Semiconductor test equipment supplier Advantest, working with PDF Solutions, introduced two innovative cloud-based software solutions: the Advantest V93000 Dynamic Parametric Test (DPT) system powered by PDF Exensio DPT, and an edge high performance compute (HPC) system. These solutions are part of the newly introduced Advantest Cloud Solutions (ACS), an ecosystem of cloud-based products and services. At the core of this ecosystem is the data- and analytics-focused platform, Advantest Cloud powered by PDF Exensio, which Advantest is co-developing with PDF Solutions.
Leveraging the core technology developed by PDF Solutions, the data generated from customer workflows is used to provide feedback on processes from semiconductor design validation to manufacturing, chip test, and system-level test. Integrating traditional data silos throughout the semiconductor value chain can significantly improve product quality, manufacturing yield, and cost efficiencies.
The Advantest V93000 Dynamic Parametric Test system powered by PDF Exensio DPT, jointly developed by Advantest and PDF Solutions, adds rule-based, intelligent test flow adaptation to the V93000 SMU8 parametric test platform. With this technology, test flows are automatically optimized on-the-fly within milli-seconds to increase die test coverage, improve the characterization of aberrant measurements, correct equipment issues, and streamline the collection of additional data to support root-cause identification and down-stream analytics.
The new ACS edge HPC product can run complex test workloads with millisecond latencies and is available for early adopters. With pre-configured containers for machine learning (ML), demodulation, or other high-performance workloads, the system makes it easy to implement ML in semiconductor test. Besides allowing users to track, manage, and secure all containers from the cloud, it also provides on-demand access to previous insertion data through application programming interfaces (APIs) with built-in forward and backward data feeds. Customers can deploy machine learning models and algorithms in production, perform in-situ test flow optimizations, and remotely manage highly sensitive IP with maximum security.
