Design of parallel computing system for embedded network distributed load tasks

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@Article{HUANG:2021:MM,

• author = "Heqing Huang and Xiaohui Xu and Chunling Tang",
• title = "Design of parallel computing system for embedded network distributed load tasks",
• journal = "Microprocessors and Microsystems",
• volume = "83",
• pages = "104017",
• year = "2021",
• ISSN = "0141-9331",
• DOI = "doi:10.1016/j.micpro.2021.104017",
• URL = "https://www.sciencedirect.com/science/article/pii/S0141933121001903",
• keywords = "genetic algorithms, genetic programming, Data centers, Parallel computer, Parallel computation, Hardware, Software, Embedded network",
• abstract = "Parallel computing is a type of computational construction in which multiple processors perform multiple small calculations at once and a whole large and complex set of problems. Dynamic simulation and real-world data modeling are required to achieve a similar level of parallel computation are critical. Co-calculation provides integration and saves time and money. Parallel computation can only be arranged for complex large data sets and his administration. Parallel computers have been used to solve various isolation and continuous optimization problems. Mechanisms such as single level, linear optimization and branch and internal point systems are not restricted, and genetic programming is often used in parallel and effectively. Embedded systems are generally distributed and often face changing demands over time. That said, existing methods that are obsolete or invalid at the time of compilation are unpredictable by classifying optimal computing tasks as the best use of existing resources for Hardware (HW) and Software (SW). Here, investigate a different idiosyncratic algorithm to balance the load of online HW / SW segmentation. Once there are modifications to suit the computing needs, the system must assign dynamic tasks and become necessary when performing tasks with local hardware or software sources and other nodes. The results obtained show that the proposed method significantly shares the load between different nodes and significantly reduces the allowable task's worst response time",

}

Genetic Programming entries for Heqing Huang Xiaohui Xu Chunling Tang

Citations