Blog Review: July 16

Synopsys’ Bradley Geden and Manoz Palaparthi explain the difference between functional signoff and RTL signoff and why increased SoC complexity means that verification flows must now capture both the intent and the integrity of a design before it can move forward.

Cadence’s Frank Ferro finds that LPDDR isn’t just for mobile devices anymore, with the new LPDDR6 standard bringing increased bandwidth, channel performance optimization, and security and reliability features attractive to AI data centers.

Siemens’ Patrick Hope dives into PCB stackup materials and the key characteristics to understand to productively compare alternatives.

Mixel’s Michael Nagib explores the latest advancements in the MIPI D-PHY and MIPI C-PHY specifications, including new equalization options, low power features, and data rate enhancements to support the next generation of high-performance camera and display technologies.

Ansys’ Marc Swinnen and Emily Gerken consider the challenges of analog design at advanced process nodes as smaller geometries lead to closer physical spacing, higher electromagnetic coupling, and higher resistance, which can all make the performance of analog circuits much more sensitive to precise details of the physical layout.

Arm’s Tony Nip introduces a standard approach to measuring and verifying CoreLink Coherent Mesh Network (CMN) interconnect performance using AMBA Viz and performance scripts that enable users to perform sweeping latency and bandwidth queries across CMN nodes and crosspoints.

Keysight’s Akhilesh Daniel finds that the demands of increasing amounts of human and machine communication on the upcoming 6G network will require it to be inherently more energy-efficient across all layers, from the physical layer to components, operations, and applications.

In a blog for SEMI, Agileo Automation’s Fahad Golra traces the evolution of semiconductor equipment automation standards, from the early days of structured communication between manufacturing equipment and host systems to modern approaches that are interoperable, contextual, secure, and scalable.

And don’t miss the blogs featured in the latest Automotive, Security & Enabling Technologies and Test, Measurement & Analytics newsletters:

Rambus’ Maxim Demchenko talks about reducing the number of interfaces used and unifying control protocols for the low-cost edge applications space.

Imagination’s Jakub Przybyl discusses building LLMs that are smaller, faster, and ready for use in resource-limited settings like edge devices.

Synopsys’ Nicolas Amringer and Stefan Pruisken provide insight into safe, efficient, and robust automotive software development in environments where multiple programming languages coexist.

Infineon’s Honey Dhandhukia digs into detecting and interpreting movements or positions with high reliability, even in complex environments.

Siemens’ Shetha Nolke suggests moving in-depth reliability checks to the earliest, most flexible phase of the design flow.

Cadence’s Veena Parthan explains how tiny robots could one day be used for targeted drug delivery and cellular-level disease interventions.

Synaptics’ Neeta Shenoy finds that the ability to process data closer to where it’s generated is a key driver for operational improvement.

Onto Innovation’s Cheolkyu Kim looks at thickness measurements of metal films during RDL and bond pad processes.

proteanTecs’ Alex Burlak finds that strong demand for advanced cloud SoCs powering training and inference is breaking assumptions about how fast the semiconductor market can shift.

Teradyne’s Matthew Griffin explains why the growing adoption of optical interconnects in data centers necessitates high-volume, automated test solutions.

Siemens’ Marc Hutner shows how technology and system complexity drive the need for enhanced fault modeling and detection.

Synopsys’ Guy Cortez details a systematic monitor analytics approach and how it evaluates power and performance of silicon from a small volume of test chips to a high volume of commercial devices.

PDF Solutions’ Jonathan Holt explains how semantic data models help to ensure data completeness and quality across the manufacturing lifecycle.

Advantest’s Roberto Colecchia talks about simplifying, securing, and automating the transfer of device test data between test floors.