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Solving a large number of load flow problems quickly is required for Monte Carlo analysis and various power system problems, including long term steady state simulation, system benchmarking, among others.

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The CASPER simulation platform also provides users with complete support of SPARCV9 instruction set enabling them to run a full operating system software stack, and hence a wide variety of benchmarking applications. This power saving data accounts for the power consumption of the power management units themselves. We have implemented two such techniques in CASPER-Chipwide Dynamic Voltage and Frequency Scaling, and Performance Aware Core-Specific Frequency Scaling, which show average power savings of 35.9% and 26.2% on a baseline 4-core SPARC based architecture respectively. Additionally CASPER is designed to accommodate cycle-accurate models of hardware controlled power management units, enabling architects to experiment with and evaluate different autonomous power-saving mechanisms to study the run-time power-performance trade-offs in embedded many-core processors. In this paper we present CASPER, a robust instruction trace driven cycle-accurate many-core multi-threading micro-architecture simulation platform where we have incorporated power estimation models of a wide variety of tunable many-core micro-architectural design parameters, thus enabling processor architects to explore a sufficiently large design space and achieve power-efficient designs. For large scale designs of many-core processors, a holistic approach integrating both these techniques at different levels of abstraction can potentially achieve maximal power savings. While most chip architects design power-efficient processors by finding an optimal power-performance balance in their design, some use sophisticated on-chip autonomous power management units, which dynamically reduce the voltage or frequencies of idle cores and hence extend battery life and reduce operating costs. This allows the result obtained to be extended to MCs made by other manufacturers, which ensures the practical value of the developed patterns.ĭespite the promising performance improvement observed in emerging many-core architectures in high performance processors, high power consumption prohibitively affects their use and marketability in the low-energy sectors, such as embedded processors, network processors and application specific instruction processors (ASIPs). The study results were tested using the STM32F103 microcontroller employing the Cortex microcontroller software interface system (CMSIS) library.

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The developed patterns make it possible to unify the source code for the Cortex-M architecture microcontrollers from different manufacturers, improve maintenance, and adapt it to the mathematical model of the finite state machine. A feature of these patterns is the higher speed of the software solution compared to the solutions based on RTOS. To address these shortcomings, typical State software patterns have been developed for an auxiliary controller within a circuit of controlling mechanisms or sensors based on the Cortex-M architecture microcontroller in real time, in a procedural paradigm. Simple software solutions are complex at unification, support, and have difficulties with mathematical modeling. This study has found that the application of RTOS leads to a speed-related constraint. The software part of these microcontrollers data could be implemented on the basis of a real-time operating system (RTOS). Such hardware can be implemented on the basis of mass microcontrollers of the Cortex-M architecture.

At the same time, it is necessary to ensure the unification of the source code, the quality of software maintenance, and mathematical modeling at a relatively low cost of software and hardware solution. There are real-time technical systems that require high speed of software solutions.