This book brings together research on numerical methods adapted for
Graphics Processing Units (GPUs). It explains recent efforts to
adapt classic numerical methods, including solution of linear
equations and FFT, for massively parallel GPU architectures. This
volume consolidates recent research and adaptations, covering
widely used methods that are at the core of many scientific and
engineering computations. Each chapter is written by authors
working on a specific group of methods; these leading experts
provide mathematical background, parallel algorithms and
implementation details leading to reusable, adaptable and scalable
code fragments. This book also serves as a GPU implementation
manual for many numerical algorithms, sharing tips on GPUs that can
increase application efficiency. The valuable insights into
parallelization strategies for GPUs are supplemented by
ready-to-use code fragments. Numerical Computations with GPUs
targets professionals and researchers working in high performance
computing and GPU programming. Advanced-level students focused on
computer science and mathematics will also find this book useful as
secondary text book or reference.
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