Efficient design exploration based on module utility selection
In this paper, we present a design exploration framework, called WIZARD, which aims at finding module selections that will lead to superior designs while considering scheduling and resource binding under latency and power constraints. The framework contains two phases: choosing the resource configuration, and determining a module binding for each resource. We introduce a powerful model called an acceptability function which models design objectives, based on tradeoffs among different design constraints as well as a user's willingness to accept a design. Module utility measure cooperating with inclusion scheduling is the key to the success of our method. The utility of a module reflects the usefulness of the module based on the acceptability function, Inclusion scheduling is an algorithm to provide information for determining the number of functional units as well as module usefulness. We also present a heuristic which modifies module utility values based on the given acceptability function until they lead to superior selections. Many experiments on well-known benchmarks show the effectiveness of the approach when the obtained module selections are compared with the results from enumerating all module selections, as well as other schemes such as MSSR and PSGA.
scheduling design space exploration fuzzy logic high-level synthesis resource allocation