Few books comprehensively cover the software and programming aspects of reversible computing. Filling this gap, Introduction to Reversible Computing offers an expanded view of the field that includes the traditional energy-motivated hardware viewpoint as well as the emerging application-motivated software approach.
Collecting scattered knowledge into one coherent account, the book provides a compendium of both classical and recently developed results on reversible computing. It explores up-and-coming theories, techniques, and tools for the application of reversible computingβthe logical next step in the evolution of computing systems.
The book covers theory, hardware and software aspects, fundamental limits, complexity analyses, practical algorithms, compilers, efficiency improvement techniques, and application areas. The topics span several areas of computer science, including high-performance computing, parallel/distributed systems, computational theory, compilers, power-aware computing, and supercomputing.
The book presents sufficient material for newcomers to easily get started. It provides citations to original articles on seminal results so that readers can consult the corresponding publications in the literature. Pointers to additional resources are included for more advanced topics. For those already familiar with a certain topic within reversible computing, the book can serve as a one-stop reference to other topics in the field.
About the Author
Kalyan Perumalla , PhD, is a senior R&D staff member and manager at Oak Ridge National Laboratory and an adjunct professor at the Georgia Institute of Technology. Dr. Perumalla is a winner of the prestigious U.S. Department of Energy Career Award in Advanced Scientific Computing Research (2010-2015). He has published over 100 articles in computing and serves on the editorial boards and program committees of leading journals and conferences in computing. He earned a PhD in computer science from the Georgia Institute of Technology. His areas of interest include reversible computing, high-performance computing, parallel discrete event simulation, and parallel combinatorial optimization.