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Break into the powerful world of parallel GPU
programming with this down-to-earth, practical
guide
Designed for professionals across multiple industrial sectors,
Professional CUDA C Programming presents CUDA -- a
parallel computing platform and programming model designed to ease
the development of GPU programming -- fundamentals in an
easy-to-follow format, and teaches readers how to think in parallel
and implement parallel algorithms on GPUs. Each chapter covers a
specific topic, and includes workable examples that demonstrate the
development process, allowing readers to explore both the "hard"
and "soft" aspects of GPU programming.
Computing architectures are experiencing a fundamental shift
toward scalable parallel computing motivated by application
requirements in industry and science. This book demonstrates the
challenges of efficiently utilizing compute resources at peak
performance, presents modern techniques for tackling these
challenges, while increasing accessibility for professionals who
are not necessarily parallel programming experts. The CUDA
programming model and tools empower developers to write
high-performance applications on a scalable, parallel computing
platform: the GPU. However, CUDA itself can be difficult to learn
without extensive programming experience. Recognized CUDA
authorities John Cheng, Max Grossman, and Ty McKercher guide
readers through essential GPU programming skills and best practices
in Professional CUDA C Programming, including:
The book makes complex CUDA concepts easy to understand for
anyone with knowledge of basic software development with exercises
designed to be both readable and high-performance. For the
professional seeking entrance to parallel computing and the
high-performance computing community, Professional CUDA C
Programming is an invaluable resource, with the most current
information available on the market.
Break into the powerful world of parallel GPU
programming with this down-to-earth, practical
guide
Designed for professionals across multiple industrial sectors,
Professional CUDA C Programming presents CUDA -- a
parallel computing platform and programming model designed to ease
the development of GPU programming -- fundamentals in an
easy-to-follow format, and teaches readers how to think in parallel
and implement parallel algorithms on GPUs. Each chapter covers a
specific topic, and includes workable examples that demonstrate the
development process, allowing readers to explore both the "hard"
and "soft" aspects of GPU programming.
Computing architectures are experiencing a fundamental shift
toward scalable parallel computing motivated by application
requirements in industry and science. This book demonstrates the
challenges of efficiently utilizing compute resources at peak
performance, presents modern techniques for tackling these
challenges, while increasing accessibility for professionals who
are not necessarily parallel programming experts. The CUDA
programming model and tools empower developers to write
high-performance applications on a scalable, parallel computing
platform: the GPU. However, CUDA itself can be difficult to learn
without extensive programming experience. Recognized CUDA
authorities John Cheng, Max Grossman, and Ty McKercher guide
readers through essential GPU programming skills and best practices
in Professional CUDA C Programming, including:
The book makes complex CUDA concepts easy to understand for
anyone with knowledge of basic software development with exercises
designed to be both readable and high-performance. For the
professional seeking entrance to parallel computing and the
high-performance computing community, Professional CUDA C
Programming is an invaluable resource, with the most current
information available on the market.