MBIST area and test time overhead has historically been estimated after synthesis because that was when the numbers became available. Synthesis and test pattern generation together are slow and resource-intensive, which means teams discover their memory test overhead late, when configuration changes have become expensive. A new stacked ensemble framework predicts both metrics from RTL-level design parameters alone, trained on 4,470 synthesis runs for area and 624 for test time, using features the design team already has: memory count, word width, address depth, port configuration, clock domains.
The mechanism shifts MBIST cost estimation from a post-synthesis artifact to an early input to memory architecture decisions. For SoC teams, embedded memories already consume a large fraction of die area, and MBIST infrastructure adds further overhead on top of that. Knowing that overhead before IP selection closes the feedback loop at the right point in the flow: while the memory configuration is still a variable, not a fixed parameter to work around.
The accuracy numbers will matter for adoption, and the training set size (particularly 624 samples for test time) suggests there is room to narrow the error bounds with more data. But the directional claim is correct: if you can predict MBIST overhead from parameters you already have in RTL, every iteration that would have required a synthesis run to get a cost estimate is a cycle compressed. SoC teams running MBIST cost estimates post-synthesis are discovering constraints after the decisions that created them have already been locked.