tag: AI

Advanced Packaging’s Next Wave
By Mark LaPedus - 20 May, 2021 - Comments: 0

Packaging houses are readying the next wave of advanced packages, enabling new system-level chip designs for a range of applications. These advanced packages involve a range of technologies, such as 2.5D/3D, chiplets, fan-out and system-in-package (SiP). Each of these, in turn, offers an array of options for assembling and integrating complex dies in an advanced package, providing chip custo... » read more

Power Optimization: What’s Next?
By Brian Bailey - 17 May, 2021 - Comments: 2

Concerns about the power consumed by semiconductors has been on the rise for the past couple of decades, but what can we expect to see coming in terms of analysis and automation from EDA companies, and is the industry ready to make the investment? Ever since Dennard scaling stopped providing automatic power gains by going to a smaller geometry, circa 2006, semiconductors have been increasing... » read more

11 Ways To Reduce AI Energy Consumption
By Bryon Moyer - 13 May, 2021 - Comments: 1

As the machine-learning industry evolves, the focus has expanded from merely solving the problem to solving the problem better. “Better” often has meant accuracy or speed, but as data-center energy budgets explode and machine learning moves to the edge, energy consumption has taken its place alongside accuracy and speed as a critical issue. There are a number of approaches to neural netw... » read more

Is AI Good Or Bad For The Planet?
By Dennis Laudick - 13 May, 2021 - Comments: 0

Will artificial intelligence save or sink planet earth? We’re surrounded by AI. When you use the internet, take a photo, use predictive text, or watch TV, you are interacting with AI. And we are still in the early stages of this revolution in technology and our lives. But AI can require large amounts of power. Researchers have documented the astounding amount of power required to train ... » read more

HyperRec: Efficient Recommender Systems with Hyperdimensional Computing
By Technical Paper Link - 12 May, 2021 - Comments: 0

A group of researchers are taking a different approach to AI. The University of California at San Diego, the University of California at Irvine, San Diego State University and DGIST recently presented a paper on a new hardware algorithm based on hyperdimensional (HD) computing, which is a brain-inspired computing model. The new algorithm, called HyperRec, uses data that is modeled with bina... » read more

What’s Next In Fab Tool Technologies?
By Mark LaPedus - 12 May, 2021 - Comments: 0

Experts at the Table: Semiconductor Engineering sat down to discuss extreme ultraviolet (EUV) lithography and other next-generation fab technologies with Jerry Chen, head of global business development for manufacturing & industrials at Nvidia; David Fried, vice president of computational products at Lam Research; Mark Shirey, vice president of marketing and applications at KLA; and Aki Fuj... » read more

Manufacturing Bits: May 10
By Mark LaPedus - 10 May, 2021 - Comments: 0

Synaptic transistors The University of Hong Kong and Northwestern University have developed an organic electrochemical synaptic transistor, a technology that could one day process and store information like the human brain. Researchers have demonstrated that the transistor can mimic the synapses in the human brain. It can build on memories to learn over time, according to researchers. Th... » read more

Why Reconfigurability Is Essential For AI Edge Inference Throughput
By Vinay Mehta - 06 May, 2021 - Comments: 0

For a neural network to run at its fastest, the underlying hardware must run efficiently on all layers. Through the inference of any CNN—whether it be based on an architecture such as YOLO, ResNet, or Inception—the workload regularly shifts from being bottlenecked by memory to being bottlenecked by compute resources. You can think of each convolutional layer as its own mini-workload, and so... » read more

Securing AI/ML With A Hardware Root Of Trust
By Thierry Kouthon - 06 May, 2021 - Comments: 0

AI/ML (Artificial Intelligence/Machine Learning) is now pervasive across all industries. It contributes to rationalizing and harnessing the enormous amount of information made available by the current massive wave of digitization. Digitization is transforming how business is run and how value is produced using digital technologies. Data, the raw material of AI/ML and deep learning algorithms, i... » read more

Shifting Auto Architectures
By Ed Sperling - 29 Apr, 2021 - Comments: 0

Domain controllers and gateways are being replaced by central processing modules and zonal gateways to handle all of the data traffic in a vehicle. Ron DiGiuseppe, automotive IP segment manager at Synopsys, talks with Semiconductor Engineering about how automotive applications are changing, what that means for engineering teams, and how they will shift as AI is increasingly deployed. » read more

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