tag: machine learning

Techniques For Improving Energy Efficiency of Training/Inference for NLP Applications, Including Power Capping & Energy-Aware Scheduling
By Technical Paper Link - 17 Aug, 2022 - Comments: 0

This new technical paper titled "Great Power, Great Responsibility: Recommendations for Reducing Energy for Training Language Models" is from researchers at MIT and Northeastern University. Abstract: "The energy requirements of current natural language processing models continue to grow at a rapid, unsustainable pace. Recent works highlighting this problem conclude there is an urgent need ... » read more

New Uses For AI In Chips
By John Koon and Ed Sperling - 11 Aug, 2022 - Comments: 1

Artificial intelligence is being deployed across a number of new applications, from improving performance and reducing power in a wide range of end devices to spotting irregularities in data movement for security reasons. While most people are familiar with using machine learning and deep learning to distinguish between cats and dogs, emerging applications show how this capability can be use... » read more

Assessing & Simulating Semiconductor Side-Channel or Unintended Data Leakage Vulnerabilities
By Technical Paper Link - 09 Aug, 2022 - Comments: 0

This research paper titled "Multiphysics Simulation of EM Side-Channels from Silicon Backside with ML-based Auto-POI Identification" from researchers at Ansys, National Taiwan University and Kobe University won the best paper award at IEEE's International Symposium on Hardware Oriented Security and Trust (HOST). The paper presents a new tool "to assess unintended data leakage vulnerabilities... » read more

How Overlay Keeps Pace With EUV Patterning
By Laura Peters - 09 Aug, 2022 - Comments: 1

Overlay metrology tools improve accuracy while delivering acceptable throughput, addressing competing requirements in increasingly complex devices. In a race that never ends, on-product overlay tolerances for leading-edge devices are shrinking rapidly. They are in the single-digit nanometer range for the 3nm generation (22nm metal pitch) devices. New overlay targets, machine learning, and im... » read more

Using ML Methods In Production-Ready Engineering Solutions For IC Verification
By WeiLii Tan - 02 Aug, 2022 - Comments: 0

By WeiLii Tan & Jeff Dyck Semiconductor designs continue to push the envelope of performance, functionality, and efficiency while their application scope expands in high-performance computing, automotive solutions, and IoT devices. The increased design complexity, scale, and mission-critical operations of semiconductor designs mean that IC verification strategies must evolve to cover expon... » read more

Analog Deep Learning Processor (MIT)
By Technical Paper Link - 29 Jul, 2022 - Comments: 0

A team of researchers at MIT are working on hardware for artificial intelligence that offers faster computing with less power. The analog deep learning technique involves sending protons through solids at extremely fast speeds.  “The working mechanism of the device is electrochemical insertion of the smallest ion, the proton, into an insulating oxide to modulate its electronic conductivity... » read more

ML And UVM Share Same Flaws
By Brian Bailey - 28 Jul, 2022 - Comments: 1

A number of people must be scratching their heads over what UVM and machine learning (ML) have in common, such that they can be described as having the same flaws. In both cases, it is a flaw of omission in some sense. Let's start with ML, and in particular, object recognition. A decade ago, Alexnet, coupled with GPUs, managed to beat all of the object detection systems that relied on tradit... » read more

Publicly Available Dataset for PCB X-Ray Inspection (FICS- University of Florida)
By Technical Paper Link - 19 Jul, 2022 - Comments: 0

Researchers from the Florida Institute for Cybersecurity (FICS) at the University of Florida published this technical paper titled "FICS PCB X-ray: A dataset for automated printed circuit board inter-layers inspection." Abstract "Advancements in computer vision and machine learning breakthroughs over the years have paved the way for automated X-ray inspection (AXI) of printed circuit bo... » read more

Using AI To Speed Up Edge Computing
By John Koon - 19 Jul, 2022 - Comments: 0

AI is being designed into a growing number of chips and systems at the edge, where it is being used to speed up the processing of massive amounts of data, and to reduce power by partitioning and prioritization. That, in turn, allows systems to act upon that data more rapidly. Processing data at the edge rather than in the cloud provides a number of well-documented benefits. Because the physi... » read more

Machine Learning Application For Early Power Analysis Accuracy Improvement
By Siemens EDA - 19 Jul, 2022 - Comments: 0

In this paper, we introduce a machine learning (ML) application that accurately estimates the switching power of the cells without needing the SPEF file (SPEF less PA flow). Three ML models (multi-linear regression, random forest and decision tree) were trained and tested on different industrial designs at 7nm technology. They are trained using different cells’ properties available, SPEF, and... » read more

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