Keysight Technologies introduced PathWave Waveform Analytics, an edge-to-cloud computing application that improves anomaly detection and reduces data storage costs in pre-silicon validation using machine learning algorithms.
Keysight’s PathWave Waveform Analytics software solution includes a new data compression technology that enables long-duration waveform compression, high resolution playback and analysis exceeding several terabytes of data. Built-in machine learning improves the discovery of voltage and current anomalies, as well as transient trends captured by the waveforms.
Highlights
- Shortens analysis time in pre-silicon validation with patented machine learning algorithms that identify anomalies and outliers
- Reduces overall project costs by debugging in pre-silicon, which saves time in the costly post-silicon validation phase
- Improves design reliability with pre-and post-processing algorithms that accurately detect voltage and current spikes on power and signal waveforms
“Highly power-efficient semiconductors require robust, reliable and secure analytics during design qualification,” said Christopher Cain, vice president and general manager of Keysight’s Electronic Industrial Products. “Keysight’s innovative big-data waveform analytics solutions enable those semiconductor designers to automate design analysis, improving productivity of those tasks by up to 90 percent, thus accelerating their companies’ time-to-market opportunity.”
