Multicore And Gpu Programming: An Integrated Ap... -

The second edition (2022) updated all sample code to the C++17 standard and added a new chapter on concurrent data structures. Common Critiques

Those needing to implement high-performance scientific simulations or machine learning algorithms. Multicore and GPU Programming: An Integrated Approach

Professionals looking to optimize applications by balancing workloads across modern hardware platforms. Multicore and GPU Programming: An Integrated Ap...

by Gerassimos Barlas is widely regarded by reviewers from Amazon and Goodreads as a comprehensive and clear guide for transitioning from sequential to parallel programming. It is particularly praised for its "hybrid" focus , teaching readers how to combine diverse tools like MPI, OpenMP, and CUDA to leverage both CPUs and GPUs effectively. Key Strengths

At over 1,000 pages , it is a massive reference that may be overwhelming for those seeking a quick, high-level overview rather than a deep dive. Ideal Audience According to Elsevier , the book is best suited for: The second edition (2022) updated all sample code

Reviewers on Amazon highlight the "great details" in explanations and the helpfulness of practice problems and downloadable source code .

It is frequently used as a university textbook for parallel computing courses. by Gerassimos Barlas is widely regarded by reviewers

The book covers a vast landscape of parallel computing, including threads, OpenMP, MPI, CUDA, OpenCL, and the Thrust template library.