Raghuwanshi M Parallel and High-Performance Computing in AI 2025

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Tecno123 · #1 Post by **Tecno123** » Fri Sep 12, 2025 6:36 am

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Name: Raghuwanshi M Parallel and High-Performance Computing in AI 2025
Format: pdf
Size: 9.94 MB

Book:

Title: Parallel and High-Performance Computing in Artificial Intelligence
Author: Raghuwanshi, Mukesh;Borkar, Pradnya;Jhaveri, Rutvij H.;Raut, Roshani; & Pradnya Borkar & Rutvij H. Jhaveri & Roshani Raut
Language: polski
Year: 2025
Subjects: Computers, Science & Technology, Engineering, Technology, Artificial Intelligence (AI), Robotics & Artificial Intelligence, Artificial Intelligence - General
Publisher: CRC Press
ISBN: 9781040332726
Total pages: 513

Description:

Parallel and High-Performance Computing in Artificial Intelligence explores high-performance architectures for data-intensive applications as well as efficient analytical strategies to speed up data processing and applications in automation, machine learning, deep learning, healthcare, bioinformatics, natural language processing (NLP), and vision intelligence.
The book's two major themes are high-performance computing (HPC) architecture and techniques and their application in artificial intelligence. Highlights include:

HPC use cases, application programming interfaces (APIs), and applications

Parallelization techniques

HPC for machine learning

Implementation of parallel computing with AI in big data analytics

HPC with AI in healthcare systems

AI in industrial automation

Coverage of HPC architecture and techniques includes multicore architectures, parallel-computing techniques, and APIs, as well as dependence analysis for parallel computing. The book also covers hardware acceleration techniques, including those for GPU acceleration to power big data systems.
As AI is increasingly being integrated into HPC applications, the book explores emerging and practical applications in such domains as healthcare, agriculture, bioinformatics, and industrial automation. It illustrates technologies and methodologies to boost the velocity and scale of AI analysis for fast discovery. Data scientists and researchers can benefit from the book's discussion on AI-based HPC applications that can process higher volumes of data, provide more realistic simulations, and guide more accurate predictions. The book also focuses on deep learning and edge computing methodologies with HPC and presents recent research on methodologies and applications of HPC in AI.

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