tag: AI

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

Roadblocks For ML in EDA
By Brian Bailey - 28 Apr, 2021 - Comments: 1

Is EDA a suitable space for utilizing machine learning (ML)? The answer depends on a number of factors, including where exactly it is being applied, how much support there is from the industry, and whether there are demonstrable advantages. Exactly where ML will play a role has yet to be decided. Replacing existing heuristics with machine learning, for example, would require an industry-wide... » read more

Manufacturing Bits: April 27
By Mark LaPedus - 27 Apr, 2021 - Comments: 0

Next-gen neuromorphic computing The European Union (EU) has launched a new project to develop next-generation devices for neuromorphic computing systems. The project, called MeM-Scales, plans to develop a novel class of algorithms, devices, and circuits that reproduce multi-timescale processing of biological neural systems. The results will be used to build neuromorphic computing systems th... » read more

New Methodologies Create New Opportunities
By Brian Bailey - 27 Apr, 2021 - Comments: 0

Experts at the Table: Semiconductor Engineering sat down to discuss what open source verification means today and what it should evolve into, with Jean-Marie Brunet, senior director for the Emulation Division at Siemens EDA; Ashish Darbari, CEO of Axiomise; Simon Davidmann, CEO of Imperas Software; Serge Leef, program manager in the Microsystems Technology Office at DARPA; Tao Liu, staff hardwa... » read more

Putting Limits On What AI Systems Can Do
By Ed Sperling - 22 Apr, 2021 - Comments: 0

New techniques and approaches are starting to be applied to AI and machine learning to ensure they function within acceptable parameters, only doing what they're supposed to do. Getting AI/ML/DL systems to work has been one of the biggest leaps in technology in recent years, but understanding how to control and optimize them as they adapt isn't nearly as far along. These systems are generall... » read more

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