“Tell me a dark story about a guy who makes pizza with a twist ending”
Those were the first words I ever wrote to ChatGPT. Seriously. I was
testing out this “new chat thing” that was supposedly very good. And
we were all impressed. I read that story aloud to the friends I was
hanging out with that night. We were all so blown away by the details
and intrigue it seemed to pull out of thin air in a matter of
seconds. My prompts and relationship with ChatGPT have come a long way
since then.
A recent post on the PCEA Discord server requested a bit of assistance
using PSPICE models within LTspice. Here's a quick video explaining
how I usually do this!
For reference, this video shows how to download the
PSPICE
model for
the TI LM293
comparator
and import it into
LTspice
. We then set up a
very basic circuit to show functionality.
For many years, I've loved listening to Owl City; this affinity has
carried down to my children who, along with me, particularly enjoy
their latest album. While each song in the album is an excellent story
in its own right, we all like the tale told in The Tornado. This led
to my own recounting of a time, many years ago, when I experienced
some extreme weather while aboard a Coast Guard buoy tender in the
Long Island Sound. The kids, in their own manner of storytelling, have
begun to tell this story as, "the time daddy was inside the middle of
a tornado". While I may not have been in the very center of the storm,
it may be fun to explore some historical data and see how close my
boat was to the actual tornado.
Continuing on the theme of using machine learning to speed up
electromagnetic simulations, we've got some new work to share! This
paper goes beyond the 2D example previously explored and now looks at
full-wave 3D solutions
. Most importantly, we wanted to show that this
is possible with geometry generalizations. For example, many papers
pass things like via drill diameter and other parameters directly as
input to their
neural networks
. We instead mesh the geometry into a 3D
rectangular grid and pass this as input to the
neural network
instead. The result was quite impressive!
Some initial research points to yes, for certain applications. Here's a
preview of a paper I'll be sharing at this year's
IEEE
EMC
+
SIPI
conference in Spokane. There's still a lot of work to be done, and I'm
admittedly quite a
machine learning
amateur. Even so, I think there
are areas in
signal integrity
where we can find smart ways to apply
machine learning
to speed up design cycle time.
A few months ago, I had the wonderful privilege of presenting a
webinar with the great team at Nine Dot Connects (NDC). I've been a
huge fan of NDC ever since I first started learning Altium at my first
job out of undergrad, so I was thrilled to be asked to work with
them. The webinar goes over some important PCB stackup design aspects
which are crucial for successful high-speed digital design.
I recently presented (another) webinar with EMA Design Automation to
discuss
DDR5
! This time the discussion was centered around a live
post-layout demo. In the example, I showed the analysis of a board
with
PowerSI
(which, of course, had some failures when the DDR report
was generated). We then used
S-parameter
and
TDR
analysis to track down
the failures. Lastly, we used the
Clarity
Via Wizard to generate new
via models and we used
Allegro
High-Speed Structures to place them in
the layout. Lastly, the board was verified to show a passing report.
I recently presented a webinar with EMA Design Automation to discuss
DDR5
! I cover the new features added compared to
DDR4
then spend some
time showing a demo of Cadence
Topology Explorer
(
TopXp
) including
simulation of a full byte lane with
IBIS-AMI
models.
We've all been there: you've got a problem to solve and are faced with
the make versus buy decision. In my case, I wanted to switch a USB
peripheral between two PCs; that's the only hard requirement. The
easiest solution would have been to simply add a USB hub to my
KVM switch
and call it a day, but that wouldn't carry USB-3 multi-gigabit
data rates (not that I needed to, but I wanted to).
I love talking about electrical engineering, signal & power integrity, PCB design, electromagnetic simulation or any other topic. Reach out to me any time.
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