Hardware modules would be much easier to reuse if they supported generic flexible high-level interfaces. However, these interfaces are rarely used since they lead to timing and area overheads compared to a customized design. This paper describes a reachability analysis framework that identifies over-provisioning in instances of flexible design, and offers a technique for annotating this information so that modern synthesis tools can remove most of the overhead. Results are demonstrated on a variety of flexible structures, including functional blocks, programmable state machines, and latency-insensitive interfaces.

Creating parameterized “chip generators” has been proposed as one way to decrease chip NRE costs. While many approaches are available for creating or generating flexible data path elements, the design of flexible controllers is more problematic. The most common approach is to create a microcoded engine as the controller, which offers flexibility through programmable table-based lookup functions. This paper shows that after “programming” the hardware for the desired application, or applications, these flexible controller designs can be easily converted to efficient fixed (or less programmable) solutions using partial evaluation capabilities that are already present in most synthesis tools.

The drive for low-power, high performance computation coupled with the extremely high design costs for ASIC designs, has driven a number of designers to try to create a flexible, universal computing platform that will supersede the microprocessor. We argue that these flexible, general computing chips are trying to accomplish more than is commercially needed. Since design NRE costs are an order of magnitude larger than fabrication NRE costs, a two-step design system seems attractive. First, the users configure/program a flexible computing framework to run their application with the desired performance. Then, the system "compiles" the program and configuration, tailoring the original framework to create a chip that is optimized toward the desired set of applications. Thus the user gets the reduced development costs of using a flexible solution with the efficiency of a custom chip.