Using graph isomorphism for mapping of data flow applications on reconfigurable computing systems

The tremendous increase in the computing capacity of the embedded architectures has led to widespread deployment of embedded applications. These applications generally exhibit similar patterns in their specification such as filters in which multiply and accumulate operations are repetitive. If such patterns are identified and used for the system design, trade-off between the area and delay can be achieved. This paper proposes a new methodology which allows to implements a design by retrieving similar patterns known as graph isomorphs and interfaces them as HW accelerators in the system-on-chip design flow. An effective algorithm that converges in polynomial time has been proposed to find such similar subgraphs. In the next phase of the design flow, an algorithm has been proposed which performs the scheduling of clusters and minimizes the time overhead. All algorithms have been written in python for parsing the data flow description and test the correctness of the proposed work. The proposed design flow has been applied to five different programs which are sine, cosine, exponent, matrix multiplication and discrete cosine transform (DCT). These have been described as a data flow graph and have been used for results comparison. An estimation table showing the HW and SW parameter of the data flow operators has been developed for timing and area analysis of the programs. The work is an effort to show the clustering and scheduling of a standalone specification which is mapped on static reconfigurable fabric. Reconfigurable computing systems (RCS) are a popular platform for embedded computing applications as they offer a wide exploration in the design space by allowing HW, SW or HW-SW (hybrid) implementation depending on computational demand and resource requirement. These systems have inspired the designers to find new frameworks for achieving the optimized system characteristics under the given constraints. Any static or dynamic HW hardware optimization in an application can be proposed, implemented and easily verified on the chip. The results presented show the comparison of the proposed approach with SW and HW implementation of DCT design on the Xilinx ML507 board. HW timer has been used to find the execution of each implementation. The experimental verification of the proposed algorithms shows that static IP core design flow gives better results.