About George Turkiyyah George Turkiyyah Research Professor, Applied Mathematics and Computational Science numerical simulations High Performance Computing scientific computing geometric modeling Neural Network training algorithms large languaje models 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. Articles Related News September 2024 Return of Socrates: KAUST Developing AI Education for Personalized Learning 1 min read · Thu, Sep 12 2024 News Clip News KAUST is advancing AI-driven personalized learning platforms to transform STEM education in Saudi Arabia, aligning with Vision 2030’s goals by creating an intelligent tutoring system that enhances critical thinking and supports students and teachers, particularly in underserved communities, while addressing the Kingdom's significant demand for qualified STEM educators. February 2021 ECRC contributions to SIAM CSE21 4 min read · Sat, Feb 27 2021 News research conference HPC computational science and engineering 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 September 2020 H2Opus: a Performance-Oriented Library for Hierarchical Matrices 1 min read · Wed, Sep 16 2020 News GPU Computing High Performance Computing numerical linear algebra 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 February 2018 Pulling rank on spatial statistics 1 min read · Sun, Feb 18 2018 News High Performance Computing statistics A technique that uses the power of computing could solve statistical problems cheaper and faster than current methods.
Return of Socrates: KAUST Developing AI Education for Personalized Learning 1 min read · Thu, Sep 12 2024 News Clip News KAUST is advancing AI-driven personalized learning platforms to transform STEM education in Saudi Arabia, aligning with Vision 2030’s goals by creating an intelligent tutoring system that enhances critical thinking and supports students and teachers, particularly in underserved communities, while addressing the Kingdom's significant demand for qualified STEM educators.
ECRC contributions to SIAM CSE21 4 min read · Sat, Feb 27 2021 News research conference HPC computational science and engineering 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
H2Opus: a Performance-Oriented Library for Hierarchical Matrices 1 min read · Wed, Sep 16 2020 News GPU Computing High Performance Computing numerical linear algebra 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
Pulling rank on spatial statistics 1 min read · Sun, Feb 18 2018 News High Performance Computing statistics A technique that uses the power of computing could solve statistical problems cheaper and faster than current methods.
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