FPGA device area is dominated by interconnect, so low-cost FPGA architectures often have reduced interconnect capacity. This limited routing capacity creates a hard channel width constraint that can make it difficult for CAD tools to successfully map a circuit into these devices. Instead of migrating a design to a high-cost, resource-rich architecture that is easier to route, we present a cheaper alternative: a fully automated CAD flow (Un/DoPack) that finds local regions of high interconnect demand and reduces it by spreading out the logic in that region. This is done by introducing whitespace in the form of empty logic elements (LEs) within the configurable logic blocks (CLBs) of the congested region. After spreading, the congested region occupies more routing channels and so obtains access to greater aggregate interconnect capacity. Although this has the side effect of using more CLBs, it has the advantage of lowering peak interconnect demands and making a previously-unroutable circuit routable. We also design a new set of synthetic benchmark circuits that model interconnect variation within a large design. Using these benchmarks, we show that circuits with high interconnect variation require FPGA devices to have large channel widths. However, since congestion of such circuits is localized, Un/DoPack is very good at reducing the peak demands of circuits with high interconnect variation. Our results suggest that even for an average Rent exponent of 0.62 (a modest value), a large variation of this exponent within a design will also require FPGAs to have large channel widths. Thus, it is crucial to study interconnect variation of benchmark circuits when designing lowcost FPGAs. Previous research studying interconnect properties focuses on average Rent exponent values of each design, but we believe new work should study variation as well. For circuits with high interconnect variation, we demonstrate that channel widths can be reduced by up to ~40% with only ~10% increase in area.

Designers of field-programmable gate arrays (FPGAs) are always striving to improve the performance of their designs. As they migrate to newer process technologies in search of higher speeds, the challenge of interconnect delay grows larger. For an FPGA, this challenge is crucial since most FPGA implementations use many long wires. A common technique used to reduce interconnect delay is repeater insertion. Recent work has shown that FPGA interconnect delay can be improved by using unidirectional wires with a single driver at only one end of a wire. With this change, it is now possible to consider interconnect optimization techniques such as repeater insertion. In this work, a technique to construct switch driver circuit designs is developed. Using this method, it is possible to determine the driver sizing, spacing and the number of stages of the circuit design. A computer-aided design model of the new circuit designs is developed to assess the impact they have on the delay performance of FPGAs. Results indicate that, by using the presented circuit design technique, the critical path can be reduced by 19% for short wires, and up to 40% for longer wires.

A computational circuit is custom-designed hardware which promises to offer maximum speedup of computationally intensive software algorithms. However, the practical needs to manage development cost and many low-level physical design details erodes much of the potential speedup by distracting attention away from high-level architectural design. Instead, designers need an inexpensive, processor-like platform where computational circuits can be rapidly synthesized and simulated. This enables rapid architectural evolution and mitigates the risk of producing custom hardware. In this paper we present a tool flow (RVETool) for compiling computational circuits into a massively parallel processor array (MPPA). We demonstrate the CAD runtime is on average 70x faster than FPGA tools, with a circuit speed 6.4x slower than FPGA devices. Unlike the fixed logic capacity of FPGAs, RVETool can trade area for simulation performance by targeting a wide range of processor cores.