Related papers: Usability Evaluation of Cloud for HPC Applications
Cloud resource allocation has emerged as a major challenge in modern computing environments, with organizations struggling to manage complex, dynamic workloads while optimizing performance and cost efficiency. Traditional heuristic…
Output-intensive scientific applications are highly sensitive to low storage throughput. While existing scientific application stacks are optimized for traditional High-Performance Computing (HPC) environments with high remote storage and…
Exascale computing will get mankind closer to solving important social, scientific and engineering problems. Due to high prototyping costs, High Performance Computing (HPC) system architects make use of simulation models for design space…
Cloud Computing offers virtualized computing, storage, and networking resources, over the Internet, to organizations and individual users in a completely dynamic way. These cloud resources are cheaper, easier to manage, and more elastic…
High-performance computing platforms such as supercomputers have traditionally been designed to meet the compute demands of scientific applications. Consequently, they have been architected as producers and not consumers of data. The Apache…
Modern HPC systems are built with innovative system architectures and novel programming models to further push the speed limit of computing. The increased complexity poses challenges for performance portability and performance evaluation.…
The pace of improvement in the performance of conventional computer hardware has slowed significantly during the past decade, largely as a consequence of reaching the physical limits of manufacturing processes. To offset this slowdown, new…
High Performance Computing (HPC) has evolved over the past decades into increasingly complex and powerful systems. Current HPC systems consume several MWs of power, enough to power small towns, and are in fact soon approaching the limits of…
The recent years witness a trend of applying large-scale distributed deep learning in both business and scientific computing areas, whose goal is to speed up the training time to achieve a state-of-the-art quality. The HPC community feels a…
The increase of existing computational capabilities has made simulation emerge as a third discipline of Science, lying midway between experimental and purely theoretical branches [1, 2]. Simulation enables the evaluation of quantities which…
Cloud computing has become the backbone of the computing industry and offers subscription-based on-demand services. Through virtualization, which produces a virtual instance of a computer system running in an abstracted hardware layer, it…
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…
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…
HPC-based applications often have complex workflows with many software dependencies that hinder their portability on contemporary HPC architectures. In addition, these applications often require extraordinary efforts to deploy and execute…
Artificial Intelligence for scientific applications increasingly requires training large models on data that cannot be centralized due to privacy constraints, data sovereignty, or the sheer volume of data generated. Federated learning (FL)…
The scale of scientific High Performance Computing (HPC) and High Throughput Computing (HTC) has increased significantly in recent years, and is becoming sensitive to total energy use and cost. Energy-efficiency has thus become an important…
New challenges in Astronomy and Astrophysics (AA) are urging the need for a large number of exceptionally computationally intensive simulations. "Exascale" (and beyond) computational facilities are mandatory to address the size of…
Cloud computing provisions computer resources at a cost-effective way based on demand. Therefore it has become a viable solution for big data analytics and artificial intelligence which have been widely adopted in various domain science.…
Data-intensive container-based cloud applications have become popular with the increased use cases in the Internet of Things domain. Challenges arise when engineering such applications to meet quality requirements, both classical ones like…
Cloud computing with its three key facets (i.e., IaaS, PaaS, and SaaS) and its inherent advantages (e.g., elasticity and scalability) still faces several challenges. The distance between the cloud and the end devices might be an issue for…