2 citations · 5 across the 15 of their papers we have counts for
16 papers
Fisher Scoring for Exact Matérn Covariance Estimation through Stable Smoothness Optimization
Yiping Hong, Sameh Abdulah, Marc G. Genton +1
Gaussian Random Fields (GRFs) with Matérn covariance functions have emerged as a powerful framework for modeling spatial processes due to their flexibility in capturing different f…
Scalable Asynchronous Federated Modeling for Spatial Data
Jianwei Shi, Sameh Abdulah, Ying Sun +1
Spatial data are central to applications such as environmental monitoring and urban planning, but are often distributed across devices where privacy and communication constraints l…
High-Performance Statistical Computing (HPSC): Challenges, Opportunities, and Future Directions
Sameh Abdulah, Mary Lai O. Salvana, Ying Sun +2
We recognize the emergence of a statistical computing community focused on working with large computing platforms and producing software and applications that exemplify high-perfor…
RCOMPSs: A Scalable Runtime System for R Code Execution on Manycore Systems
Xiran Zhang, Javier Conejero, Sameh Abdulah +5
R has become a cornerstone of scientific and statistical computing due to its extensive package ecosystem, expressive syntax, and strong support for reproducible analysis. However,…
Scaled Block Vecchia Approximation for High-Dimensional Gaussian Process Emulation on GPUs
Qilong Pan, Sameh Abdulah, Mustafa Abduljabbar +8
Emulating computationally intensive scientific simulations is crucial for enabling uncertainty quantification, optimization, and informed decision-making at scale. Gaussian Process…
Decentralized Inference for Spatial Data Using Low-Rank Models
Jianwei Shi, Sameh Abdulah, Ying Sun +1
Advancements in information technology have enabled the creation of massive spatial datasets, driving the need for scalable and efficient computational methodologies. While offerin…
GPU-Accelerated Modified Bessel Function of the Second Kind for Gaussian Processes
Zipei Geng, Sameh Abdulah, Ying Sun +3
Modified Bessel functions of the second kind are widely used in physics, engineering, spatial statistics, and machine learning. Since contemporary scientific applications, includin…
Block Vecchia Approximation for Scalable and Efficient Gaussian Process Computations
Qilong Pan, Sameh Abdulah, Marc G. Genton +1
Gaussian Processes (GPs) are vital for modeling and predicting irregularly-spaced, large geospatial datasets. However, their computations often pose significant challenges in large…
Boosting Earth System Model Outputs And Saving PetaBytes in their Storage Using Exascale Climate Emulators
Sameh Abdulah, Allison H. Baker, George Bosilca +9
We present the design and scalable implementation of an exascale climate emulator for addressing the escalating computational and storage requirements of high-resolution Earth Syst…
MPCR: Multi-Precision Computations Package in R
Mary Lai O. Salvana, Sameh Abdulah, Minwoo Kim +3
In the early days of computing, severe memory constraints made it necessary to use lower floating-point precision. As hardware capabilities have advanced, modern systems, particula…
Parallel Approximations for High-Dimensional Multivariate Normal Probability Computation in Confidence Region Detection Applications
Xiran Zhang, Sameh Abdulah, Jian Cao +4
Addressing the statistical challenge of computing the multivariate normal (MVN) probability in high dimensions holds significant potential for enhancing various applications. One c…
GPU-Accelerated Vecchia Approximations of Gaussian Processes for Geospatial Data using Batched Matrix Computations
Qilong Pan, Sameh Abdulah, Marc G. Genton +3
Gaussian processes (GPs) are commonly used for geospatial analysis, but they suffer from high computational complexity when dealing with massive data. For instance, the log-likelih…
On the Impact of Spatial Covariance Matrix Ordering on Tile Low-Rank Estimation of Matérn Parameters
Sihan Chen, Sameh Abdulah, Ying Sun +1
Spatial statistical modeling and prediction involve generating and manipulating an n*n symmetric positive definite covariance matrix, where n denotes the number of spatial location…
Visualization and Assessment of Copula Symmetry
Cristian F. Jimenez-Varon, Hao Lee, Marc G. Genton +1
Visualization and assessment of copula structures are crucial for accurately understanding and modeling the dependencies in multivariate data analysis. In this paper, we introduce…
Portability and Scalability Evaluation of Large-Scale Statistical Modeling and Prediction Software through HPC-Ready Containers
Sameh Abdulah, Jorge Ejarque, Omar Marzouk +5
HPC-based applications often have complex workflows with many software dependencies that hinder their portability on contemporary HPC architectures. In addition, these applications…
Efficient Large-scale Nonstationary Spatial Covariance Function Estimation Using Convolutional Neural Networks
Pratik Nag, Yiping Hong, Sameh Abdulah +3
Spatial processes observed in various fields, such as climate and environmental science, often occur on a large scale and demonstrate spatial nonstationarity. Fitting a Gaussian pr…