dse-loop

Automate parameter tuning by running an autonomous design-space exploration loop that executes your program, analyzes outcomes, and selects new parameters until an objective is met. This reduces manual trial-and-error for architecture and EDA tasks.

Autonomous design-space exploration iteratively runs a target program, evaluates the results against a defined objective, and intelligently selects the next parameter set. It continues this loop until meeting the goal or hitting a configured timeout and iteration cap.

Yes, you can set a time budget and iteration limit for EDA parameter sweeps. The loop uses configurable constants like TIMEOUT, MAX_ITERATIONS, and PATIENCE, which you can override inline to control exploration behavior and ensure repeatable workflows.

Optimize cache and pipeline parameters by defining your performance or power objective and starting the exploration loop. The automated process tests parameter combinations, analyzes the outcomes, and iterates until your target IPC or performance goal is achieved.

The best way to run iterative parameter sweeps for EDA tasks is using an autonomous exploration loop. It automates the execute-analyze-select cycle, applying configurable time budgets and iteration caps to systematically find optimal parameters without manual intervention.

You should not use an autonomous exploration loop if your optimization problem lacks a clear objective or if the parameter space cannot be evaluated programmatically. The loop relies on executing a program and analyzing outcomes to select new parameters until the objective is met.