Parallel high performance computing artificial (14 Ergebnisse)

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Zustand: New. Dr. M. M. Raghuwanshi is the Dean of Engineering at S.B.Jain Institute of Technology Management and Research, Nagpur, India.Dr. Pradnya Borkar is an Associate Professor at the Department of Computer Science and Engineering and R&amp.

Taschenbuch. Zustand: Neu. Neuware - 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. …

Gebundene Ausgabe. Zustand: Neu. High-Performance Computing: Architectures, Parallel Programming, and Intelligent Applications offers a comprehensive exploration of the technologies, architectures, and intelligent applications that shape modern high-performance computing. As computational workloads continue to expand across Artificial Intelligence, Machine Learning, scientific research, engineering, healthcare, finance, climate modeling, and big data analytics, HPC has become essential for solving complex problems rapidly and efficiently.The book introduces the fundamental concepts of HPC, including performance measurement, scalability, speedup, efficiency, parallelism, and workload optimization. It explores modern computing architectures, including multicore and many-core processors, GPUs, heterogeneous systems, shared-memory and distributed-memory architectures, HPC clusters, supercomputers, and emerging exascale platforms. A significant focus is placed on parallel programming and optimization. Readers are introduced to MPI, OpenMP, Pthreads, CUDA, OpenCL, GPU programming, synchronization, communication, load balancing, memory management, and performance optimization techniques. The book also covers distributed computing, cluster scheduling, grid computing, cloud-based HPC, virtualization, containerization, resource management, fault tolerance, and energy-efficient computing. The book further connects HPC with Artificial Intelligence, Distributed AI, and HPC-enabled intelligent applications. Sprache: Englisch Gewicht in Gramm: 547.…

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Hardback. Zustand: New. 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 applicationsParallelization techniquesHPC for machine learningImplementation of parallel computing with AI in big data analyticsHPC with AI in healthcare systemsAI in industrial automationCoverage 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. …

Hardcover. Zustand: Brand New. 336 pages. 9.18x6.12x9.21 inches. In Stock.

Hardback. Zustand: New. 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 applicationsParallelization techniquesHPC for machine learningImplementation of parallel computing with AI in big data analyticsHPC with AI in healthcare systemsAI in industrial automationCoverage 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. …