Related papers: High Performance Computing for Geospatial Applicat…
The evolution of High-Performance Computing (HPC) platforms enables the design and execution of progressively larger and more complex workflow applications in these systems. The complexity comes not only from the number of elements that…
This article describes a geometric partitioning software that can be used for quick computation of data partitions on many-core HPC machines. It is most suited for dynamic applications with load distributions that vary with time.…
Big data has now become a strong focus of global interest that is increasingly attracting the attention of academia, industry, government and other organizations. Big data can be situated in the disciplinary area of traditional geospatial…
Cloud computing recently developed into a viable alternative to on-premises systems for executing high-performance computing (HPC) applications. With the emergence of new vendors and hardware options, there is now a growing need to…
Power efficiency is critical in high performance computing (HPC) systems. To achieve high power efficiency on application level, it is vital importance to efficiently distribute power used by application checkpoints. In this study, we…
The growing energy demands of HPC systems have made energy efficiency a critical concern for system developers and operators. However, HPC users are generally less aware of how these energy concerns influence the design, deployment, and…
With the rise of electronic data, particularly Earth observation data, data-based geospatial modelling using machine learning (ML) has gained popularity in environmental research. Accurate geospatial predictions are vital for domain…
High performance computing (HPC) has driven collaborative science discovery for decades. Exascale computing platforms, currently in the design stage, will be deployed around 2022. The next generation of supercomputers is expected to utilize…
Over the past several years, The George Washington University has recruited a significant number of researchers in a wide variety of domains requiring the availability of advanced computational resources. We discuss the challenges and…
High intensive computation applications can usually take days to months to finish an execution. During this time, it is common to have variations of the available resources when considering that such hardware is usually shared among a…
Very High Resolution satellite and aerial imagery are used to monitor and conduct large scale surveys of ecological systems. Convolutional Neural Networks have successfully been employed to analyze such imagery to detect large animals and…
The world of computing is in rapid transition, now dominated by a world of smartphones and cloud services, with profound implications for the future of advanced scientific computing. Simply put, high-performance computing (HPC) is at an…
With the upcoming generation of telescopes, cluster scale strong gravitational lenses will act as an increasingly relevant probe of cosmology and dark matter. The better resolved data produced by current and future facilities requires…
The purpose of the present review is to discuss the role of Soft Computing techniques in understanding the complexity associated with atmospheric phenomena and thus developing predictive models. Problems in atmospheric data analysis are…
The computational power of High-Performance Computing (HPC) systems is constantly increasing, however, their input/output (IO) performance grows relatively slowly, and their storage capacity is also limited. This unbalance presents…
We conducted a systematic survey of emerging quantum-HPC platforms, which integrate quantum computers and High-Performance Computing (HPC) systems through co-location. Currently, it remains unclear whether such platforms provide tangible…
Applications in High-Performance Computing (HPC) environments face challenges due to increasing complexity. Among them, the increasing usage of sparse data pushes the limits of data structures and programming models and hampers the…
The accelerating technological landscape and drive towards net-zero emission made the power system grow in scale and complexity. Serial computational approaches for grid planning and operation struggle to execute necessary calculations…
We recognize the emergence of a statistical computing community focused on working with large computing platforms and producing software and applications that exemplify high-performance statistical computing (HPSC). The statistical…
Modeling and inferring spatial relationships and predicting missing values of environmental data are some of the main tasks of geospatial statisticians. These routine tasks are accomplished using multivariate geospatial models and the…