This book describes several approaches to adaptability that are applied for the optimization of parallel applications, such as thread-level parallelism exploitation and dynamic voltage and frequency scaling on multicore systems. This book explains how software developers can apply a novel technique to adapt the number of threads at runtime without any modification in the source code nor recompilation. This book is useful for software developers in general since it offers realistic examples throughout to demonstrate various techniques presented.

Autorentext
Arthur Francisco Lorenzon received his Dr. degree from Federal University of Rio Grande do Sul (UFRGS), Brazil, in 2018. Currently, he is a professor at Federal University of Pampa (UNIPAMPA), in charge of Parallel Computing, Embedded Systems, and Computer Organization disciplines at the undergraduate and graduate levels. His primary research interests include the parallelism exploitation in multicore systems, evaluation of different parallel programming interfaces, and the design of approaches to automate and optimize the thread-level parallelism exploitation.
Antonio Carlos Schneider Beck Filho received his Dr. degree from UFRGS, Brazil, in 2008. Currently, he is a professor at the Applied Informatics Department at the Informatics Institute of UFRGS, in charge of Embedded Systems and Computer Organization disciplines at the undergraduate and graduate levels. His primary research interests include computer architectures and embedded systems design, focusing on power consumption.

Inhalt

1. Run-time Adaptability: the key for improving parallel applications a. introduction b. scalability analysis c. this book
2. Fundamental Concepts  a. parallel computing in software  b. power and energy consumption  c. design space exploration of optimization techniques
3. Does the parallel programming interface matter? a. Introduction b. methodology c. results
4. Improving parallel applications a. thread-level parallelism exploitation b. dynamic voltage and frequency scaling
5. Case Study a. Aurora: seamless optimization of OpenMP applications b. FDT: feedback-driven threading c. VARUNA
6. Conclusion