Thermonat models heat with unprecedented accuracy

Have you noticed how new smartphone models don’t seem to come out at as quick a clip as they did a decade ago? That’s partly due to the fact that you can’t pack more processing power into the same space without creating new thermal issues.

Pure transistor scaling has slowed down of late, but IBM and others are continuing to work toward smaller and smaller nodes. As transistor nodes get smaller, heat becomes a bigger problem. AI technologies, too, are driving increased chip power density and generating more heat.

Today IBM Research is announcing the results of its work under DARPA’s Thermonat, short for Thermal Design of Nanoscale Transistors, in which the IBM team modeled thermal behaviors of semiconductors all the way down to the atomic level.¹ As part of IBM’s Thermonat effort, machine-learning software trained on IBM’s massive stores of semiconductor data achieved prediction accuracy within one degree, tens of thousands of times faster than the next best simulation…