DEVELOPING INNOVATIVE STRATEGIES WITH
MACHINE LEARNING
For over a three decades I’ve been working to help companies improve their products through design optimization and automation. By leveraging the emerging tools in machine learning, I can help you solve previously intractable problems. Get in touch today to transform your products.
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When choosing which memories to include on a silicon chip, there can be trillions upon trillions of permutations. This is where machines have a clear advantage over humans in their ability to process massive data.
Even the best human's will leave 20% or more on the table.
With memory selection optimization you will get the absolute best memories for your desired area-power tradeoff.
MEMORY SELECTION
PREDICTIVE MODELING
The backbone of a good optimization or selection system are accurate estimation models.
Knowledge and practice of modern regression and classification machine learning algorithms as well as best practices such as feature engineering, dimensionality reduction, cross-validation, and out of sample testing are critical in developing these models.
OPTIMIZATION & AUTOMATION
Other examples of preventing over design (and thereby leaving profit behind) include:
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Redundancy selection for optimal yield-area tradeoff
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Monte carlo methods for quantifying internal circuit margins
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Best in class characterization flows