Exploring the DataFlow Supercomputing Paradigm / Computer Communications and Networks (PDF)

The mapping of additional algorithms onto the DataFlow architecture is also covered in the following Springer titles from the same team: DataFlow Supercomputing Essentials: Research, Development and Education, DataFlow Supercomputing Essentials: Algorithms, Applications and Implementations, and Guide to DataFlow Supercomputing.

Topics and Features:

• Introduces a novel method of graph partitioning for large graphs involving the construction of a skeleton graph
• Describes a cloud-supported web-based integrated development environment that can develop and run programs without DataFlow hardware owned by the user
• Showcases a new approach for the calculation of the extrema of functions in one dimension, by implementing the Golden Section Search algorithm
• Reviews algorithms for a DataFlow architecture that uses matrices and vectors as the underlying data structure
• Presents an algorithm for spherical code design, based on the variable repulsion force method
• Discusses the implementation of a face recognition application, using the DataFlow paradigm
• Proposes a method for region of interest-based image segmentation of mammogram images on high-performance reconfigurable DataFlow computers
• Surveys a diverse range of DataFlow applications in physics simulations, and investigates a DataFlow implementation of a Bitcoin mining algorithm