editor's blog
Subscribe Now

Algorithms or Methodologies?

You see it two to four times a year from each EDA player: “x% Productivity Gains with y Tool!” Cadence recently had such an announcement with their Incisive tool; Synopsys has just had a similar story with FineSim.

As I was talking with the Cadence folks about this, I wondered: How much of this productivity gain comes as a result of engine/algorithm improvements, and how much as a result of methodology changes? The answer is, of course, that it comes from both.

But there’s a difference in when the benefits accrue. Engine improvements are immediately visible when you run the tool. Methodology changes: not so much. And there are actually two aspects to methodology.

The first is that, of course, a new methodology requires training and getting used to. So the first project done using a new methodology will take longer; the next one should be better because everyone is used to the new way of doing things. This is a reasonably well-known effect.

But there may be an extra delayed benefit: some methodology changes require new infrastructure or have a conversion cost. If, for example, you replace some aspect of simulation with a new formal tool, you have to modify your testbench and create the new test procedure from scratch. There may be, for instance, numerous pieces of IP that need to be changed to add assertions. These are largely one-time investments, with incremental work required on follow-on projects.

In this example, it may be that, even with the conversion work, things go faster even on the first project. But productivity will be even better next time, when much of the infrastructure and changes are ready and waiting.

As to the engines, I was talking to the folks at Mentor yesterday, and wondered whether improvements to the tools themselves become asymptotic: does there come a point when you just can’t go any faster? Their answer was, “No,” since there’s always some bottleneck that didn’t used to be an issue until the other bigger bottlenecks got fixed. The stuff that got ignored keeps bubbling up in priority, the upshot being that there’s always something that can be improved to speed up the tools.

Leave a Reply

featured blogs
Dec 19, 2024
Explore Concurrent Multiprotocol and examine the distinctions between CMP single channel, CMP with concurrent listening, and CMP with BLE Dynamic Multiprotocol....
Dec 24, 2024
Going to the supermarket? If so, you need to watch this video on 'Why the Other Line is Likely to Move Faster' (a.k.a. 'Queuing Theory for the Holiday Season')....

featured video

Introducing FPGAi – Innovations Unlocked by AI-enabled FPGAs

Sponsored by Intel

Altera Innovators Day presentation by Ilya Ganusov showing the advantages of FPGAs for implementing AI-based Systems. See additional videos on AI and other Altera Innovators Day in Altera’s YouTube channel playlists.

Learn more about FPGAs for Artificial Intelligence here

featured chalk talk

SiC-Based High-Density Industrial Charger Solutions
Sponsored by Mouser Electronics and onsemi
In this episode of Chalk Talk, Amelia Dalton and Prasad Paruchuri from onsemi explore the benefits of silicon carbide based high density industrial charging solutions. They investigate the topologies of Totem Pole PFC and Half Bridge LLC circuits, the challenges that bidirectional CLLC resonant DC-DC converters are solving today, and how you can take advantage of onsemi’s silicon carbide charging solutions for your next design.
May 21, 2024
37,625 views