editor's blog
Subscribe Now

Ban Power Consumption

“How much power does it consume?”

This has been a key question ever since I started work as a product engineer many years ago. Heck, back then we even published power consumption numbers, although we used ICC as a proxy – we didn’t actually publish power, but you could easily do the multiplication with VCC to get it. (Yes, this was bipolar.)

These days, the concept is even more important, what with all the focus on battery-powered whats-itses. But in deconstructing a lot of what’s going on now, there’s an interesting nuance coming to the fore: energy vs. power.

  • Energy is a “thing.” It’s something physical that has a measurable quantity.
  • Power, by contrast, is not a thing; it represents the rate of flow of a thing, namely energy.

This is more than just an academic difference. Batteries and fuel cells can store more energy than a supercapacitor can, but they release that energy at a slower rate than the supercap. So one is capable of higher energy capacity; the other of higher power. The distinction actually matters.

So I find myself tripping more and more over the familiar phrase, “power consumption.” Power isn’t a “thing,” so it can’t be consumed. Energy is a “thing,” and it can be consumed.

So “power consumption” makes no conceptual sense; “energy consumption” makes a ton of sense.

An electronic device consumes energy, but, from a practical standpoint, you can’t know the energy consumed until you know how long you’ve run the device. And you have to be able to serve up the energy to the device from your energy store at the rate the device expects, or else you’ll starve it. So “power” is ultimately involved as a critical device requirement; energy consumption not so much.

So if “power consumption” is off the table, “power requirement” seems a suitable replacement.

I will therefore labor to use either “energy consumption” or “power requirement” henceforth.

And no, I don’t expect the world to follow. (One of my many quixotic attempts to apply logic to language… like the perennial abuse of the plural of “die” and the silly overuse of @…)

Leave a Reply

featured blogs
Aug 11, 2020
While Cadence System in Package (SiP) is '€“ and continues to be '€“ one of the most complete solutions for package design, the Virtuoso RF Solution gives access to a constantly increasing set of package... [[ Click on the title to access the full blog on the Cadence Com...
Aug 11, 2020
Making a person appear to say or do something they did not actually say or do has the potential to take the war of disinformation to a whole new level....
Aug 7, 2020
HPC. FinTech. Machine Learning. Network Acceleration. These and many other emerging applications are stressing data center networks. Data center architectures evolve to ensure optimal resource utilization and allocation. PECFF (PCIe® Enclosure Compatible Form Factor) was dev...
Aug 7, 2020
[From the last episode: We looked at activation and what they'€™re for.] We'€™ve talked about the structure of machine-learning (ML) models and much of the hardware and math needed to do ML work. But there are some practical considerations that mean we may not directly us...

Featured Video

Product Update: New DesignWare USB4 IP Solution

Sponsored by Synopsys

Are you ready for USB4? Join Gervais Fong and Eric Huang to learn more about this new 40Gbps standard and Synopsys DesignWare IP that helps bring your USB4-enabled SoC to market faster.

Click here for more information about DesignWare USB4 IP

Featured Paper

Computational Software: 4 Ways It is Transforming System Design & Hardware Design

Sponsored by BestTech Views

Cadence President Anirudh Devgan shares his detailed insights on Computational Software. Anirudh provides a clear definition of computational software, and four specific ways computational software is transforming system design & hardware design -- including highly distributed compute, reduced memory footprints, co-optimization, and machine learning applications.

Click here for the white paper.

Featured Chalk Talk

Machine Learning at the Edge

Sponsored by Mouser Electronics and NXP

AI and neural networks are part of almost every new system design these days. But, most system designers are just coming to grips with the implications of designing AI into their systems. In this episode of Chalk Talk, Amelia Dalton chats with Anthony Huereca of NXP about the ins and outs of machine learning and the NXP iEQ Machine Learning Software Development Environment.

Click here for more information about NXP Semiconductors i.MX RT1060 EVK Evaluation Kit (MIMXRT1060-EVK)