The HaMMon project is the outcome of an industrial partnership that includes many Italian research institutions and private companies. It is led by UnipolSai and Leitha, and funded by the ICSC, the Italian National Re...
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ISBN:
(数字)9798331524937
ISBN:
(纸本)9798331524944
The HaMMon project is the outcome of an industrial partnership that includes many Italian research institutions and private companies. It is led by UnipolSai and Leitha, and funded by the ICSC, the Italian National Research Center for High Performance computing, Big Data and Quantum *** ambition of HaMMon is to build a flexible and scalable platform to analyze the hydrogeological and atmospheric balance of the Italian territory. The project aims to expand the current knowledge in hazard mapping, monitoring, and forecasting from an industrial perspective by leveraging innovative technologies and the interdisciplinary activities carried out by the *** this work, we present the cloud-HPC infrastructure deployed in the High-Performance computing for Artificial Intelligence (HPC4AI) green data center of the University of Turin which supports the testing and development of HaMMon’s applications and services. We describe the current activities and preliminary results related to the integration of Photogrammetry techniques, Data Visualization and Artificial Intelligence technologies, applied on aerial images, to assess extreme natural events and evaluate their impact on risk-exposed assets.
The proceedings contain 147 papers from the Proceedings of the 16th IASTED internationalconference on parallel and distributedcomputing and Systems. The topics discussed include: a grid simulation infrastructure sup...
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The proceedings contain 147 papers from the Proceedings of the 16th IASTED internationalconference on parallel and distributedcomputing and Systems. The topics discussed include: a grid simulation infrastructure supporting advance reservation;auction-based resource allocation protocols in grids;effectiveness of grid configurations on application performance;a constant time shortest-path routing algorithm for pyramid networks;wormhole routers for network-on-chop;communication optimization on broadcast-based clusters;a localization algorithm extension for the evolvable sensor network;and migration algorithms for automated load balancing.
Proof of Data Possession is a technique for ensuring the integrity of data stored in cloud storage. However, most audit schemes assume only one role for data owners, which is not suitable for complex Smart Healthcare ...
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Agent-Based Modeling and Simulation (ABMS) has been increasingly applied in various research fields, thanks to the capability of these models to describe fine-grained realworld behavior and to the ease of interpretati...
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ISBN:
(数字)9798331524937
ISBN:
(纸本)9798331524944
Agent-Based Modeling and Simulation (ABMS) has been increasingly applied in various research fields, thanks to the capability of these models to describe fine-grained realworld behavior and to the ease of interpretation by domain experts. However, such models lack a formal definition and well-defined semantics that are common to the different tools supporting ABMS. This may occasionally lead to greater complexity in interpreting the results with respect to other modeling approaches. To address this issue, an ABM semantics that adopts a continuous-time approach and a next-event time advance simulation algorithm has been formally defined and presented. Such an approach may lead to high computation times as it requires recalculations of activity rates for all the agents after each event. In this preliminary study, we exploit the FLAME GPU framework to evaluate the benefits that GPU computing may bring to the performance of our simulation algorithm.
GNU parallel is a versatile and powerful tool for process parallelizatlon widely used in scientific computing. This paper demonstrates its effective application in high-performance computing (HPC) environments, partic...
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ISBN:
(纸本)9798350355543
GNU parallel is a versatile and powerful tool for process parallelizatlon widely used in scientific computing. This paper demonstrates its effective application in high-performance computing (HPC) environments, particularly focusing on its scalability and efficiency in executing large-scale high-throughput high-performance computing (HT-HPC) workflows. Through real-world examples, we highlight GNU parallel's performance across various HPC workloads, including GPU computing, container-based workloads, and node-local NVMe storage. Our results on two leading supercomputers, OLCF's Frontier and NERSC's Perlmutter, showcase GNU parallel's rapid process dispatching ability and its capacity to maintain low overhead even at extreme scales. We explore GNU parallel's application in massive parallel file transfers using a scheduled Data Transfer Node (DTN) cluster, emphasizing its broad utility in diverse scientific workflows. Beyond its direct application as a viable workflow manager, GNU parallel can be employed in conjunction with other workflow systems as a "last-mile" parallelizing driver and as a quick prototyping tool to design and extract parallel profiles from application executions. We then argue that the potential for GNU parallel to transform workflow management at extreme scales is substantial, paving the way for more efficient and effective scientific discoveries.
Fortran compilers that provide support for Fortran's native parallel features often do so with a runtime library that depends on details of both the compiler implementation and the communication library, while oth...
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ISBN:
(纸本)9798350355543
Fortran compilers that provide support for Fortran's native parallel features often do so with a runtime library that depends on details of both the compiler implementation and the communication library, while others provide limited or no support at all. This paper introduces a new generalized interface that is both compiler- and runtime-library-agnostic, providing flexibility while fully supporting all of Fortran's parallel features. The parallel Runtime Interface for Fortran (PRIF) was developed to be portable across shared- and distributed-memory systems, with varying operating systems, toolchains and architectures. It achieves this by defining a set of Fortran procedures corresponding to each of the parallel features defined in the Fortran standard that may be invoked by a Fortran compiler and implemented by a runtime library. PRIF aims to be used as the solution for LLVM Flang to provide parallel Fortran support. This paper also briefly describes our PRIF prototype implementation: Caffeine.
The authors present and evaluate an unplugged activity to introduce parallelcomputing concepts to undergraduate students. Students in five CS classrooms used a deck of playing cards in small groups to consider how pa...
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ISBN:
(纸本)9798350355543
The authors present and evaluate an unplugged activity to introduce parallelcomputing concepts to undergraduate students. Students in five CS classrooms used a deck of playing cards in small groups to consider how parallelization can improve performance and how improvement decreases with increased parallelization. Before and after the activity, students took a short survey about their solution and their ideas about parallelism. The authors carried out this activity in seven courses at five institutions in the 2023-2024 academic year. The results showed that students had an increased appreciation for parallelization and this type of activity.
Celestial objects are known to be change in brightness over time, driven by a diverse combination of physical processes, whose time scales range from sub-milliseconds to billions of years. Stingray is an open-source P...
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ISBN:
(数字)9798331524937
ISBN:
(纸本)9798331524944
Celestial objects are known to be change in brightness over time, driven by a diverse combination of physical processes, whose time scales range from sub-milliseconds to billions of years. Stingray is an open-source Python package that brings advanced time series analysis techniques to the astronomical community, with a focus on high-energy astrophysics, but built on top of general-purpose classes and methods that are designed to be easily adapted and extended to other use cases. We describe the work being done to adapt Stingray to the analysis of large data archives. In particular, we measure the performance and scalability of Stingray and use parallelcomputing to speed up selected parts of the code.
Widespread deployment of distributed renewable energy sources fosters the research and development of peer-topeer (P2P) energy trading systems. Despite the benefits this energy-sharing paradigm can bring to the stakeh...
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ISBN:
(数字)9798331542139
ISBN:
(纸本)9798331542146
Widespread deployment of distributed renewable energy sources fosters the research and development of peer-topeer (P2P) energy trading systems. Despite the benefits this energy-sharing paradigm can bring to the stakeholders in modern energy systems, how to effectively facilitate energy trading among a large number of energy prosumers (producers-and-consumers) remains a non-trivial challenge. This paper proposes a new P2P energy trading system to support energy trading among prosumers located in geographically distributed microgrids. Backboned by a clustering mechanism that dynamically organizes the microgrids into multiple coalitions, the system can enable energy trading within a microgrid and among different microgrids, making it scalable to cater for the energy trading needs of widearea prosumers. Numerical simulation is conducted on an IEEE 33-bus benchmark distribution system to validate the proposed method.
This study proposes an advanced optimization methodology for managing a grid-connected residential hybrid thermal and electrical energy system, incorporating a combined heat and power (CHP) fuel cell and a battery-bas...
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ISBN:
(数字)9798350356236
ISBN:
(纸本)9798350356243
This study proposes an advanced optimization methodology for managing a grid-connected residential hybrid thermal and electrical energy system, incorporating a combined heat and power (CHP) fuel cell and a battery-based energy storage system (ESS). A predictive scheduling framework is designed to optimize the operational plan for distributed energy resources (DER) over a 24-hour period. The main objective is to reduce the operational expenses of a smart home by strategically allocating resources while considering dynamic electricity tariffs and the efficiency of the ESS. To achieve this, an enhanced Adaptive Gravitational Search Algorithm (AGSA) is employed. The research also includes a comparative evaluation of the AGSA against conventional Gravitational Search Algorithm (GSA) and Harmony Search Algorithm (HSA) methods. This comparison underscores the AGSA's superior performance in optimizing residential energy systems. The findings offer significant insights into the application of optimization algorithms for improving cost-efficiency and energy management in modern smart homes.
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