This project implements a genetic algorithm approach to solve the Resource-Constrained Project Scheduling Problem (SRCPSP), which is a well-known NP-hard optimization problem in operations research ...
A Python implementation of a framework for scheduling deep learning applications on heterogeneous embedded devices (CPU, GPU, NPU) using genetic algorithms. Based on a Paper By DUSEOK KANG, JINWOO OH, ...
Abstract: In embedded operating systems, as the number of kernels increases, the granularity of task allocation needs to become finer and finer. However, overly detailed task allocation may lead to ...
Robot applications encompass a multitude of edge computing tasks, such as image processing, health monitoring, path planning, and infotainment. However, task scheduling within such environments ...
Editor's Note: Embedded Systems Architecture, 2nd Edition, is a practical and technical guide to understanding the components that make up an embedded system’s architecture. Offering detailed ...
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