Using AI To Glue Disparate IC Ecosystem Data


AI holds the potential to change how companies interact throughout the global semiconductor ecosystem, gluing together different data types and processes that can be shared between companies that in the past had little or no direct connections. Chipmakers always have used abstraction layers to see the bigger picture of how the various components of a chip go together, allowing them to pinpoi... » read more

RAG-Enabled AI Stops Hallucinations, Adds Sources


Many EDA companies have taken the first steps to incorporate generative AI into their tools, and in such tightly controlled environments GenAI appears to have great benefits. But its broader adoption has been delayed by its notorious inaccuracy, giving results that are often out of date, untrue, and unsourced. That's starting to change. GenAI is evolving so rapidly that these kinds of proble... » read more

HBM4 Feeds Generative AI’s Hunger For More Memory Bandwidth


Generative AI (Gen AI), built on the exponential growth of Large Language Models (LLMs) and their kin, is one of today’s biggest drivers of computing technology. Leading-edge LLMs now exceed a trillion parameters and offer multimodal capabilities so they can take a broad range of inputs, whether they’re in the form of text, speech, images, video, code, and more, and generate an equally broa... » read more

New AI Processors Architectures Balance Speed With Efficiency


Leading AI systems designs are migrating away from building the fastest AI processor possible, adopting a more balanced approach that involves highly specialized, heterogeneous compute elements, faster data movement, and significantly lower power. Part of this shift revolves around the adoption of chiplets in 2.5D/3.5D packages, which enable greater customization for different workloads and ... » read more

Memory Implications Of Gen AI In Gaming


The global gaming market across hardware, software and services is on track to exceed annual revenues of $500B in 2025.1 That’s bigger by an order of magnitude than the combination of movies and music. On the cutting edge of that enormous market is open world gaming, where the driving goal is to give players the freedom to do anything they can imagine in a coherent and immersive environment. ... » read more

Prevent AI Hardware Obsolescence And Optimize Efficiency With eFPGA Adaptability


Large Language Models (LLMs) and Generative AI are driving up memory requirements, presenting a significant challenge. Modern LLMs can have billions of parameters, demanding many gigabytes of memory. To address this issue, AI architects have devised clever solutions that dramatically reduce memory needs. Evolving techniques like lossless weight compression, structured sparsity, and new numer... » read more

Capturing Knowledge Within LLMs


At DAC this year, there was a lot of talk about AI and the impact it is likely to have. While EDA companies have been using it for optimization and improving iteration loops within the flow, the end users have been concentrating on how to use it to improve the user interface between engineers and tools. The feedback is very positive. Large language models (LLMs) have been trained on a huge a... » read more

Will AI Disrupt EDA?


Generative AI has disrupted search, it is transforming the computing landscape, and now it's threatening to disrupt EDA. But despite the buzz and the broad pronouncements of radical changes ahead, it remains unclear where it will have impact and how deep any changes will be. EDA has two primary roles — automation and optimization. Many of the optimization problems are NP hard, which means ... » read more

PCIe 7.0: Speed, Flexibility & Efficiency For The AI Era


As the industry came together for PCI-SIG DevCon last month, one thing took center stage, and that was PCI Express 7.0. While still in the final stages of development, the world is certainly ready for this significant new milestone of the PCIe specification. Let’s look at how PCIe 7.0 is poised to address the escalating demands of AI, high-performance computing, and emerging data-intensive ap... » read more

Chip Design Digs Deeper Into AI


Growing demand for blazing fast and extremely dense multi-chiplet systems are pushing chip design deeper into AI, which increasingly is viewed as the best solution for sifting through scores of possible configurations, constraints, and variables in the least amount of time. This shift has broad implications for the future of chip design. In the past, collaborations typically involved the chi... » read more

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