eFPGA Architectural Improvements That Lower Test Cost And Increase Quality


More than 40 chips have been licensed to use EFLX eFPGA and >20 chips are working in silicon. Big customers like Renesas are planning high volume families of chips using embedded FPGA. As a result, we have gained extensive experience and knowledge in almost 10 years of doing eFPGA especially in production test for cost reduction and reliability improvement. eFPGA DFT and MBIST for high q... » read more

How Much AI Is Really Needed?


Tensor Core GPUs have created a generative AI model gold rush. Whether it’s helping students with math homework, planning a vacation, or learning to prepare a six-course meal, generative AI is ready with answers. But that's only one aspect of AI, and not every application requires it. AI — now an all-inclusive term, referring to the process of using algorithms to learn, predict, and make... » read more

The Challenge And Value Proposition of eFPGA Emulation


More than 40 chips have been licensed to use EFLX eFPGA and more than 20 chips are already working in silicon. Big customers like Renesas are planning high volumes and families of chips using eFPGA. eFPGA is being used in process nodes from 180nm to 5nm, with 3nm and 18A in evaluation. Especially for the high-volume customers working in advanced finFET nodes, the strong need is for first ... » read more

Taking eFPGA Security To The Next Level


Security is an important topic for every SOC, but it’s especially salient in the context of high-risk assets included in the eFPGA for obfuscation. Whether the device is used in defense systems or in cars driving around town, encryption is important so the device remains secure and can’t be modified maliciously, whether through physical attacks or remote hacking. There are several different... » read more

Chip Industry Week In Review


By Jesse Allen, Karen Heyman, and Liz Allan The U.S. Department of Defense (DOD) announced $238 million in awards toward establishing eight regional innovation hubs under the CHIPS and Science Act. The hubs aim to accelerate hardware prototyping and "lab-to-fab" transition of semiconductor technologies for secure edge/IoT, 5G/6G, AI hardware, quantum technology, electromagnetic warfare, and ... » read more

Patterns And Issues In AI Chip Design


AI is becoming more than a talking point for chip and system design, taking on increasingly complex tasks that are now competitive requirements in many markets. But the inclusion of AI, along with its machine learning and deep learning subcategories, also has injected widespread confusion and uncertainty into every aspect of electronics. This is partly due to the fact that it touches so many... » read more

Use Cases And Value Proposition Of eFPGA


Flex Logix EFLX eFPGA is the first eFPGA that enables a customer to match the performance of FPGAs from AMD/Xilinx and Intel (in the same process node) with the same density (LUTs/mm2). EFLX eFPGA has been in use with customers now for more than 5 years, hardware and software. More than 40 chips have been licensed to use EFLX eFPGA and more than 20 chips are working in silicon. Big customers... » read more

Chiplets: Deep Dive Into Designing, Manufacturing, And Testing


Chiplets are a disruptive technology. They change the way chips are designed, manufactured, tested, packaged, as well as the underlying business relationships and fundamentals. But they also open the door to vast new opportunities for existing chipmakers and startups to create highly customized components and systems for specific use cases and market segments. This LEGO-like approach sounds ... » read more

Tradeoffs In DSP Design


More intelligence is now required in the front-, mid-, and back-haul for 5G/6G communication, requiring a mix of high performance, low power, and enough flexibility to accommodate constantly changing protocols and algorithms. One solution to these conflicting goals involves reconfigurable DSPs, in which the processing element is hardwired like an ASIC but still configurable for a variety of app... » read more

AI Transformer Models Enable Machine Vision Object Detection


The object detection required for machine vision applications such as autonomous driving, smart manufacturing, and surveillance applications depends on AI modeling. The goal now is to improve the models and simplify their development. Over the years, many AI models have been introduced, including YOLO, Faster R-CNN, Mask R-CNN, RetinaNet, and others, to detect images or video signals, interp... » read more

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