RISC-V Wants All Your Cores


RISC-V is no longer content to disrupt the CPU industry. It is waging war against every type of processor integrated into an SoC or advanced package, an ambitious plan that will face stiff competition from entrenched players with deep-pocketed R&D operations and their well-constructed ecosystems. When Calista Redmond, CEO for RISC-V International, said at last year's summit that RISC-V w... » read more

Week In Review: Design, Low Power


Arm filed its registration statement for a highly anticipated IPO. Chip industry heavyweights Apple, Samsung, NVIDIA, and Intel are all expected to invest. Find the SEC filing here. Taiwan’s National Science and Technology Council (NSTC) laid out a 10-year initiative to bolster its IC design market share to 40% worldwide by 2033, with the first year’s budget of US $376 million. The sh... » 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

SW-HW Framework: Graphic Rendering on RISC-V GPUs (Georgia Tech, Cal Poly)


A new technical paper titled "Skybox: Open-Source Graphic Rendering on Programmable RISC-V GPUs" was published by researchers at Georgia Tech, California Polytechnic State University-San Luis Obispo. Abstract Excerpt: "In this work, we present Skybox, a full-stack open-source GPU architecture with integrated software, compiler, hardware, and simulation environment, that enables end-to-end G... » read more

Complex Tradeoffs In Inferencing Chips


Designing AI/ML inferencing chips is emerging as a huge challenge due to the variety of applications and the highly specific power and performance needs for each of them. Put simply, one size does not fit all, and not all applications can afford a custom design. For example, in retail store tracking, it's acceptable to have a 5% or 10% margin of error for customers passing by a certain aisle... » read more

New Uses For AI In Chips


Artificial intelligence is being deployed across a number of new applications, from improving performance and reducing power in a wide range of end devices to spotting irregularities in data movement for security reasons. While most people are familiar with using machine learning and deep learning to distinguish between cats and dogs, emerging applications show how this capability can be use... » read more

What Future Processors Will Look Like


Mark Papermaster, CTO at AMD, sat down with Semiconductor Engineering to talk about architectural changes that are required as the benefits of scaling decrease, including chiplets, new standards for heterogeneous integration, and different types of memory. What follows are excerpts of that conversation. SE: What does a processor look like in five years? Is it a bunch of chips in a package? I... » read more

New End Markets, More Demand For Complex Chips


Experts at the Table: Semiconductor Engineering sat down to discuss economic conditions and how that affects chip design with Anirudh Devgan, president and CEO of Cadence; Joseph Sawicki, executive vice president of Siemens EDA; Niels Faché, vice president and general manager at Keysight; Simon Segars, advisor at Arm; and Aki Fujimura, chairman and CEO of D2S. This discussion was held in front... » read more

Choosing Which Tasks To Optimize In Chips


The optimization of one or more tasks is an important aspect of every SoC created, but with so many options now on the table it is often unclear which is best. Just a few years ago, most people were happy to buy processors from the likes of Intel, AMD and Nvidia, and IP cores from Arm. Some even wanted the extensibility that came from IP cores like Tensilica and ARC. Then, in 2018, John Henn... » read more

Using GPUs In Semiconductor Manufacturing


Massive simulation and curvilinear shapes are forcing the photomask industry to rethink what types of chips work best. Aki Fujimura, CEO of D2S, talks about what happens when shapes printed on a mask are closer to what actually gets printed, how GPUs can be used to accelerate CPUs in single instruction/multiple data (SIMD) operations, and why pixel data is different from other data. » read more

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