tag: machine learning

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

Effectiveness of a Reinforcement-Learning Based Dynamic Power Manager In a SW Framework
By Technical Paper Link - 13 Jul, 2022 - Comments: 0

New technical paper titled "Low-Overhead Reinforcement Learning-Based Power Management Using 2QoSM" from researchers at ETH Zurich and Georgia Tech. Abstract "With the computational systems of even embedded devices becoming ever more powerful, there is a need for more effective and pro-active methods of dynamic power management. The work presented in this paper demonstrates the effectiven... » read more

Sibyl, a lightweight, reinforcement learning-based data placement technique for hybrid storage systems (ETH Zurich)
By Technical Paper Link - 06 Jul, 2022 - Comments: 0

New research paper titled "Sibyl: Adaptive and Extensible Data Placement in Hybrid Storage Systems Using Online Reinforcement Learning" from researchers at ETH Zurich, Eindhoven University of Technology, and LIRMM, Univ. Montpellier, CNRS. Abstract "Hybrid storage systems (HSS) use multiple different storage devices to provide high and scalable storage capacity at high performance. Recent r... » read more

Coverage-Directed Test Selection Method for Automatic Test Biasing During Simulation-Based Verification
By Technical Paper Link - 22 Jun, 2022 - Comments: 0

New research paper titled "Supervised Learning for Coverage-Directed Test Selection in Simulation-Based Verification" from researchers at University of Bristol and Infineon Technologies. Abstract: "Constrained random test generation is one the most widely adopted methods for generating stimuli for simulation-based verification. Randomness leads to test diversity, but tests tend to repeate... » read more

Deep Reinforcement Learning to Dynamically Configure NoC Resources
By Technical Paper Link - 17 Jun, 2022 - Comments: 0

New research paper titled "Deep Reinforcement Learning Enabled Self-Configurable Networks-on-Chip for High-Performance and Energy-Efficient Computing Systems" from Md Farhadur Reza at Eastern Illinois University. Find the open access technical paper here. Published June 2022. M. F. Reza, "Deep Reinforcement Learning Enabled Self-Configurable Networks-on-Chip for High-Performance and Energ... » read more

Research Bits: June 14
By Jesse Allen - 14 Jun, 2022 - Comments: 0

Photonic deep neural network chip Engineers from the University of Pennsylvania built a photonic deep neural network on a 9.3 square millimeter chip they say is faster and more efficient at classifying images, with the ability to process nearly two billion images a second. The chip uses a series of waveguides that form 'neutron layers' mimicking the brain. “Our chip processes information ... » read more

AlphaGo Game Influences Argonne’s New AI Tool For Materials Discovery
By Technical Paper Link - 10 Jun, 2022 - Comments: 0

Research paper titled "Learning in continuous action space for developing high dimensional potential energy models" from researchers at Argonne National Lab with contributions from Oak Ridge National Laboratory. Abstract "Reinforcement learning (RL) approaches that combine a tree search with deep learning have found remarkable success in searching exorbitantly large, albeit discrete action ... » read more

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