When we hear McKinsey & Company, we may think of one of the “Big Three” management consultancies. While that’s true, this firm has a reach and impact that goes far beyond management consulting. According to its website, the firm accelerates sustainable and inclusive growth. While this is an inspirational statement, the… Read More
Artificial Intelligence
Transformers Transforming the Field of Computer Vision
Over the last few years, transformers have been fundamentally changing the nature of deep learning models, revolutionizing the field of artificial intelligence. Transformers introduce an attention mechanism that allows models to weigh the importance of different elements in an input sequence. Unlike traditional deep learning… Read More
Assertion Synthesis Through LLM. Innovation in Verification
Assertion based verification is a very productive way to catch bugs, however assertions are hard enough to write that assertion-based coverage is not as extensive as it could be. Is there a way to simplify developing assertions to aid in increasing that coverage? Paul Cunningham (Senior VP/GM, Verification at Cadence), Raúl … Read More
Fast Path to Baby Llama BringUp at the Edge
Tis the season for transformer-centric articles apparently – this is my third within a month. Clearly this is a domain with both great opportunities and challenges: extending large language model (LLM) potential to new edge products and revenue opportunities, with unbounded applications and volumes yet challenges in meeting… Read More
Cadence Tensilica Spins Next Upgrade to LX Architecture
When considering SoC architectures it is easy to become trapped in simple narratives. These assume the center of compute revolves around a central core or core cluster, typically Arm, more recently perhaps a RISC-V option. Throw in an accelerator or two and the rest is detail. But for today’s competitive products that view is a … Read More
Inference Efficiency in Performance, Power, Area, Scalability
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
Synopsys Expands Synopsys.ai EDA Suite with Full-Stack Big Data Analytics Solution
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
Fitting GPT into Edge Devices, Why and How
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
Anomaly Detection Through ML. Innovation in Verification
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 Inches Up the Infrastructure Value Chain
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
Rapidus, IBM, and the Billion-Dollar Silicon Sovereignty Bet