dse-loop

Automating design space exploration involves running an autonomous loop that executes simulations, collects metrics, and proposes next configurations until an objective is met or timeout occurs. You define the program, tunable parameters, objective, and timeout to start the iterative DSE process.

Autonomous parameter tuning for EDA optimization is the process of iteratively sweeping and adjusting RTL parameters without human intervention. The system analyzes simulation results, selects the next parameter configurations, and enforces safety constraints until the target objective is achieved.

To set up a parameter sweep loop, you specify a task description, the simulation program to run, tunable microarchitectural parameters, the optimization objective, and a timeout. The system then autonomously runs, collects results, and iterates until the objective is met.

Yes, you can enforce safety constraints during automated design space exploration. The system applies hard limits and safety rules to prevent destructive actions while it autonomously runs simulations and proposes new parameter configurations.

Automated parameter tuning supports recovery and logging by maintaining a recoverable state with structured history. It logs baseline and best configurations alongside running results, allowing you to resume and audit the exploration loop after interruptions.

You should use an autonomous DSE loop when iterative design space exploration requires continuous simulation execution and parameter adjustment. It is ideal for complex computer architecture and EDA tasks where manual tuning is impractical and a structured, timeout-bounded approach is needed.