One of the reasons that temperature and power dissipation have become such large issues is that increased speed has increased the number of operations per second, while the power dissipation per operation has not dropped that much. The reason for the speed increase can be partly shown to be inefficient software, more commonly called "bloatware". Of course it is easier and faster to write, but poorly written code wastes power. The excuse for allowing code that is not efficient has been that memory and processing power were so cheap that they could make up for the poor code. Now it is becoming clear that this is a bad choice, since the devices have become so very small, leading to much higher power densities.
One means of reducing the heat load, then, would be to use better code, and slow down the processor a bit. Of course this will require a level of programming skill that is not very common, and also a reduction in the number of useles features that seem to be everywhere. But it is the one solution that does not wind up challenging the basic laws of physics.
Airborne is the first sector we'll see, with mini-drones already requiring DSP capability in a vastly shrunken space. Automotive is always a field ripe for more dashboard integration, but I'd expect medical electronics to increase demands fairly quickly. Medical record digitization has accelerated now that hospitals are accepting tablets as a better alternative than laptops, and this will drive an overall move to get patient data acquisition into handheld platforms whenever and wherever possible.
What's your sense of the thermal and packaging challenge in the embedded space as MCU vendors pack more and faster cores (dual core) into what used to be fairly standardized and not all that cutting edge parts?
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For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.