tag: machine learning

Artificial Neural Network (ANN)-Based Model To Evaluate The Characteristics of A Nanosheet FET (NSFET)
By Technical Paper Link - 02 Sep, 2022 - Comments: 0

This new technical paper titled "Machine-Learning-Based Compact Modeling for Sub-3-nm-Node Emerging Transistors" was published by researchers at SungKyunKwan University, Korea. Abstract: "In this paper, we present an artificial neural network (ANN)-based compact model to evaluate the characteristics of a nanosheet field-effect transistor (NSFET), which has been highlighted as a next-generat... » read more

ML Architecture for Solving the Inverse Problem for Matter Wave Lithography: LACENET
By Technical Paper Link - 29 Aug, 2022 - Comments: 0

This recent technical paper titled "Realistic mask generation for matter-wave lithography via machine learning" was published by researchers at University of Bergen (Norway). Abstract: "Fast production of large area patterns with nanometre resolution is crucial for the established semiconductor industry and for enabling industrial-scale production of next-generation quantum devices. Metasta... » read more

ML-Based Framework for Automatically Generating Hardware Trojan Benchmarks
By Technical Paper Link - 25 Aug, 2022 - Comments: 0

A new technical paper titled "Automatic Hardware Trojan Insertion using Machine Learning" was published by researchers at University of Florida and Stanford University. Abstract (partial): "In this paper, we present MIMIC, a novel AI-guided framework for automatic Trojan insertion, which can create a large population of valid Trojans for a given design by mimicking the properties of a small... » read more

Machine Learning-Driven Full-Flow Chip Design Automation
By Cadence - 24 Aug, 2022 - Comments: 0

To enable the semiconductor industry to continue growing, the chip design process must become more efficient. With the availability of massive, cloud-enabled, distributed computing and advancements in machine learning computer science, the next chip design automation revolution is now possible. The Cadence® Cerebrus™ Intelligent Chip Explorer utilizes both of these technologies, based o... » read more

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

← Older posts Newer posts →

  • Sponsors

About

Navigation

Connect With Us

Copyright ©2013-2025 SMG   |  Terms of Service  |  Privacy Policy