AI Power Consumption Exploding


Machine learning is on track to consume all the energy being supplied, a model that is costly, inefficient, and unsustainable. To a large extent, this is because the field is new, exciting, and rapidly growing. It is being designed to break new ground in terms of accuracy or capability. Today, that means bigger models and larger training sets, which require exponential increases in processin... » read more

The Challenge Of Optimizing Chip Architectures For Workloads


It isn't possible to optimize a workload running on a system just by looking at hardware or software separately. They need to be developed together and intricately intertwined, an engineering feat that also requires bridging two worlds with have a long history of operating independently. In the early days of computing, hardware and software were designed and built by completely separate team... » read more

Is Programmable Overhead Worth The Cost?


Programmability has fueled the growth of most semiconductor products, but how much does it actually cost? And is that cost worth it? The answer is more complicated than a simple efficiency formula. It can vary by application, by maturity of technology in a particular market, and in the context of much larger systems. What's considered important for one design may be very different for anothe... » read more

Startup Funding: July 2021


The trend of big funding for Chinese autonomous driving companies continued in July, with three startups each drawing $100M or more for efforts in ADAS and computer vision for automotive. The month also saw one electric vehicle manufacturer get a massive boost as it begins production on its first models, while significant funding also went to a company that wants to recycle used up EV batteries... » read more

Architectural Considerations For AI


Custom chips, labeled as artificial intelligence (AI) or machine learning (ML), are appearing on a weekly basis, each claiming to be 10X faster than existing devices or consume 1/10 the power. Whether that is enough to dethrone existing architectures, such as GPUs and FPGAs, or whether they will survive alongside those architectures isn't clear yet. The problem, or the opportunity, is that t... » read more

Domain-Specific Memory


Domain-specific computing may be all the rage, but it is avoiding the real problem. The bigger concern is the memories that throttle processor performance, consume more power, and take up the most chip area. Memories need to break free from the rigid structures preferred by existing software. When algorithms and memory are designed together, improvements in performance are significant and pr... » read more

Firmware Skills Shortage


Good hardware without good software is a waste of silicon, but with so many new processors and accelerator architectures being created, and so many new skills required, companies are finding it hard to hire enough engineers with low-level software expertise to satisfy the demand. Writing compilers, mappers and optimization software does not have the same level of pizazz as developing new AI ... » read more

Von Neumann Is Struggling


In an era dominated by machine learning, the von Neumann architecture is struggling to stay relevant. The world has changed from being control-centric to one that is data-centric, pushing processor architectures to evolve. Venture money is flooding into domain-specific architectures (DSA), but traditional processors also are evolving. For many markets, they continue to provide an effective s... » read more

Startup Funding: July 2020


A number of semiconductor and design companies took in funding this month, from a mega round for a data center switch maker to seed grants for two Canadian companies and new funding for an IP marketplace. China continues to be a hot area for electric vehicles, with one company raising half a billion for its two models currently in production. For July, we highlight fifteen startups that raised ... » read more

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