Great news from the IEEE International Symposium on Field-Programmable Custom Computing Machines this week – our paper KAPow: A System Identification Approach to Online Per-module Power Estimation in FPGA Designs won the best paper award!

KAPow is all about trying to understand where your FPGA design is burning power, at run time, so that some higher level control entity can make intelligent decisions based on that information.

The problem is that we just don’t have the power sensors – we only know the total power consumed by the device, not the power consumed by each module in the design. So what to do?

Enter KAPow. Our tool (soon to be released publicly as an output from the PRiME project) will take RTL, instrument it and return back RTL that estimates its own power consumption.

The idea is fairly straight-forward: Automatically identify at synthesis (compile) time a subset of nets that you think are going to have a good correlation with power consumption of a module. Insert cheap counters to monitor their activity at run-time, and then use an online recursive least squares model to adaptively learn a model of power consumption of each module, based on the overall power consumption of the chip.

Results are good: power estimates are good down to about 5mW, and the infrastructure itself adds less than 4% to the total power consumed by the device.

Now, of course, the question is what to do with all this information that can now be collected at run-time. Watch this space!

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