An effort to test various annealers for nextpnr

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NextPNR hyperparam optimization

Running the tunner is simple, just prepend one:

• The goal of tunner is to significantly shorten the time to explore the best parameters given a configuration space.
• The tunner will find near the best one in orders of magnitude shorter time compared to exhaustive brute force.

Available annelars for nextpnr are in tunners:

Tunner	MultiAlgo	Parallel
Mango	N	Y
HyperActive	Y	N
Optuna	Y	N
HyperOpt	Y	N

The brute force experiment

Given a configuration space expensive but complete brute force exploration can be done:

• 0-explore-brute.sh will explore the space (will take some time)
• 1-parse-results.sh will aggregate log results into a JSON file
• 2-graph-results.sh will display histogram occurences of yielded clock speeds

Experiment	Image1	Image2
MARLANN	Default: 28.21 Mhz	Default: 96.79 Mhz
PicoRV32	Default: 89.79 Mhz

Future goal (WiP)

Given parameter space:

• track early features extracted from several nexpnr startups
• encode early features in metric measurable feature vectors
• generate a cost model (xgboost) in TVM autotune fashion
• try fit/estimate/predict out from learned model the best set