When To Expect Domain-Specific AI Chips


The chip industry is moving toward domain-specific computation, while artificial intelligence (AI) is moving in the opposite direction, creating a gap that could force significant changes in how chips and systems are architected in the future. Behind this split is the amount of time it takes to design hardware and software. In the 18 months since ChatGPT was launched on the world, there has ... » read more

Will Domain-Specific ICs Become Ubiquitous?


Questions are surfacing for all types of design, ranging from small microcontrollers to leading-edge chips, over whether domain-specific design will become ubiquitous, or whether it will fall into the historic pattern of customization first, followed by lower-cost, general-purpose components. Custom hardware always has been a double-edged sword. It can provide a competitive edge for chipmake... » read more

Re-architecting Hardware For Energy


A lot of effort has gone into the power optimization of a system based on the RTL created, but that represents a small fraction of the possible power and energy that could be saved. The industry's desire to move to denser systems is being constrained by heat, so there is an increasing focus on re-architecting systems to reduce the energy consumed per useful function performed. Making signifi... » read more

Startup Funding: March 2023


Funding was broadly spread between sectors in March, with automotive edging ahead thanks to a more than $100 million round for a company manufacturing electric, autonomous heavy commercial trucks for freight logistics. To keep up with the amount of information presented by cars and ADAS, several companies raised funds for head-up displays with increasing levels of detail and expanded fields of ... » read more

A Hierarchical And Tractable Mixed-Signal Verification Methodology For First-Generation Analog AI Processors


Artificial intelligence (AI) is now the key driving force behind advances in information technology, big data and the internet of things (IoT). It is a technology that is developing at a rapid pace, particularly when it comes to the field of deep learning. Researchers are continually creating new variants of deep learning that expand the capabilities of machine learning. But building systems th... » read more

Week In Review: Design, Low Power


Arm is expected to list solely on a U.S. stock exchange when it goes public again later this year, forgoing the London Stock Exchange for now, the BBC reports. Global investment banks expect the offering to value the company between $30 billion and $70 billion, according to Bloomberg. Disaggregating chips into specialized processors, memories, and architectures is becoming necessary for cont... » read more

A Hierarchical And Tractable Mixed-Signal Verification Methodology For First-Generation Analog AI Processors


Artificial intelligence (AI) is now the key driving force behind advances in information technology, big data and the internet of things (IoT). It is a technology that is developing at a rapid pace, particularly when it comes to the field of deep learning. Researchers are continually creating new variants of deep learning that expand the capabilities of machine learning. But building systems th... » read more

Bug-Free Designs


It is possible in theory to create a design with no bugs, but it's impractical, unnecessary, and extremely difficult to prove for bugs you care about. The problem is intractable because the potential state space is enormous for any practical design. The industry has devised ways to handle this complexity, but each has limitations, makes assumptions, and employs techniques that abstract the p... » read more

Foundational Changes In Chip Architectures


We take many things in the semiconductor world for granted, but what if some of the decisions made decades ago are no longer viable or optimal? We saw a small example with finFETs, where the planar transistor would no longer scale. Today we are facing several bigger disruptions that will have much larger ripple effects. Technology often progresses in a linear fashion. Each step provides incr... » read more

Rethinking Machine Learning For Power


The power consumed by machine learning is exploding, and while advances are being made in reducing the power consumed by them, model sizes and training sets are increasing even faster. Even with the introduction of fabrication technology advances, specialized architectures, and the application of optimization techniques, the trend is disturbing. Couple that with the explosion in edge devices... » read more

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