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Artificial Intelligence
Support for AI at the edge has prompted a good deal of innovation in accelerators, initially in CNNs, evolving to DNNs and RNNs (convolutional neural nets, deep neural nets, and recurrent neural nets). Most recently, the transformer technology behind the craze in large language models is proving to have important relevance at… Read More
More than two years ago, Synopsys launched its AI-driven design space optimization (DSO.ai) capability. It is part of the company’s Synopsys.ai EDA suite, an outcome of its overarching AI initiative. Since then, DSO.ai has boosted designer productivity and has been leveraged for 270 production tape-outs. DSO.ai uses machine… Read More
It is tempting to think that everything GPT-related is just chasing the publicity bandwagon and that articles on the topic, especially with evidently impossible claims (as in this case), are simply clickbait. In fact, there are practical reasons for hosting at least a subset of these large language models (LLMs) on edge devices… Read More
Assertion based verification only catches problems for which you have written assertions. Is there a complementary approach to find problems you haven’t considered – the unknown unknowns? Paul Cunningham (Senior VP/GM, Verification at Cadence), Raúl Camposano (Silicon Catalyst, entrepreneur, former Synopsys CTO and now… Read More
Arm just revealed at HotChips their compute subsystems (CSS) direction led by CSS N2. The intent behind CSS is to provide pre-integrated, optimized and validated subsystems to accelerate time to market for infrastructure system builders. Think HPC servers, wireless infrastructure, big edge systems for industry, city, enterprise… Read More
The various algorithms that comprise artificial intelligence (AI) are finding their way into the chip design flow. What is driving a lot of this work is the complexity explosion of new chip designs required to accelerate advanced AI algorithms. It turns out AI is both the problem and the solution in this case. AI can be used to cut … Read More
The automotive industry is undergoing a major transformation. The convergence of electrification, connectivity, driver-assistance technologies, and software-defined vehicles has led to the rise of use of advanced System-on-Chips (SoCs) that drive unprecedented levels of functionality and performance. However, this… Read More
In the rapidly evolving landscape of artificial intelligence (AI), the concept of machine unlearning has emerged as a fascinating and crucial area of research. While the traditional paradigm of AI focuses on training models to learn from data and improve their performance over time, the notion of unlearning takes a step further… Read More
Semiconductor industry is going through an unprecedented technological revolution with AI/ML, GPU, RISC-V, chiplets, automotive and 5G driving the hardware design innovation. The race to deliver high performance, optimizing power and area (PPA), while ensuring safety and security is truly on. It has never been a more exciting… Read More
Artificial Intelligence (AI) has witnessed explosive growth in applications across various industries, ranging from autonomous vehicles and natural language processing to computer vision and robotics. The AI embedded semiconductor market is projected to reach $800 billion by year 2030. Compare this with just $48 billion… Read More
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