- The platform enables long-duration waveform compression, high-resolution playback and analysis
- It shortens analysis time in pre-silicon validation with patented machine learning algorithms that identify anomalies and outliers
Keysight Technologies has announced the launch of PathWave Waveform Analytics. It is an edge-to-cloud computing application that will improve anomaly detection and reduces data storage costs in pre-silicon validation using machine learning algorithms.
The automotive, IoT and mobile devices markets are growing rapidly. The markets need to leverage design thinking and innovative technology to enable semiconductor design engineers to quickly develop products that are robust, reliable, and secure against malicious intrusions while reducing power consumption.
Long-duration waveform compression
The company said that its PathWave Waveform Analytics is an advanced analytics software solution that includes a new data compression technology. It claimed that the platform enables long-duration waveform compression, high-resolution playback, and analysis exceeding several terabytes of data. Its built-in machine learning improves the discovery of voltage and current anomalies and transient trends captured by the waveforms.
Christopher Cain, vice president, and general manager of Keysight’s Electronic Industrial Products said, “Highly power-efficient semiconductors require robust, reliable, and secure analytics during design qualification. 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.”
The company said that the platform shortens analysis time in pre-silicon validation with patented machine learning algorithms that identify anomalies and outliers. It reduces overall project costs by debugging in pre-silicon, which saves time in the costly post-silicon validation phase. Keysight also claimed that the platform improves design reliability with pre-and post-processing algorithms that accurately detect voltage and current spikes on power and signal waveforms.
Identify outlier waveform shapes
Keysights said that its PathWave Waveform Analytics will enable designers to identify outlier waveform shapes via high-level view into clustering results. It will analyse data in high resolution with hierarchical clustering for multi-level drill down. It will also analyse any portion of the big vector data or waveform that was captured and stored and respond quickly so that minimum data is transferred between the edge computer and the server.
The company said that it will help designers to view an unlimited number of channels on a single dashboard, with options to pin or move the waveform in the interested channel for comparison. It will also equip them to perform multiple dimensional comparisons and fine-tune the waveforms for analysis.
