature. Gathering such associations can benefit disease diagnosis and treatment decisions. We developed the DDMGD database to provide a comprehensive repository of information related to genes methylated in diseases, gene expression, and disease progression. Using DEMGD, a

Exploiting Data Sparsity in Matrix Algorithms for Adaptive Optics and Seismic Imaging

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B2 R5209;

This thesis addresses the exponential growth of experimental data and the resulting computational complexity seen in two major scientific applications, which account for most cycles consumed on today's supercomputers.

New cost-effective GPUs solver redesigns the computational game

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Prof. David Keyes and his team proposed a GPUs light architecture to solve systems of multiple equations involving a large amount of data. Broadly used in computer gaming, mobile, and PC graphics - GPUs allow customizing an effective result-driven support to create a computational framework for increasing the number of processors while reducing the memory required to temporarily store the data.

Pulling rank on spatial statistics

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A technique that uses the power of computing could solve statistical problems cheaper and faster than current methods.

KAUST gets ready for SC18

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For the past 10 years, KAUST has made a strong presence at the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC) that takes place in different cities around the U.S. every year. 2018 will mark a special year for KAUST at SC, which will take place in Dallas, Texas, in November, with around 13,000 supercomputing professionals in attendance. The University will have an engaging presence on the exhibition floor and in the seminars, and the technical program of SC18 will be chaired by the Director of the KAUST Extreme Computing Research Center (ECRC)

Yuxi Hong

Ph.D. Student, Computer Science
Yuxi Hong is a PhD student working with Professor David Keyes. He is working on accelerating the training process of deep learning from different aspects. Why KAUST? KAUST is a great place for research. Why HPC and machine learning? I believe we need more computation in the future. Scalable and efficient computing methods are basic tools for the scientific research. Education Profile MS Tsinghua University. BS Tsinghua University.

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.

Tongzhou Gu

M.S. Student, Computer Science
Tongzhou is a MS/Ph.D. Student in the Software-Defined Advanced Networked and Distributed Systems (SANDS) Lab in KAUST, advised by Prof. Marco Canini. He obtained his bachelor’s degree from the Southern University of Science and Technology in 2022. During the time of his undergraduate study, he was an SDE intern at AWS Shanghai AI Lab and a research intern at SANDS Lab. Tongzhou’s research interests lie in High-Performance Networking and Computing as well as Distributed Machine Learning Systems. Currently, he is working on accelerating large-scale ML training with comprehensive approaches

Tariq Alturkestani

Ph.D. Student, Computer Science
Tariq is a PhD student in Computer Science working under the supervision of Professor David E. Keyes. He is working on developing a library that enables users to overlap I/O and compute. Tariq holds a Bachelors degree from Penn State University and a Master from KAUST. Education Profile MS, Computer Science, King Abdullah University of Science and Technology (KAUST), 2014. BS, Computer Science, Penn State University, USA, 2013.

Renmin Han

Postdoctoral Research Fellow, Structural and Functional Bioinformatics
Renmin Han is a Research Scientist at the Structural and Functional Bioinformatics Group (SFB) of Professor Xin Gao at King Abdullah University of Science and Technology (KAUST). ​Renmin obtained his Ph.D. degree in Computer Science from the Institute of Computing Technology, Chinese Academy of Sciences, China. Research Interests ​Renmin is interested in the development of computer science. Currently, he is working on imaging processing in electron micrography, especially for the reconstruction of biological ultrastructures. His work is to use computational methods to improve the boundary of

Rabab Alomairy

Rabab Alomairy is a PhD candidate in Computer Science. She is studying under supervision of Professor David E. Keyes and Senior research scientist Hatem Ltaief. Research Interest Rabab's research interests focus on Task-Based Numerical Libraries and Applications, Performance Optimizations, AI on Large Scale and Dense Linear Algebra. Why KAUST? I choose KAUST because KAUST is the greenland that is fertile for growing any innovative idea. Why did you choose high performance computing? I choose high performance computing field because it is the key for many disciplines. Many of grand challenges

Omar Knio

Professor Knio focuses on developing state-of-the-art methods and algorithms for simulating complex multiscale systems, and their implementation to the analysis and optimization of renewable energy systems.

Noha AlHarthi

Noha Al-Harthi received her PhD in Computer Science and was a member of KAUST's Extreme Computing Research Center and CEML. Her doctoral dissertation was conducted under the supervision of Professor David Keyes and Professor Hakan Bagci in the field of high-performance computing for wave propagation. Education Ph.D., Computer Science, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia, 2012-2019. M.S, Computer Science, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia, 2011-2012. B.S., Information System, Effat University, Jeddah

Nicolas Doucet

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

Mohamed Hassan

Postdoctoral Research Fellow, Computer Science
Mohamed W. Hassan is a Postdoctoral Research Fellow in the Accelerated Connected Computing Lab at KAUST. He works on reconfigurable computing and computer architecture for high performance computing. He received his PhD in Electrical and Computer Engineering from Virginia Tech in 2021. He received Bachelor's and Master's degrees in Computer Engineering from the Arab Academy of Science, Egypt in 2010 and 2013 respectively. Mohamed's research has explored accelerating scientific applications in heterogenous systems including CPUs, GPUs, and FPGAs. He is especially interested in optimizing High
KAUST-CEMSE-Matteo-Parsani

Matteo Parsani

Professor Parsani develops robust, variable order and self-adaptive algorithms for solving fluid flow problems in complex geometries. The application domains currently driving Parsani's research are compressible computational aerodynamics, computational aeroacoustics for noise reduction in vehicles and molecular communication.

Marcin Rogowski

Ph.D. Student, Computer Science

Lisandro Dalcin

Lisandro Dalcin obtained a degree in Electromechanical Engineering from National Technological University, Concepción del Uruguay, Argentina in 2001 and a PhD degree in Engineering Sciences, Computational Mechanics from National University of the Littoral, Santa Fe, Argentina in 2008. Research Interest Lisandro Dalcin's research interest include ​​Parallel and High Performance Computing, Scientific Software Development, Finite Element Methods and Computational Fluid Dynamics.​ Education Profile ​​PhD in Engineering Sciences, Computational Mechanics, National University of the Littoral, Santa

Konstantin Burlachenko

Ph.D. Student, Computer Science
Konstantin Burlachenko is a Ph.D. candidate at the KAUST Optimization and Machine Learning Lab under the supervision of Professor Peter Richtarik.

Karim Awara

Karim Awara obtained his Master's Degree in Computer Science under the supervision of Professor Panagiotis Kalnis from King Abdullah University of Science and Technology. Research Interests Karim's research interests included the Database and High-Performance Computing field. Awards and Distinctions Awarded, internationally, as one of the best 5 teams in SIGMOD 2010 contest for developing high multi-query optimization techniques. And presented the work at SIGMOD conference, June 2010 in Indianapolis, IN, USA. Rewarded as one of the top four teams in Egypt in a software Engineering competition

Hatem Ltaief

Hatem is a Principal Research Scientist at CEMSE Division at KAUST. His research interests include mixed-precision algorithms, parallel numerical algorithms, parallel programming models, performance optimizations for manycore architectures and high performance computing. He has been collaborating with domain scientists, i.e., astronomers, statisticians, computational chemists and geophysicists, on leveraging their applications to meet the challenges at exascale.

George Turkiyyah

Professor Turkiyyah's expertise lies in high-performance and GPU computing, numerical simulation and optimization and their application to machine learning and large-scale modeling.

Elmootazbellah Elnozahy

Professor (former), Computer Science
Elmootazbellah (Mootaz) Elnozahy is a renowned computer scientist who has filed, individually and with colleagues, 58 U.S. patents. He has successfully secured research and development funding grants of ~$320M.

David Keyes

Senior Associate to the President, King Abdullah University of Science and Technology
David Keyes works at the interface of computational science and engineering and high performance computing, which he helped edit into the DNA of KAUST as a founding Dean in 2009 and then as director of the Extreme Computing Research Center. He currently serves as Senior Associate to the President, Chair of the KAUST RDIA Economies of the Future committee, and delegate to the Saudi Center for the Fourth Industrial Revolution.

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)

Ali H. AlNasser

M.S. Student, Computer Science
Ali AlNasser is a Masters student in Computer Science. His research interests are scaling deep learning algorithms available now to be used on multicore computers by leveraging the high parallelism in Deep learning. Why KAUST? The abundance of opportunities available in KAUST. Education Profile B.S, Electrical & Computer Engineering, University of Colorado at Boulder. B.S, Applied Mathematics, University of Colorado at Boulder.