Topics

<> machine learning (24)

Yimeng Chen

Postdoctoral Research Fellow, Computer Science
Yimeng Chen is a Postdoctoral Researcher in Prof. Jürgen Schmidhuber's research group at King Abdullah University of Science and Technology (KAUST).

Nanbo Li

Postdoctoral Research Fellow, Computer Science
Nanbo Li is a Postdoctoral Fellow working in Prof. Jürgen Schmidhuber research group at the King Abdullah University of Science and Technology (KAUST) Center of Excellence for Generative AI.

Omar Ahmed

M.S. Student, Bioengineering
Omar Ahmed is an MS student in the Bioengineering department at KAUST. His research explores the mechanisms that enable brain signal generalisability across individuals, addressing how neural activity patterns can be reliably interpreted despite significant inter-subject and temporal variability. A major challenge in neuroscience is that brain activity varies substantially between people and even within the same person over time, which limits the development of universal diagnostic and therapeutic tools. Towards this goal, Omar is developing deep learning models that can identify consistent
KAUST-CEMSE-CS-VISION-CAIR-Dalal-Aldossary

Dalal E. Aldossary

M.S. Student, Computer Science
Dalal is a Master’s student in Computer Science at KAUST. She is part of the VISION-CAIR and the Neuroscience & AI Lab (NAIL), where she works on developing machine learning models that interpret and learn EEG representations and behavior.

Zakaria El Kassimi

KAUST offers a unique environment where applied mathematics and data science meet real-world impact, with exceptional resources and a supportive community for ambitious research.

Jonathan Klein

Research Scientist, Computer Science
My fields of research interests include computational simulation, plant simulation and modeling, synthetic training data, machine learning architectures, none-line-of-sight imaging, and computational photography.

Yibin Wang

Keep Moving forward

Andrea Vanessa Rocha

Research Specialist, Statistics
Chengjie zhao

Chengjie Zhao

Visiting Researcher, Information Science Lab
Visiting Student, King Abdullah University of Science and Technology

Mohamed Ads

Visiting Student, King Abdullah University of Science and Technology

Hayssam Dahrouj

Senior Research Scientist at KAUST (King Abdullah University of Science and Technology)

Karen Sanchez

Postdoctoral Research Fellow
Karen Sanchez is a Postdoctoral Researcher in the IVUL lab at KAUST, specializing in deep learning, machine learning, and artificial intelligence (AI) for healthcare applications. Her research focuses on video understanding, domain adaptation, generative AI, and methods for preserving patient privacy.

Hani A. Al Majed

M.S. Student
Electrical and Computer Engineering Master's student at KAUST under the supervision of Professor Bernard Ghanem, with expertise in machine learning workflow automation, physics-informed neural operators, and AI for Science, particularly in chemistry applications. Passionate about leveraging AI to solve complex scientific problems.

Ahmad Sait

M.S. Student, Computer Science
Ahmad Sait is a Master's student in the Computer Science program at KAUST. Before joining KAUST, Ahmad obtained his Bachelor's degree in Computer Science from King Abdulaziz University, Saudi Arabia. Ahmad is also a KAUST Academy graduate from the AI track, having been under the supervision of Prof. Naeemullah Khan. The Academy provided him with seven opportunities to assist in teaching students enrolled in subsequent cohorts.

Saleh AlJazzar

Research Fellow at King Abdullah University of Science and Technology (KAUST) .

Muhammad Esmat

Visiting student at, King Abdullah University of Science and Technology (KAUST).

Yasser Jaber

Visiting Student Researcher ,Machine Learning Engineer at KAUST (King Abdullah University of Science and Technology).
Syed Abidullah Fareed

Syed Abidullah Fareed

Visiting Student (former), Information Science Lab

Ahsan Mehmood

Intern (former), Information Science Lab
Visiting student at King Abdullah University of Science and Technology (KAUST).

Abdulkarem Badiea Alshaibani

Visiting Student at the Information Science Lab at the King Abdullah University of Science and Technology (KAUST).

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

1 min read ·
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

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.
Sameh Abdulah

Sameh Abdulah

Sameh Abdulah > Appointments, Roles and Affiliations, Hierarchical Computations on Manycore Architectures
Dr. Sameh Abdulah specializes in HPC, scalable algorithms, and climate modeling, with innovations receiving the ACM Gordon Bell Prize for Climate Modelling.

David Keyes

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.
<> High Performance Computing (22)

New cost-effective GPUs solver redesigns the computational game

1 min read ·
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

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

KAUST gets ready for SC18

1 min read ·
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)

Tariq receives his best paper award at EuroPar'2020

1 min read ·
Maximizing I/O Bandwidth for Out-of-Core HPC Applications on Heterogeneous Large-Scale Systems Best Paper Presentation by Tariq Alturkestani PhD Student, Computer Science, KAUST Thursday, Aug 27, 3:30pm - 4:00pm (AST) https://zoom.us/j/99947879910 Tariq will present his best paper at EuroPar'2020 at the virtual EuroPar'2020 conference in Warsaw, Poland. The reverse time migration (RTM) method is critical in seismic imaging for oil and gas industries. He demonstrates the effectiveness of his Multilayer Buffer System (MLBS) framework on Shaheen-2 (using 2048 compute nodes) and Summit

H2Opus: a Performance-Oriented Library for Hierarchical Matrices

1 min read ·
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

Our Masked Guest Speakers Series

1 min read ·
Every week, we have a masked guest speaker opening our HiCMA weekly meeting by giving a remote talk on broad topics related to numerical linear algebra, high performance computing, programming models and performance optimizations. Our motto is fun and science!

The Arab World Prepares the Exascale Workforce

1 min read ·
The April 2021 Communications of the ACM special section on computing in the Arab world features an article by ECRC Director and KAUST founding dean David Keyes on preparing the exascale workforce. Keyes muses on the lure of hands-on opportunities to resolve today’s application-architecture tension with innovative algorithms for recruiting students, and he follows the placement of a dozen recent ECRC doctoral students from the MENA region in the US exascale computing project and Saudi industry. For them, “graduation” means an upgrade to a more powerful computer :-). Several have also seen

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.

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.

Stefano Zampini

As a computational mathematician and software engineer, Stefano Zampini's work lies at the intersection of numerical analysis, predictive simulations, and high-performance computing, with recent forays into machine learning.

Rabab Alomairy

KAUST alumna Dr. Rabab Alomairy advances high-performance computing and AI research as a postdoctoral fellow at MIT.

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.

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

Hatem Ltaief

Principal Research Scientist, Applied Mathematics and Computational Science
Dr. Hatem Ltaief is a Principal Research Scientist at KAUST. He works on mixed-precision algorithms and performance optimizations to help HPC scientific applications address the exascale challenges. His innovations have been recognized with the ACM Gordon Bell Prize (shared) for Climate Modeling in 2024.

Dalal Sukkari

Research interests and present research project. Dalal's research centers on a new high performance implementation of the QR-based Dynamically Weighted Halley iterations (QDWH) to compute the polar decomposition and its application to the SVD (QDWH-SVD). She has introduced a high performance QDWH-SVD implementation on multicore architecture enhanced with multiple GPUs, and on distributed memory based on the state-of-the-art vendor-optimized numerical library ScaLAPACK, and has presented the first asynchronous, task-based formulation of the polar decomposition QDWH and its corresponding

David Keyes

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.
<> HPC (19)

KAUST researchers define the emerging field of high-performance statistical computing (HPSC)

4 min read ·
KAUST researchers outline a new discipline for statistical computing at supercomputing scale.

Amal Alghamdi

KAUST alumna Dr. Rabab Alomairy wins prestigious IEEE CS TCHPC Early Career Researchers Award

3 min read ·

HPC

KAUST alumna and Ibn Rushd Postdoctoral Fellow Dr. Rabab Alomairy received the IEEE CS Early Career Researchers Award in HPC, becoming the first Middle Eastern and one of the youngest recipients professionally to earn this distinction in the award’s decade-long history.

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

1 min read ·
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...

PhD Defense of Tariq AlTurkestani

1 min read ·
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

KAUST scientists win prestigious Gauss Award for supercomputing excellence

1 min read ·
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.

Turning your desktop to a Supercomputer with ExaGeoStatR

1 min read ·
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

1 min read ·
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

1 min read ·
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!

1 min read ·
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!

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

A predictive eye on the prize

3 min read ·
Climate prediction models have had a mathematical makeover that has won attention from a computer science award.

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

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
<> artificial intelligence (12)

Omar Ahmed

M.S. Student, Bioengineering
Omar Ahmed is an MS student in the Bioengineering department at KAUST. His research explores the mechanisms that enable brain signal generalisability across individuals, addressing how neural activity patterns can be reliably interpreted despite significant inter-subject and temporal variability. A major challenge in neuroscience is that brain activity varies substantially between people and even within the same person over time, which limits the development of universal diagnostic and therapeutic tools. Towards this goal, Omar is developing deep learning models that can identify consistent

Nuclear Fusion Powered by AI and HPC

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B9 L2 R2325

This talk presents advanced simulations with AI-driven optimization to improve the performance of a next-generation plasma-jet-driven magneto-inertial fusion concept.
Salem Alsaqaf

Salem Al-saqaf

Salem Al-Saqaf is an Electrical and Computer Engineer specializing in semiconductors, electronics and AI. He combines strong academic training with practical industry experience in AI-driven solutions, data science, and system optimization. His work spans applied research and real-world innovation, aiming to advance intelligent systems, enhance semiconductor applications, and develop technologies that bridge academic discovery with industrial impact.
Najmeddine Dhieb

Najmeddine Dhieb

Mohamed Ads

Visiting Student, King Abdullah University of Science and Technology

Yasmeen Alsaedy

M.S. Student, Computer Science
She is an AI researcher specializing in generative AI and deep learning. With a strong academic foundation and hands-on experience in machine learning, data science and artificial intelligence, she is passionate about advancing AI applications in real-world scenarios. She has contributed to cutting-edge projects, published research, and collaborated on innovative solutions that bridge the gap between AI theory and practice. Her expertise includes designing and implementing advanced data models, AI-driven visual/text computing, and deep learning architectures.

Yasser Jaber

Visiting Student Researcher ,Machine Learning Engineer at KAUST (King Abdullah University of Science and Technology).
Syed Abidullah Fareed

Syed Abidullah Fareed

Visiting Student (former), Information Science Lab

Ahmed Youssef Ragab Radwan

Visiting Student (former), Information Science Lab
Visiting student at the Information Science Lab, in the Electrical Engineering Department, CEMSE, King Abdullah University of Science and Technology (KAUST)

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

-

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

ECRC Activities at SC22!

-

Dallas TX USA

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

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

1 min read ·
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
<> GPU Computing (12)

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

-

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)

-

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

1 min read ·
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.

Tariq receives his best paper award at EuroPar'2020

1 min read ·
Maximizing I/O Bandwidth for Out-of-Core HPC Applications on Heterogeneous Large-Scale Systems Best Paper Presentation by Tariq Alturkestani PhD Student, Computer Science, KAUST Thursday, Aug 27, 3:30pm - 4:00pm (AST) https://zoom.us/j/99947879910 Tariq will present his best paper at EuroPar'2020 at the virtual EuroPar'2020 conference in Warsaw, Poland. The reverse time migration (RTM) method is critical in seismic imaging for oil and gas industries. He demonstrates the effectiveness of his Multilayer Buffer System (MLBS) framework on Shaheen-2 (using 2048 compute nodes) and Summit

H2Opus: a Performance-Oriented Library for Hierarchical Matrices

1 min read ·
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.

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

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)
<> Deep learning (11)

Yimeng Chen

Postdoctoral Research Fellow, Computer Science
Yimeng Chen is a Postdoctoral Researcher in Prof. Jürgen Schmidhuber's research group at King Abdullah University of Science and Technology (KAUST).

Zakaria El Kassimi

KAUST offers a unique environment where applied mathematics and data science meet real-world impact, with exceptional resources and a supportive community for ambitious research.

Adonai Vera

Machine Learning Engineer with 6+ years of experience specializing in computer vision, deep learning, and robotics. Led AI solutions for retail analytics, UAV systems, and edge devices. Author, educator, and TensorFlow Google Developer Expert.

Juan Pablo Muñoz Díaz

Karen Sanchez

Postdoctoral Research Fellow
Karen Sanchez is a Postdoctoral Researcher in the IVUL lab at KAUST, specializing in deep learning, machine learning, and artificial intelligence (AI) for healthcare applications. Her research focuses on video understanding, domain adaptation, generative AI, and methods for preserving patient privacy.

Mhd. Emad Alolaby

Sixiu Liu

Ph.D. degree in Earth science and engineering with the King Abdullah University of Science and Technology (KAUST)

Ahmed Youssef Ragab Radwan

Visiting Student (former), Information Science Lab
Visiting student at the Information Science Lab, in the Electrical Engineering Department, CEMSE, King Abdullah University of Science and Technology (KAUST)
<> Computer Vision (10)

Nanbo Li

Postdoctoral Research Fellow, Computer Science
Nanbo Li is a Postdoctoral Fellow working in Prof. Jürgen Schmidhuber research group at the King Abdullah University of Science and Technology (KAUST) Center of Excellence for Generative AI.

Omar Ahmed

M.S. Student, Bioengineering
Omar Ahmed is an MS student in the Bioengineering department at KAUST. His research explores the mechanisms that enable brain signal generalisability across individuals, addressing how neural activity patterns can be reliably interpreted despite significant inter-subject and temporal variability. A major challenge in neuroscience is that brain activity varies substantially between people and even within the same person over time, which limits the development of universal diagnostic and therapeutic tools. Towards this goal, Omar is developing deep learning models that can identify consistent
KAUST-CEMSE-CS-VISION-CAIR-Dalal-Aldossary

Dalal E. Aldossary

M.S. Student, Computer Science
Dalal is a Master’s student in Computer Science at KAUST. She is part of the VISION-CAIR and the Neuroscience & AI Lab (NAIL), where she works on developing machine learning models that interpret and learn EEG representations and behavior.

Adonai Vera

Machine Learning Engineer with 6+ years of experience specializing in computer vision, deep learning, and robotics. Led AI solutions for retail analytics, UAV systems, and edge devices. Author, educator, and TensorFlow Google Developer Expert.

Abdelrahman Eldesokey

Postdoctoral Research Fellow
Abdelrahman Eldesokey is a Postdoctoral Fellow at KAUST, working on Generative AI and Computer Vision. His research focuses on diffusion models, multimodal large language models, and vision foundation models, aiming to make generative systems more controllable, interpretable, and reliable.
Najmeddine Dhieb

Najmeddine Dhieb

Karen Sanchez

Postdoctoral Research Fellow
Karen Sanchez is a Postdoctoral Researcher in the IVUL lab at KAUST, specializing in deep learning, machine learning, and artificial intelligence (AI) for healthcare applications. Her research focuses on video understanding, domain adaptation, generative AI, and methods for preserving patient privacy.

Aznaur Aliev

M.S. Student

Hani A. Al Majed

M.S. Student
Electrical and Computer Engineering Master's student at KAUST under the supervision of Professor Bernard Ghanem, with expertise in machine learning workflow automation, physics-informed neural operators, and AI for Science, particularly in chemistry applications. Passionate about leveraging AI to solve complex scientific problems.

Ahmad Sait

M.S. Student, Computer Science
Ahmad Sait is a Master's student in the Computer Science program at KAUST. Before joining KAUST, Ahmad obtained his Bachelor's degree in Computer Science from King Abdulaziz University, Saudi Arabia. Ahmad is also a KAUST Academy graduate from the AI track, having been under the supervision of Prof. Naeemullah Khan. The Academy provided him with seven opportunities to assist in teaching students enrolled in subsequent cohorts.
<> cybersecurity (8) <> Signal processing (8)

Serine Medjber

Visiting student at King Abdullah University of Science and Technology (KAUST) under the supervision of Mr. Tareq Al-Naffouri

Mohammed Amine Labbas

Visiting student at King Abdullah University of Science and Technology (KAUST) under the supervision of Mr. Tareq Al-Naffouri
Chengjie zhao

Chengjie Zhao

Visiting Researcher, Information Science Lab
Visiting Student, King Abdullah University of Science and Technology
Almutasem Bellah Enad

Almutasem Bellah Enad

Visiting Researcher (former), Information Science Lab
Visiting Student, King Abdullah University of Science and Technology, Present M.Eng in Electrical and Computer Engineering, American University of Beirut, Lebanon
Ahmad Dkhan

Ahmad Dkhan

Visiting Scholar (former), Information Science Lab
Visiting Student, King Abdullah University of Science and Technology Present -Master's in Electrical and Computer Engineering, American University of Beirut, Lebanon

Saleh AlJazzar

Research Fellow at King Abdullah University of Science and Technology (KAUST) .

Alaa Alameer Ahmad

Research visit to communication theory lab in computer, electrical and mathematical sciences and engineering. KAUST (King Abdullah University of Science and Technology) ,Worked with research groups supervised by Prof. Mohamed-Slim Alouini and Prof. Tareq AL-Naffouri.

Abdullatif Al-Rabah

MS Degree, Computer, Electrical and Mathematical Sciences and Engineering at King Abdullah University of Science and Technology (KAUST).
<> applied mathematics (7)

Juan Pablo Muñoz Díaz

Peter Schmid

​Professor Schmid's research interests are in theoretical and computational fluid dynamics, with emphasis on hydrodynamic stability theory, flow control, model reduction and system identification. He is also interested in computational techniques for flow optimization and quantitative flow analysis.

Taking computing to the next level

1 min read ·
KAUST’s new supercomputer will enable ground-breaking scientific modeling and analysis in Saudi Arabia and worldwide.

Taking graphics cards beyond gaming

1 min read ·
A highly efficient mathematical solver designed to run on graphics processors gives scientists and engineers a powerful new tool for a common computational problem.

Signaling success for 5th gen communications

1 min read ·
An efficient wireless signal optimization scheme achieves peak performance for next-generation mobile communications.

Cutting datasets down to size

1 min read ·
A powerful statistical tool could significantly reduce the burden of analyzing very large datasets.

Keep the data coming

1 min read ·
A continuous data supply ensures data-intensive simulations can run at maximum speed.
<> IoT (7)
Salem Alsaqaf

Salem Al-saqaf

Salem Al-Saqaf is an Electrical and Computer Engineer specializing in semiconductors, electronics and AI. He combines strong academic training with practical industry experience in AI-driven solutions, data science, and system optimization. His work spans applied research and real-world innovation, aiming to advance intelligent systems, enhance semiconductor applications, and develop technologies that bridge academic discovery with industrial impact.

Serine Medjber

Visiting student at King Abdullah University of Science and Technology (KAUST) under the supervision of Mr. Tareq Al-Naffouri

Mohammed Amine Labbas

Visiting student at King Abdullah University of Science and Technology (KAUST) under the supervision of Mr. Tareq Al-Naffouri
Ruochen Zhu

Ruochen Zhu

Mohamed Ads

Visiting Student, King Abdullah University of Science and Technology
Syed Abidullah Fareed

Syed Abidullah Fareed

Visiting Student (former), Information Science Lab

Ahsan Mehmood

Intern (former), Information Science Lab
Visiting student at King Abdullah University of Science and Technology (KAUST).
<> statistics (7)

Yimeng Chen

Postdoctoral Research Fellow, Computer Science
Yimeng Chen is a Postdoctoral Researcher in Prof. Jürgen Schmidhuber's research group at King Abdullah University of Science and Technology (KAUST).
Juan Jose Galeano Arenas

Juan José Galeano Arenas

Ph.D. Student, Statistics
Juan José Galeano Arenas is a MS/PhD student at the King Abdullah University of Science and Technology (KAUST), studying under the supervision of Professor Håvard Rue in his research group.

Pulling rank on spatial statistics

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

Cutting datasets down to size

1 min read ·
A powerful statistical tool could significantly reduce the burden of analyzing very large datasets.

Pop stats for big geodata

1 min read ·
A universal high-performance computing interface allows popular statistical tools to run efficiently on large geospatial datasets.

Mixing precision for model acceleration

1 min read ·
A mixed-precision approach for modeling large geospatial datasets can achieve benchmark accuracy with a fraction of the computational run time.

A model for millions of locations

1 min read ·
CEMSE statisticians developed a framework which enables modeling of a range of meteorological and environmental datasets from up to 2 million locations globally.
<> numerical linear algebra (6)

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

-

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)

-

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

KAUST scientists win prestigious Gauss Award for supercomputing excellence

1 min read ·
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.

H2Opus: a Performance-Oriented Library for Hierarchical Matrices

1 min read ·
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

Our Masked Guest Speakers Series

1 min read ·
Every week, we have a masked guest speaker opening our HiCMA weekly meeting by giving a remote talk on broad topics related to numerical linear algebra, high performance computing, programming models and performance optimizations. Our motto is fun and science!

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

1 min read ·
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
<> parallel algorithms (6)

ECRC brings astronomy back home

1 min read ·
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.
Sameh Abdulah

Sameh Abdulah

Sameh Abdulah > Appointments, Roles and Affiliations, Hierarchical Computations on Manycore Architectures
Dr. Sameh Abdulah specializes in HPC, scalable algorithms, and climate modeling, with innovations receiving the ACM Gordon Bell Prize for Climate Modelling.

Li Luo

Research Interest Li Luo's research interest include Scalable Parallel Algorithms, Computational Fluid Dynamics (CFD). Why KAUST? Discuss with the top class faculty, work with the world-class equipment, and enjoy the most diversified culture on the planet. Why did you choose your field of research? Simulation of large flow problems is computationally demanding, such as the two-phase flow and the blood flow in realistic cases. The use of supercomputers and highly scalable parallel algorithms is necessary. Research projects P2Pflow: a Parallel two-Phase flow solver P2Pflow is a parallel finite

Long Qu

Dr. Long Qu is a Research Scientist at the Extreme Computing Research Center at KAUST, working with Prof. David E. Keyes and Dr. Hatem Ltaief. Research Interests Long Qu's research interests include seismic imaging and high performance computing on heterogeneous hardware architectures.

Kadir Akbudak

Dr. Kadir Akbudak is a Consultant at Extreme Computing Research Center at KAUST, working with Professor David E. Keyes and Dr. Hatem Ltaief. Research Interests Kadir Akbudak's research interests include Combinatorial scientific computing, Graph and hypergraph partitioning, Locality-aware partitioning and scheduling, High performance kernels for sparse computations, Vectorization for irregular applications, Iterative numerical methods and Parallel numerical algorithms. Education Profile Ph.D., Computer Engineering, Bilkent University, 2015. M.S., Computer Engineering, Bilkent University, 2009

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
<> supercomputing (6)

Taking computing to the next level

1 min read ·
KAUST’s new supercomputer will enable ground-breaking scientific modeling and analysis in Saudi Arabia and worldwide.

KAUST gets ready for SC18

1 min read ·
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)

KAUST Professor David Keyes to chair International Supercomputing Conference 2020

1 min read ·
David Keyes, KAUST professor of applied mathematics and computational science; director of the University's Extreme Computing Research Center; and senior associate to the President of KAUST, will chair the International Supercomputing Conference (ISC) 2020. He will be the first program chair from a Middle Eastern institution, as announced by ISC 2020.

Shaheen II open to serve COVID-19 research around the Kingdom

1 min read ·
The COVID-19 pandemic has imposed challenges across the globe that need to be solved using scientific discovery and innovation. In line with that, the KAUST Supercomputing Core Laboratory (KSL) has opened a call for proposals that require its supercomputer Shaheen II, as well as other cluster computing resources, to support research projects.

KAUST scientists win prestigious Gauss Award for supercomputing excellence

1 min read ·
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.

Mixing precision for model acceleration

1 min read ·
A mixed-precision approach for modeling large geospatial datasets can achieve benchmark accuracy with a fraction of the computational run time.
<> AI (5) <> big data (5)

On The Coupling between HPC and Statistics: Challenges, Opportunities, and Future Trends of Emerging Techniques -- (Virtual SIAM CSE21 Minisymposium)

-

KAUST

Abstract Big data modeling/inference and large-scale simulations have followed largely independent paths to the high-performance computing (HPC) frontier, but important opportunities now arise that can be addressed by combining the strengths of each. HPC is becoming increasingly significant in scaling existing statistical methods to larger and more complex applications and developing novel methods that are amenable to scaling within the constraints that exist in modern HPC architectures. The purpose of this minisymposium is to bring together researchers in the area of statistics and HPC to

Keep the data coming

1 min read ·
A continuous data supply ensures data-intensive simulations can run at maximum speed.

Mixing precision for model acceleration

1 min read ·
A mixed-precision approach for modeling large geospatial datasets can achieve benchmark accuracy with a fraction of the computational run time.

Code of collaboration

1 min read ·
David Keyes's and Matteo Ravasi's cross-disciplinary project results in improved efficiency for seismic processing, with promising applications for the energy industry.

Kadir Akbudak

Dr. Kadir Akbudak is a Consultant at Extreme Computing Research Center at KAUST, working with Professor David E. Keyes and Dr. Hatem Ltaief. Research Interests Kadir Akbudak's research interests include Combinatorial scientific computing, Graph and hypergraph partitioning, Locality-aware partitioning and scheduling, High performance kernels for sparse computations, Vectorization for irregular applications, Iterative numerical methods and Parallel numerical algorithms. Education Profile Ph.D., Computer Engineering, Bilkent University, 2015. M.S., Computer Engineering, Bilkent University, 2009
<> Cyber Security (5) <> extreme computing (5)
ACM Gordon Bell Prize for Climate Modelling

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

1 min read ·
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.

Superior seismic imaging for better drilling

1 min read ·
Software could transform underground imaging of fossil fuel reserves by providing unprecedented detail in record time.

Keep the data coming

1 min read ·
A continuous data supply ensures data-intensive simulations can run at maximum speed.

Mixing precision for model acceleration

1 min read ·
A mixed-precision approach for modeling large geospatial datasets can achieve benchmark accuracy with a fraction of the computational run time.
Sameh Abdulah

Sameh Abdulah

Sameh Abdulah > Appointments, Roles and Affiliations, Hierarchical Computations on Manycore Architectures
Dr. Sameh Abdulah specializes in HPC, scalable algorithms, and climate modeling, with innovations receiving the ACM Gordon Bell Prize for Climate Modelling.
<> integrated photonics (5)

Naiqin Bu

KAUST-CEMSE-ECE-IPL-Nikita-Kondratyev

Nikita Kondratyev

Mikhail Mishevskii

Mikhail received the B.S. degree in applied mathematics and physics from Novosibirsk State, Novosibirsk, Russia and received a master's degree with honors from the Skolkovo Institute of Science and Technology (Skoltech). His research interests include: nonlinear optics, integrated photonics, ultrafast lasers, frequency comb generation. During his time at Skoltech participated in the Skoltech Translational Research and Innovation Program industrial project to create a pulsed submicron laser for pumping a single-photon quantum light source. Mikhail awarded with Scholarship of the President of

Aleksandr Movsisian

Aleksandr received his bachelor’s degree in 2023 in Physics from Moscow State University (MSU, ranked first in Russia) and completed a master’s degree in Physics with honors at the same institution. He has over two years of research experience in quantum optics, optomechanics, and quantum measurement theory as part of the LIGO group at MSU. His work has focused on squeezed states of light, measurement topologies, and methods to overcome the Standard Quantum Limit, resulting in two first-author publications in JOSA B and Optics Letters. Aleksandr also gained hands-on experimental experience at

Aram Mkrtchyan

Postdoctoral Research Fellow, Electrical and Computer Engineering
<> ISAC (5)
kaust-cemse-ece-ccsl-changhao-he

Changhao He

kaust-cemse-ece-ccsl-yousef-awad

Yousef Awad

kaust-cemse-ece-ccsl-bumin-kagan-yildirim

Bumin Kagan Yildirim

Bang Huang

Postdoctoral Research Fellow, Electrical and Computer Engineering
Bang Huang works as a postdoctoral fellow at the Computer Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), under the supervision of Prof. Mohamed-Slim Alouini in the Communication Theory Lab (CTL). Education and Early Career Bang Huang received the M.S. degree (with honors) in electrical engineering and Ph.D degree in information and communication engineering from the School of Information and Communication Engineering (SICE), University of Electronic Science and Technology of China (UESTC), Chengdu, China, in

Xiaowei Pang

Postdoctoral Research Fellow, Electrical and Computer Engineering
Xiaowei Pang is currently a Postdoctoral Research Fellow at the Computer Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), working with Professor Mohamed-Slim Alouini in the Communication Theory Lab (CTL). Education and Early Career Xiaowei Pang received her B.S. degree in Telecommunication Engineering from Northwestern Polytechnical University, Xi'an, China, in 2018, and her Ph.D. degree in Information and Communication Engineering from Dalian University of Technology, Dalian, China, in 2024. From 2021 to 2022
<> optimization (5)
Chengjie zhao

Chengjie Zhao

Visiting Researcher, Information Science Lab
Visiting Student, King Abdullah University of Science and Technology

Chaabane Mankai

Surrounded by bright minds and groundbreaking research, KAUST is a great place to learn and grow.

Ahmed Youssef Ragab Radwan

Visiting Student (former), Information Science Lab
Visiting student at the Information Science Lab, in the Electrical Engineering Department, CEMSE, King Abdullah University of Science and Technology (KAUST)

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.

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.
<> Parallel and Distributed Computing (5)

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

-

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)

-

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

PhD Defense of Tariq AlTurkestani

1 min read ·
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

Tariq receives his best paper award at EuroPar'2020

1 min read ·
Maximizing I/O Bandwidth for Out-of-Core HPC Applications on Heterogeneous Large-Scale Systems Best Paper Presentation by Tariq Alturkestani PhD Student, Computer Science, KAUST Thursday, Aug 27, 3:30pm - 4:00pm (AST) https://zoom.us/j/99947879910 Tariq will present his best paper at EuroPar'2020 at the virtual EuroPar'2020 conference in Warsaw, Poland. The reverse time migration (RTM) method is critical in seismic imaging for oil and gas industries. He demonstrates the effectiveness of his Multilayer Buffer System (MLBS) framework on Shaheen-2 (using 2048 compute nodes) and Summit

Stefano Zampini

As a computational mathematician and software engineer, Stefano Zampini's work lies at the intersection of numerical analysis, predictive simulations, and high-performance computing, with recent forays into machine learning.
<> seismic imaging (5)

Superior seismic imaging for better drilling

1 min read ·
Software could transform underground imaging of fossil fuel reserves by providing unprecedented detail in record time.

Code of collaboration

1 min read ·
David Keyes's and Matteo Ravasi's cross-disciplinary project results in improved efficiency for seismic processing, with promising applications for the energy industry.

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

1 min read ·
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

Long Qu

Dr. Long Qu is a Research Scientist at the Extreme Computing Research Center at KAUST, working with Prof. David E. Keyes and Dr. Hatem Ltaief. Research Interests Long Qu's research interests include seismic imaging and high performance computing on heterogeneous hardware architectures.

Kadir Akbudak

Dr. Kadir Akbudak is a Consultant at Extreme Computing Research Center at KAUST, working with Professor David E. Keyes and Dr. Hatem Ltaief. Research Interests Kadir Akbudak's research interests include Combinatorial scientific computing, Graph and hypergraph partitioning, Locality-aware partitioning and scheduling, High performance kernels for sparse computations, Vectorization for irregular applications, Iterative numerical methods and Parallel numerical algorithms. Education Profile Ph.D., Computer Engineering, Bilkent University, 2015. M.S., Computer Engineering, Bilkent University, 2009
<> computational science (4) <> computational science and engineering (4)

ECRC contributions to SIAM CSE21

1 min read ·
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

The Arab World Prepares the Exascale Workforce

1 min read ·
The April 2021 Communications of the ACM special section on computing in the Arab world features an article by ECRC Director and KAUST founding dean David Keyes on preparing the exascale workforce. Keyes muses on the lure of hands-on opportunities to resolve today’s application-architecture tension with innovative algorithms for recruiting students, and he follows the placement of a dozen recent ECRC doctoral students from the MENA region in the US exascale computing project and Saudi industry. For them, “graduation” means an upgrade to a more powerful computer :-). Several have also seen

Stefano Zampini

As a computational mathematician and software engineer, Stefano Zampini's work lies at the intersection of numerical analysis, predictive simulations, and high-performance computing, with recent forays into machine learning.

David Keyes

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.
<> Mixed Precisions (4)

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

-

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)

-

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

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
<> Performance optimization (4)

Our Masked Guest Speakers Series

1 min read ·
Every week, we have a masked guest speaker opening our HiCMA weekly meeting by giving a remote talk on broad topics related to numerical linear algebra, high performance computing, programming models and performance optimizations. Our motto is fun and science!

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

1 min read ·
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

Rabab Alomairy

KAUST alumna Dr. Rabab Alomairy advances high-performance computing and AI research as a postdoctoral fellow at MIT.

Hatem Ltaief

Principal Research Scientist, Applied Mathematics and Computational Science
Dr. Hatem Ltaief is a Principal Research Scientist at KAUST. He works on mixed-precision algorithms and performance optimizations to help HPC scientific applications address the exascale challenges. His innovations have been recognized with the ACM Gordon Bell Prize (shared) for Climate Modeling in 2024.
<> Photonics and optoelectronics (4)
Mohammed Alotaibi

Mohammed Obidallah Alotaibi

Ph.D. Student, Photonics Laboratory
I am Mohammed Obidallah Alotaibi, joining the KAUST Photonics Lab. I hold an M.S. in Electrical Engineering from the University of Central Florida and a B.S. from Umm Al-Qura University. Previously, I served as an Instrument Engineer at Aramco and currently lecture at Taibah University. I am passionate about advancing photonic technologies in energy and sustainability applications, and I look forward to contributing to the lab’s research in optoelectronics and integrated photonic systems. Previous Work Experience: Instrument Engineer, Saudi Aramco (2010–2012) Teaching Assistant & Lecturer

Yan Wang

Ph.D. Student, Photonics Laboratory
M.S./Ph.D. in Electrical Engineering at King Abdullah University of Science and Technology (KAUST), Saudi Arabia, Aug. 2024- present BEng. in Communication Engineering at University of Electronic Science and Technology of China (UESTC), Chengdu, China, Sept. 2019 - Jun. 2024​
Jiahoa Wei profile picture

Jiahao Wei

M.S. Student, Photonics Laboratory
Education Jan 2025 - present, M.S./Ph.D. in Electrical Engineering at KAUST, Thuwal, Saudi Arabia. Sep 2020 - Jun 2024, B.S. in Optoelectronic Information Science and Engineering at Southern University of Science and Technology (SUSTech), Shenzhen, China.
Zinan Xiao profile picture

Zinan Xiao

Ph.D. Student, Photonics Laboratory
Education Aug 2024 - present, Ph.D. in Electrical Engineering at KAUST, Thuwal, Saudi Arabia. Oct 2020 - Oct 2021, M.S. in Optics and photonics at Imperial College London, London, UK. Sep 2016 - Jun 2020, B.S. in Optoelectronic information engineering at Chongqing University, Chongqing, China.
<> Python (4) <> data analysis (3) <> dense linear algebra (3) <> embedded systems (3) <> haps (3)

Bang Huang

Postdoctoral Research Fellow, Electrical and Computer Engineering
Bang Huang works as a postdoctoral fellow at the Computer Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), under the supervision of Prof. Mohamed-Slim Alouini in the Communication Theory Lab (CTL). Education and Early Career Bang Huang received the M.S. degree (with honors) in electrical engineering and Ph.D degree in information and communication engineering from the School of Information and Communication Engineering (SICE), University of Electronic Science and Technology of China (UESTC), Chengdu, China, in

Xiaowei Pang

Postdoctoral Research Fellow, Electrical and Computer Engineering
Xiaowei Pang is currently a Postdoctoral Research Fellow at the Computer Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), working with Professor Mohamed-Slim Alouini in the Communication Theory Lab (CTL). Education and Early Career Xiaowei Pang received her B.S. degree in Telecommunication Engineering from Northwestern Polytechnical University, Xi'an, China, in 2018, and her Ph.D. degree in Information and Communication Engineering from Dalian University of Technology, Dalian, China, in 2024. From 2021 to 2022
H

Hussein Al-Shatri

I chose KAUST because of its reputation for excellence in research and its recent emphasis on applied research. With my extensive background in both academic research and industrial development, I am excited to contribute my experience and ambition. My goal is to foster new ideas and develop innovative prototypes in the field of wireless communications, which will undoubtedly enhance people's lives.
<> LiDAR (3) <> Linux (3) <> MATLAB (3) <> Nonlinear Optics (3) <> parallel computing (3)

New cost-effective GPUs solver redesigns the computational game

1 min read ·
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.

KAUST scientists win prestigious Gauss Award for supercomputing excellence

1 min read ·
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.

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)
<> parallel numerical algorithms (3)

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

Hatem Ltaief

Principal Research Scientist, Applied Mathematics and Computational Science
Dr. Hatem Ltaief is a Principal Research Scientist at KAUST. He works on mixed-precision algorithms and performance optimizations to help HPC scientific applications address the exascale challenges. His innovations have been recognized with the ACM Gordon Bell Prize (shared) for Climate Modeling in 2024.
<> Reinforcement Learning (3) <> scientific computing (3)
Georgios Grekas

Georgios Grekas

Postdoctoral Research Fellow, Applied Mathematics and Computational Science

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

Tariq receives his best paper award at EuroPar'2020

1 min read ·
Maximizing I/O Bandwidth for Out-of-Core HPC Applications on Heterogeneous Large-Scale Systems Best Paper Presentation by Tariq Alturkestani PhD Student, Computer Science, KAUST Thursday, Aug 27, 3:30pm - 4:00pm (AST) https://zoom.us/j/99947879910 Tariq will present his best paper at EuroPar'2020 at the virtual EuroPar'2020 conference in Warsaw, Poland. The reverse time migration (RTM) method is critical in seismic imaging for oil and gas industries. He demonstrates the effectiveness of his Multilayer Buffer System (MLBS) framework on Shaheen-2 (using 2048 compute nodes) and Summit
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