Automatic FPGA Placement Configuration for Customer Designs

Searching for new ways to improve the efficiency of integrated circuits (IC) led to the development of specialized heterogeneous configurable IC (FPGA) and systems-on-a-chip. Their key feature is an extended interpretation of standard cell library, containing ready-to-use IP cores along with standard cells. Specific customer designs require the flexibility of the configurable heterogeneous IC’s architecture and, therefore, automatic CAD clustering and placement algorithms configuration. The development of efficient configuration methods and algorithms is impossible without relying on the mathematical apparatus. In this work, such mathematical apparatus is provided. The authors described a set-theoretic model of a hierarchical project and formalized the hierarchical approach to the netlist, using the apparatus of mathematical logic, set and graph theories. The correspondence between the customers designs’ elements and FPGA’s elements has been formalized to provide fast clustering and placement configuration. The obtained results provide the basis for future efficient methods for automatic placement and clustering configuration.

Wire-Length and Run-Time Optimization in FPGA Placement Using Hybrid Iterative Algorithms

This paper introduces hybrid iterative algorithms that combine Particle Swarm Optimization (PSO) and Simulated Annealing (SA) algorithms for Field Programmable Gate Array (FPGA) placement by considering adaptive inertia weight and local minima avoidance. The algorithms target to optimize the wire-length of the nets, run time and critical path delay in the placement of logic blocks. Using the adaptive inertia weight parameter and local minima avoidance, the hybrid PSO-SA algorithm is modified to Time-varying PSO-SA (TPSO-SA) and Modified PSO-SA (MPSO-SA) algorithm, respectively. These different hybrid PSO-SA algorithms are checked for efficiency by comparing with the Versatile Place and Route (VPR) algorithm of the Verilog to Routing (VTR) tool using Microelectronics Centre of North Carolina (MCNC) benchmark circuits. The hybrid PSO-SA algorithms give 5–37% better results for wire-length cost and 20–58% reduction in runtime compared to the VPR placement algorithm on different benchmark circuits. Critical path delay is also taken into consideration.