First published in 1994, "Parallel Computing: Theory and Practice" has become a widely acclaimed and influential textbook in the field. The book is divided into 11 chapters, which systematically cover the basics of parallel computing, including architectural foundations, parallel algorithms, and programming paradigms. Quinn's writing style is characterized by clarity, precision, and a focus on practical applications, making the book accessible to a broad audience, from undergraduate students to seasoned researchers.
While Amdahl’s Law says speedup is limited by serial code, Quinn pushes further with Isoefficiency . He demonstrates how to measure scalability —the ability of an algorithm to maintain efficiency as processors increase. His formula: [ W = K \cdot f(p) ] (Where W is workload, p is processors, and f(p) is the growth function) is a staple of his teaching. You cannot master this without his specific examples. First published in 1994, "Parallel Computing: Theory and
Parallel Computing : Theory and Practice - Better World Books While Amdahl’s Law says speedup is limited by
Each processor possesses private local memory. Nodes must exchange data explicitly via message-passing networks. Parallel Algorithm Complexity and Performance Metrics You cannot master this without his specific examples
If you are looking for more modern implementations (like MPI or OpenMP), Quinn also authored (2003). This later work is often preferred for contemporary practical programming exercises and is sometimes available on GitHub as a supplementary resource. Parallel computing : theory and practice - Internet Archive