Reducing Power In Data Centers


The rollout of generative AI, coupled with more data in general, is requiring data centers to run servers harder and longer. That, in turn, is generating more heat and accelerating aging, and to ensure these systems continue working over their projected lifetimes, chipmakers are building extra margin into chips. That increases the amount of energy required to run and cool them, and it can short... » read more

Modeling Compute In Memory With Biological Efficiency


The growing popularity of generative AI, which uses natural language to help users make sense of unstructured data, is forcing sweeping changes in how compute resources are designed and deployed. In a panel discussion on artificial intelligence at last week’s IEEE Electron Device Meeting, IBM’s Nicole Saulnier described it as a major breakthrough that should allow AI tools to assist huma... » read more

The Evolution Of Generative AI Up To The Model-Driven Era


Generative AI has become a buzzword in 2023 with the explosive proliferation of ChatGPT and large language models (LLMs). This brought about a debate about which is trained on the largest number of parameters. It also expanded awareness of the broader training of models for specific applications. Therefore, it is unsurprising that an association has developed between the term “Generative AI�... » read more

Considerations For Accelerating On-Device Stable Diffusion Models


One of the more powerful – and visually stunning – advances in generative AI has been the development of Stable Diffusion models. These models are used for image generation, image denoising, inpainting (reconstructing missing regions in an image), outpainting (generating new pixels that seamlessly extend an image's existing bounds), and bit diffusion. Stable Diffusion uses a type of dif... » read more

Applications Of Large Language Models For Industrial Chip Design (NVIDIA)


A technical paper titled “ChipNeMo: Domain-Adapted LLMs for Chip Design” was published by researchers at NVIDIA. Abstract: "ChipNeMo aims to explore the applications of large language models (LLMs) for industrial chip design. Instead of directly deploying off-the-shelf commercial or open-source LLMs, we instead adopt the following domain adaptation techniques: custom tokenizers, domain-ad... » read more

Unlocking The Power Of Edge Computing With Large Language Models


In recent years, Large Language Models (LLMs) have revolutionized the field of artificial intelligence, transforming how we interact with devices and the possibilities of what machines can achieve. These models have demonstrated remarkable natural language understanding and generation abilities, making them indispensable for various applications. However, LLMs are incredibly resource-intensi... » read more

AI For Circuit Design Quality, Productivity, And Advanced-Node Mapping


The future of circuit design, encompassing analog, RF/5G, and custom electronic circuits, is set to be revolutionized by the integration of generative AI tools. These advanced tools will not only enhance the quality of designs and boost designer productivity but also facilitate the mapping of designs from older semiconductor process nodes to more advanced nodes such as 3nm and below. This blog ... » 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

Unleashing The Power Of Generative AI In Chip, System, And Product Design


The field of chip, system, and product design is a complex landscape, fraught with challenges that designers grapple with daily. The traditional design process, while robust, often falls short in addressing the increasing demands for efficiency, customization, and innovation. This white paper delves into these challenges, exploring the transformative potential of generative artificial int... » read more

Sweeping Changes For Leading-Edge Chip Architectures


Chipmakers are utilizing both evolutionary and revolutionary technologies to achieve orders of magnitude improvements in performance at the same or lower power, signaling a fundamental shift from manufacturing-driven designs to those driven by semiconductor architects. In the past, most chips contained one or two leading-edge technologies, mostly to keep pace with the expected improvements i... » read more

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