New Strategies For Interpreting Data Variability


Every measurement counts at the nanoscopic scale of modern semiconductor processes, but with each new process node the number of measurements and the need for accuracy escalate dramatically. Petabytes of new data are being generated and used in every aspect of the manufacturing process for informed decision-making, process optimization, and the continuous pursuit of quality and yield. Most f... » read more

Paradigms Of Large Language Model Applications In Functional Verification


This paper presents a comprehensive literature review for applying large language models (LLM) in multiple aspects of functional verification. Despite the promising advancements offered by this new technology, it is essential to be aware of the inherent limitations of LLMs, especially hallucination that may lead to incorrect predictions. To ensure the quality of LLM outputs, four safeguarding p... » read more

Cache Coherency In Heterogeneous Systems


Until recently, coherency was something normally associated with DRAM. But as chip designs become increasingly heterogeneous, incorporating more and different types of compute elements, it becomes harder to maintain coherency in that data without taking a significant hit on performance and power. The basic problem is that not all compute elements fetch and share data at the same speed, and syst... » read more

The Data Crisis Is Unfolding — Are We Ready?


The rapid advancement of technology has led to an unprecedented amount of data being generated, captured, and consumed globally. However, this reliance on data comes at a considerable cost. The widespread sharing and processing of data is necessary to navigate our everyday lives. Still, any disruption to this process can have severe consequences, threatening our ability to function as a society... » read more

Designing AI Hardware To Deal With Increasingly Challenging Memory Wall (UC Berkeley)


A new technical paper titled "AI and Memory Wall" was published by researchers at UC Berkeley, ICSI, and LBNL. Abstract "The availability of unprecedented unsupervised training data, along with neural scaling laws, has resulted in an unprecedented surge in model size and compute requirements for serving/training LLMs. However, the main performance bottleneck is increasingly shifting to memo... » read more

The Implications Of AI Everywhere: From Data Center To Edge


Generative AI has upped the ante on the transformative force of AI, driving profound implications across all aspects of our everyday lives. Over the past year, we have seen AI capabilities placed firmly in the hands of consumers. The recent news and product announcements emerging from MWC 2024 highlighted what we can expect to see from the next wave of generative AI applications. AI will be eve... » read more

AI/ML Challenges In Test and Metrology


The integration of artificial intelligence and machine learning (AI/ML) into semiconductor test and metrology is redefining the landscape for chip fabrication, which will be essential at advanced nodes and in increasingly dense advanced packages. Fabs today are inundated by vast amounts of data collected across multiple manufacturing processes, and AI/ML solutions are viewed as essential for... » read more

AI Performance And Real-Time Control In Robotics And Autonomous Applications


Recent vision AI models have to deal with dynamic and complex environments, resulting in the need for more power efficiency and speed in real-time applications. To meet the market needs, Renesas released the next-generation Dynamically Reconfigurable Processor for AI (DRP-AI) accelerator. The DRP-AI accelerator delivers high-power efficiency of 10 TOPS/W, up to 10 times higher than the conve... » read more

HBM3E And GDDR6: Memory Solutions For AI


AI/ML changes everything, impacting every industry and touching the lives of everyone. With AI training sets growing at a pace of 10X per year, memory bandwidth is a critical area of focus as we move into the next era of computing and enable this continued growth. AI training and inference have unique feature requirements that can be served by tailored memory solutions. Learn how HBM3E and G... » read more

Brain-Inspired, Silicon Optimized


The 2024 International Solid State Circuits Conference was held this week in San Francisco. Submissions were up 40% and contributed to the quality of the papers accepted and the presentations given at the conference. The mood about the future of semiconductor technology was decidedly upbeat with predictions of a $1 trillion industry by 2030 and many expecting that the soaring demand for AI e... » read more

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