Nature-Inspired Optimization Based Multithread Scheduling For Program Segments
Keywords:
Multithread scheduling, program segments, speedup multicore processors, linear simplex-elite integrated lightning search optimization (LS-EILSO)Abstract
The utilization of the processors, responsiveness, resource sharing, and efficient thread usage are the only benefits of multicore processors that allow multithreading techniques. Consequently, programming languages must allow multithreading programming to have these benefits. Since most ancient program codes were created sequentially, older software cannot work with this method. This was a difficult anytime multithreading code was being converted from old sequential procedures. There is a need for further optimization despite the availability of multiple multithreading algorithms due to discrepancies in their overhead, efficiency, and speedup. This demonstrates the efficacy of the optimization performed by a lightning search optimization over a wide range of problems. To develop multithreaded code while keeping a sequential one in mind, this research presents a linear simplex-elite integrated lightning search optimization (LS-EILSO) for multithreading scheduling. The number of stages of speedup execution time, efficiency, and cost of the LS-EILSO approach have all been evaluated. The most significant speed achieved by LS-EILSO with 32 threads is 11.98, while the average error rate between experimental and analytical cost numbers is 14.56 percent, as shown by experimental data. Additionally, it has been demonstrated that LS-EILSO can support more threads and achieve higher speedup when compared to intermediate representation based on LSO. As an illustration, the results reveal that when employing 32 threads both ways, LS-EILSO achieves a speedup of 11.71, about three times faster than the 3.77 speedups obtained by the current and planned.
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