this special issue is dedicated to examining the rapidly evolving fields of artificial intelligence, mathematical modeling, and optimization, with particular emphasis on their growing importance in computational scien...
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this special issue is dedicated to examining the rapidly evolving fields of artificial intelligence, mathematical modeling, and optimization, with particular emphasis on their growing importance in computational science. It features the most notable papers from the "Mathematical Modeling and Problem Solving" workshop at PDPTA'24, the 30thinternationalconference on parallel and distributed Processing Techniques and applications. the issue showcases pioneering research in areas such as natural language processing, system optimization, and high-performance computing. the nine selected studies include novel AI-driven methods for chemical compound generation, historical text recognition, and music recommendation, along with advancements in hardware optimization through reconfigurable accelerators and vector register sharing. Additionally, evolutionary and hyper-heuristic algorithms are explored for sophisticated problem-solving in engineering design, and innovative techniques are introduced for high-speed numerical methods in large-scale systems. Collectively, these contributions demonstrate the significance of AI, supercomputing, and advanced algorithms in driving the next generation of scientific discovery.
the proceedings contain 28 papers. the topics discussed include: performance and usability implications of multiplatform and WebAssembly containers;operations patterns for hybrid quantum applications;optimization of c...
ISBN:
(纸本)9789897587474
the proceedings contain 28 papers. the topics discussed include: performance and usability implications of multiplatform and WebAssembly containers;operations patterns for hybrid quantum applications;optimization of cloud-native application execution over the edge cloud continuum enabled by DVFS;energy-aware node selection for cloud-based parallel workloads with machine learning and infrastructure as code;security-aware allocation of replicated data in distributed storage systems;performance analysis of mdx ii: a next-generation cloud platform for cross-disciplinary data science research;data orchestration platform for AI workflows execution across computing continuum;framework for decentralized data strategies in virtual banking: navigating scalability, innovation, and regulatory challenges in thailand;and anomaly detection for partially observable container systems based on architecture profiling.
the increasing demand for real-time data analysis in Internet of things (IoT) ecosystems has created several challenges, particularly in environments where resources are limited, and minimizing data processing latency...
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this paper examines how co-locating multiple VMs on a single physical server with shared storage impacts I/O performance, specifically focusing on latency of I/O operations, and the overall throughput. We introduce a ...
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the growing popularity of data-intensive applications in cloud computing necessitates a cost-effective approach to harnessing distributed processing capabilities. However, the wide variety of instance types and config...
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Federated Learning (FL) is vulnerable to backdoor attacks through data poisoning if the data is not scrutinized, as malicious participants can inject backdoor triggers in normal samples, leading to poisoned updates. D...
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Graphics Processing Units (GPUs) are widely used as powerful hardware accelerators for data-intensive tasks. However, their efficacy can be hindered by constraints in device memory and data transfer speeds via the PCI...
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the rapid growth of cloud computing has brought new challenges in parallel Batch Machine Scheduling (PBMS), particularly when incorporating malleability and rejection constraints. this has led to the parallel Batch Ma...
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the proceedings contain 63 papers. the topics discussed include: looking for a definition of dynamic distributed system;adaptive workflow nets for grid computing;a stochastic semantics for BioAmbients;a categorical ob...
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ISBN:
(纸本)9783540739395
the proceedings contain 63 papers. the topics discussed include: looking for a definition of dynamic distributed system;adaptive workflow nets for grid computing;a stochastic semantics for BioAmbients;a categorical observation of timed testing equivalence;from unreliable objects to reliable objects: the case of atomic registers and consensus;towards a computing model for open distributed systems;enhancing online computer games for open distributed systems;enhancing online computer games for grids;optimized parallel approach for 3D modelling of forest fire behaviour;a high-level toolkit for development of distributed scientific applications;orthogonal organized finite state machine application to sensor acquired information;parallel broadband finite element time domain algorithm implemented to dispersive electromagnetic problem;and strategies for development of a parallel program for protoplanetary disc simulation.
As modern industrial chains grow increasingly complex and time-sensitive, traditional transportation planning methods face efficiency bottlenecks. To address this, we propose a parallelization method based on Sparse M...
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