tag: machine learning

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

Active Learning: Integrating Natural Intelligence Into Artificial Intelligence
By Oliver Gnepper - 09 Jun, 2022 - Comments: 0

Today, very few people would likely deny the fact that data can present major added value for companies. But analyzing data from production processes reveals the incompleteness of data collection and the associated reduced potential of the data that can be leveraged. Typical shortcomings include: Incomplete representation of processes in the dataspace, Inadequate connection of processes... » read more

AI-Powered Verification
By Brian Bailey - 01 Jun, 2022 - Comments: 1

With functional verification consuming more time and effort than design, the chip industry is looking at every possible way to make the verification process more effective and more efficient. Artificial intelligence (AI) and machine learning (ML) are being tested to see how big an impact they can have. While there is progress, it still appears to be just touching the periphery of the problem... » read more

CFU Playground: Significant Speedups & Design Space Exploration Between CPU & Accelerator
By Technical Paper Link - 30 May, 2022 - Comments: 0

Technical paper titled "CFU Playground: Full-Stack Open-Source Framework for Tiny Machine Learning (tinyML) Acceleration on FPGAs," from Google, Purdue University and Harvard University. Abstract "We present CFU Playground, a full-stack open-source framework that enables rapid and iterative design of machine learning (ML) accelerators for embedded ML systems. Our toolchain tightly integr... » read more

Improving PPA With AI
By John Koon - 12 May, 2022 - Comments: 0

AI/ML/DL is starting to show up in EDA tools for a variety of steps in the semiconductor design flow, many of them aimed at improving performance, reducing power, and speeding time to market by catching errors that humans might overlook. It's unlikely that complex SoCs, or heterogeneous integration in advanced packages, ever will be perfect at first silicon. Still, the number of common error... » read more

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