Parallel Computing for High-Performance Applications
Table Of Contents
<p>1. Introduction to Parallel Computing<br> 1.1 Overview of Parallelism<br> 1.2 Importance of Parallel Computing<br>2. Parallel Algorithms<br> 2.1 Design and Analysis of Parallel Algorithms<br> 2.2 Parallel Sorting and Searching Algorithms<br>3. Parallel Programming Models<br> 3.1 Shared Memory and Distributed Memory Models<br> 3.2 Message Passing Interface (MPI) and OpenMP<br>4. Parallel Architectures<br> 4.1 Multi-core Processors and SIMD Instructions<br> 4.2 Cluster and Grid Computing<br>5. Performance Optimization in Parallel Computing<br> 5.1 Load Balancing and Scalability<br> 5.2 Parallel I/O and Data Management<br></p>
Thesis Abstract
<p> Parallel computing has become increasingly important in the field of computer science due to the need for high-performance applications. This project aims to explore the principles and techniques of parallel computing and apply them to develop efficient and scalable software solutions. The project will investigate parallel algorithms, parallel programming models, and parallel architectures to achieve improved performance and resource utilization. The research will also focus on the challenges and opportunities of parallel computing in modern computing environments. <br></p>Thesis Overview
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