This book is meant to support teaching of the DataFlow subject. University coursesudfully or partially dedicated to the DataFlow subject are important for the followingudreason: More and more Big Data are present in all kinds of research or commercialudchallenges. Consequently, the DataFlow paradigmis getting importance, since it hasudbeen proven that it is the most suitable computing paradigm for Big Data. It offersudsuperior speedups (depending on the application, from about 20 to about 200, evenud2000 in some isolated cases) as well as power savings (typically about 20 times); itudbrings size reduction too. A recent study by researchers of the Tsinghua Universityudin China reveals that for Shallow Water Weather Forecast (a Big Data problem), onudthe 1U level, compared to Tianhe-2 (at the time of writing of this book, rated #1udon the Top 500 SuperComputers list, which compares SuperComputers based onudLinpack, a small data benchmark), Maxeler (a DataFlow machine) demonstrates theudspeedup of 14. With all the above in mind, the book is divided into four chapters:udThe first one is of an introductory nature. The second gives an overview of theudrelated research. The third represents a case study. The fourth one is oriented to theudease of use and covers the issues of importance forWebIDE (a web-based integrateduddevelopment environment).
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