A dataflow-inspired CGRA for streaming applications

The herein presented research is motivated by the need for reconfigurable, flexible computing arrays targeted at streaming applications that contain a large degree of instruction-level parallelism. Such arrays are usually referred to as coarse-grained reconfigurable arrays (CGRAs). CGRAs are composed of small, reconfigurable cores that are interconnected to form a computing grid. Here, we present a complete CGRA, consisting of an architecture and a programming language. Both the architecture and the programming language are inspired by the principles found in dataflow.