Forthcoming Articles

International Journal of High Performance Systems Architecture

International Journal of High Performance Systems Architecture (IJHPSA)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of High Performance Systems Architecture (2 papers in press)

Regular Issues

  • Dynamic Spatiotemporal Collaborative Resource Adaptation for Heterogeneous Computing in Smart Water Management   Order a copy of this article
    by Kun Ruan, Lei Cao, Peng Xu, Xiaogang Wang 
    Abstract: Smart water management systems encounter performance bottlenecks due to strongly coupled physical models and heterogeneous computing demands. To address this, we propose GGRU-MGA3C, a dynamic resource adaptation framework for cloud-edge-terminal environments. This method integrates graph convolutional networks (GCNs) and gated recurrent units (GRUs) to model high-dimensional spatiotemporal states. It employs a two-stage mechanism: offline distributed training using momentum stochastic gradient descent (MSGD) to ensure convergence stability, and online fine-tuning via asynchronous advantage actor-critic (A3C) for millisecond-level scheduling. Experimental results demonstrate an average cumulative return increase of 6.2%, a reduction in task completion time to 3.62 s, and an improved load balance index (LBI) of 0.133. In real-world flood forecasting scenarios, the system maintains decision response times within 1.15 s with a throughput of 152 tasks/min, significantly enhancing real-time service stability.
    Keywords: Dynamic adaptation of heterogeneous resources; DRL; DisRL; Real-time scheduling.
    DOI: 10.1504/IJHPSA.2026.10079032
     
  • High-performance computing and dynamic correction technology of BIM model for construction surveying of large bridges   Order a copy of this article
    by Yu Que, Ke Jiang, Jing Yuan 
    Abstract: In the construction of large bridges, real-time detection and precise control of construction errors are limited due to the serial processing of a large amount of multi-source measurement data and the long-term static and fixed state of building information modelling (BIM) models. Therefore, this paper constructs an intelligent construction control method system with closed-loop linkage of "measurement calculation model control". The fusion framework first establishes a unified state vector using an engineering coordinate system and synchronized timestamps. Global navigation satellite system (GNSS), the observation data from robot total stations, fiber optic sensors, and point cloud measurements are converted into a common observation space through observation preprocessing and spatial registration, and they continuously estimate the updated structural state through prediction and observation correction, and then serve as a unified input for subsequent calculations and model updates. The experimental results show that using a 200 station control network reduced the computation time from 21.8 min to 3.7 min; after dynamic correction, the overall convergence decreased from the average deviation of the main beam axis AP axis 21.9 mm to around 2.8 mm across the entire bridge; the 3D average deviation of the center point of the cable conduit outlet converged from 8.87 mm to 2.565 mm; the predicted height of the corrected model average deviation was 13.04 mm to +2.67 mm, and the dispersion was significantly reduced. This paper provides a systematic theoretical guidance and technical path for high-precision computer-controlled intelligent construction of large bridges.
    Keywords: high-performance computing; large bridge construction measurement; BIM model dynamic updating; multi-source sensor data fusion; structural parameter inversion.
    DOI: 10.1504/IJHPSA.2026.10081999
     

 

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