posted by Bryon Moyer
While at the recent Sensors Expo, I had a conversation with Anaren that drove home a point: with all of the focus on all of the fancy things that are theoretically possible with the burgeoning Internet of Things (IoT), back in the lab, folks are spending a lot of energy just to get devices connected. And many of the tasks – such as getting the radios up – require expertise that not everyone has.
Their focus is on the RF aspects of the design, with a couple radio modules leveraging Broadcom’s WICED (pron. “wicked,” apparently) technology. They’ve got a kit to help with development, but of course, with all the hardware in hand, you’ve still got to write software to get the RF integrated into the embedded Thing’s stack.
(Image courtesy Anaren)
So they’ve put together a free online tool called Anaren Atmosphere that they describe as being a Labview-like way of assembling the components of your embedded system. They build a communication stack via WebSocket, using RESTful APIs; the tool generates the appropriate code. They say they were able to obtain a door lock and get a connection up and working in a couple hours.
(Click to enlarge; image courtesy Anaren)
Putting things in perspective, however, this enables a smartphone to communicate with the device via Bluetooth. It’s similar to the situation with Golgi that we looked at recently: you’re really just setting up your phone to be a remote control for the device. Not that that’s bad – if your phone can place all the remotes in the house at some point, that’s probably a good thing.
But it includes no algorithms or other intelligence (typically pictured as happening in the Cloud – especially for small devices like door locks). The difference between this and Golgi is that Golgi uses the cellular system and comes in via the Cloud (but without custom algorithms and such); Anaren talks to the device locally.
Then again, this is just step one for them. Around the end of the year, they say that the tool will generate a website, so that starts to feel more like an IoT thing.
Atmosphere is also an ecosystem, and they’re rounding up sensor partners. For now, ST is on their list, and they’re looking to grow it. You can find more about the partnerships in their announcement.
posted by Bryon Moyer
What could you do if you had access to a ton of data about semiconductor design? Things like:
- How designs are structured
- Which modules are used where
- How long each module takes to design
- Who’s making changes to what modules
- How far along verification is proceeding
- Log files on every tool run
Well, you could mash them all into a Big Data repository, set the dial to spin cycle, and – voilà! – out comes all kinds of interesting tidbits of information.
For one thing, as a manager, you could see in far more detail how the design is progressing and where any holdups might be. You could reallocate resources if necessary to nudge those holdups free and have everything come sailing across the finish line at the same time.
If you’re an accounting type, you could understand in much better detail how much each module is costing and how that cost should be allocated. (I sometimes wonder whether it’s more work to do the design or to decide who should pay for the design…)
You might notice that someone is wandering through all of the many bits and pieces that make up the design. Most designers tend to touch their own modules and the ones around them. If someone is going all over the place (or everywhere at once), is there possibly some IP theft going on?
And, the pièce de resistance: you could predict more accurately when the design will tape out.
(Image courtesy IC Manage)
This is something both IC Manage and Dassault are doing. Bringing “big data” (the next hottest buzzword after “IoT”) into the design management (DM) world. Their goals would appear to be similar, although they have different algorithms (and, because there are no benchmarks, it’s impossible to say who has the best ones). Dassault has a bit broader scope, including product lifecycle and manufacturing in the scope of data they scoop up.
Part of this involves employee monitoring, and IC Manage notes that some European companies – Germany in particular – place limits on how much of that an employer can do. So in those cases, they have to anonymize some of the information.
I also talked with them about the state of project scheduling. Back in the day, the winner was the guy that promised to do the fastest design (whether or not he or she actually met that schedule). If marketing or the senior VP decided some product had to be ready by some ridiculous date, you simply had to agree, or “they’ll find someone else that will agree” (a quote from a design manager I respected a lot).
IC Manage’s Dean Drako said that, these days, scheduling is much more realistic. Meeting your promised date is now a thing, and historical tools provide evidence as to whether or not a prediction is realistic, over-aggressive, or sandbagged.
posted by Bryon Moyer
A new inertial measurement unit (IMU), the FIS1100, was announced by Fairchild, and it gives us a couple things to talk about.
First, well… Fairchild. I remember when I started in the industry [kids roll their eyes, “Oh, there goes grampa on one of his stories again”], you’d have these genealogy charts showed how various companies evolved from prior companies. And one of the very few root companies was Fairchild. Anyone who had any time in the industry had, at one point or another, worked at Fairchild.
And then, well, forgive my saying it, but they kinda just disappeared from view.
Well, they’ve now announced their first MEMS product. It’s a six-axis IMU with inputs for an external magnetometer to give nine-axis results. This is more than just attaching another sensor to a bus, since the IMU internals have their own sensor fusion (the AttitudeEngine) for generating quaternion results. They also have higher-level sensor fusion libraries (like body tracking) for execution on a host (those libraries sold separately).
(Image courtesy Fairchild)
And that leads to one of their claimed differentiators. Most IMU vendors specify a level of accuracy for their basic acceleration (linear and rotational) results. Fairchild is specifying the accuracy of their full orientation output, after the calculations. They claim to be the only ones to do that. They specify ±3° for pitch and roll and ±5° for yaw.
They also claim that their algorithms are self-correcting with respect to offset changes (but not drift). And the algorithms leverage human body motion models from Xsens, whom they acquired (and from whom also come many of the body tracking algorithms), allowing enough accuracy to run navigation without GPS input for 60-90 seconds before it gets too far out of whack. (I know, that doesn’t sound that long, but it’s a lifetime in the gyro world, where a few seconds can sometimes be all it takes…)
Other than the fact that we like high accuracy, a primary beneficiary of this approach is power. When calculations are done externally, the sensor data must be sampled frequently for accuracy. With this part, because the calculation is done externally, the output data rate can be slower – saving power. The calculation itself is in the mA-to-10s-of-mA range on a non-aggressive silicon process node with low leakage.
(Image courtesy Fairchild)
The other trick they’ve managed is dual vacuum. As we discussed when covering Teledyne-DALSA’s MIDIS process, accelerometers like some damping – meaning they need some air in the cavity. Gyroscopes, meanwhile, like a high vacuum for best quality. So the accelerometer and gyro chambers have different vacuum levels, with the gyro chamber including a getter to maintain the low vacuum.
They’re also touting through-silicon vias (TSVs) for a smaller footprint, but they’re not using that yet; they’ve put in place a pathway to TSVs. For now, they’re still using wire bonding.
You can find more info in their announcement.