Don’t Let Your Skills Go Stale
Don’t get me wrong - we NEED experts. When everybody on the team is at wit’s end, and the doohickey is still 90 degrees out of phase with the whatchamacallit, causing the franistan to reboot the microkernel and locking up the fritzerator just when it was about to recombobulate, we want to be able to call up the Mighty Casey, who can waltz into the lab, make some grumbling noises, poke around with his 1958 scope probes for a bit, type a few keystrokes, and then announce, “There ya go! Just a simple recalibration of your anhydrous lookup tables and it’s all hunky-dory.”
Yep, we all need that guy sometimes.
But there is a very real long-term downside to actually becoming that guy. It’s a natural tendency among engineers. We’re probably the most curious profession on the planet. When we dive into a topic, we want to understand everything - causes, effects, side effects, corner cases, the whole kit and caboodle. Developing such expertise takes years, even on what might seem like the narrowest of disciplines.
Sending Commands Where Data Publishing Dominates
While watching the unending array of Internet of Things (IoT) discussions, it occurred to me that something important was missing from the conversation.
When we talk about the IoT and all the data and all of the messaging protocols required for sharing the data, we’re talking only about one direction of data flow: sensing, and then transmitting the sensor results somewhere else. But a true automated system – whether home or factory or farm – also involves the reverse: making the edge nodes do something. A world of sensors does little good without accompanying actuators unless all you’re trying to do is publish metrics or analytics.
EDA, Big Data, and Where We Go From Here
Big data: can’t live with it, can’t do anything without it. In this week’s Fish Fry, we look at the growing challenges and opportunities of big data in EDA. My guest is Michael Munsey (Dassault Systemes) and we discuss the future of big data and analytics in EDA, where the biggest big data pain points can be found (and how design tools can help), and why there are so many musicians in electronic engineering. Also this week, we celebrate a kickstarter campaign that brings monthly subscription box services to a whole new “maker” level.
We Attend ESC So You Don’t Have To
At last, I’ve been vindicated. A semi-official study has shown that car alarms are wholly worthless, and that they actually may be a social and economic drain on the community at large. Not surprisingly, 99% of people who hear a blaring car alarm completely ignore it (which obviously defeats the purpose of the alarm), while the few souls who actually do report an alarm to the police don’t do it because they think the car is being stolen. No, they report it as a noise complaint. Even insurance companies, a group famously guided by hard-nosed statistics over mere anecdotal evidence, and with tens of millions of data points to rely upon, treat car alarms as worthless in preventing theft or damage. Worse than useless, in fact. The earsplitting noise just covers the sound of breaking glass, making it actually easier for bad guys to steal the car or its contents. Go figure.
Is the Future All One Thing?
Sometimes, while wrapped up in the day-to-day minutia of technology trends, we can lose sight of the big, slow movements. Underneath the fast-paced, frenetic world of next-node Moore’s Law chaos are some giant trendline tectonic plates - slowly sliding, shifting along fault lines that are barely visible in our normal tech lives.
Let’s fire up our future-facing seismometers and see what electronic bastions are poised to slide off into the ocean when the next “big one” hits.
For the past thirty years, there has been extreme diversity in chips and in chip makers. We have processor companies making processors, of course; memory companies, microcontroller companies, FPGA companies, analog companies, RF companies, interface companies - every specialized type of chip hosts a mini-market of semiconductor specialists, competing for points of market share in their own little tightly-walled technology arena.
Silicon Cloud, IBM Give It a Go
Four years ago, EDA in the Cloud was cool. Since then, it seems to have, well, cooled off. Until recently: it’s once more showing signs of heating up in an attempt to become cool again.
Cloud computing has always been problematic for EDA. Anything requiring the transfer of company jewels into unknown hands has too often been a deal breaker. The noise made by Synopsys and Cadence several years ago has noticeably subsided. OneSpin added a cloud capability, but only by promising not to send design information into the cloud – only abstracted proof requests.