De-Risking High-Speed RF Designs from Electromagnetic Crosstalk Issue

De-Risking High-Speed RF Designs from Electromagnetic Crosstalk Issue
by Mike Gianfagna on 02-12-2020 at 6:00 am

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At DesignCon 2020, ANSYS sponsored a series of very high-quality presentations.  Some focused on advanced methods and new technology exploration and some provided head-on, practical and actionable capabilities to improve advanced designs. The presentation I will discuss here falls into the latter category. The topic was… Read More


It’s The Small Stuff That Gets You …

It’s The Small Stuff That Gets You …
by Mike Gianfagna on 02-10-2020 at 6:00 am

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The last session I attended at DesignCon 2020 wasn’t a session at all. Rather it was an interactive discussion with Todd Westerhoff, product manager for electronic board systems at Mentor Graphics. Todd made some observations about the way high-performance PCBs are designed today and perhaps the way they should be designed. … Read More


Platform ASICs Target Datacenters, AI

Platform ASICs Target Datacenters, AI
by Bernard Murphy on 07-17-2018 at 7:00 am

There is a well-known progression in the efficiency of different platforms for certain targeted applications such as AI, as measured by performance and performance/Watt. The progression is determined by how much of the application can be run with specialized hardware-assist rather than software, since hardware can be faster… Read More


More Than Your Average IP Development Kit

More Than Your Average IP Development Kit
by Bernard Murphy on 02-13-2018 at 7:00 am

When I think of an IP development kit, I imagine software plus a hardware model I can run on a prototyper or, closer to the kits offered by semi companies, software plus a board hosting an FPGA implementation of the IP along with DDR memory, flash and a variety of interfaces. These approaches work well for IP providers because hardware… Read More


DSP-Based Neural Nets

DSP-Based Neural Nets
by Bernard Murphy on 10-24-2017 at 7:00 am

You may be under the impression that anything to do with neural nets necessarily runs on a GPU. After all, NVIDIA dominates a lot of what we hear in this area, and rightly so. In neural net training, their solutions are well established. However, GPUs tend to consume a lot of power and are not necessarily optimal in inference performance… Read More


Embedding FPGA IP

Embedding FPGA IP
by Bernard Murphy on 09-05-2017 at 7:00 am

The appeal of embedding an FPGA IP in an ASIC design is undeniable. For much of your design, you want all the advantages of ASIC: up to GHz performance, down to mW power (with active power management), all with very high levels of integration with a broad range of internal and 3[SUP]rd[/SUP]-party IP (analog/RF, sensor fusion, image/voice… Read More