tag: DNN

Insights From The AI Hardware & Edge AI Summit
By Ashish Darbari - 25 Jul, 2024 - Comments: 0

By Ashish Darbari, Fabiana Muto, and Nicky Khodadad In today's rapidly changing technology landscape, artificial intelligence (AI) is more than a buzzword. It is transforming businesses and societies. From advances in scalable AI methodology to urgent calls for sustainability, the AI Hardware & Edge AI Summit recently held in London, sparked vibrant discussions that will determine the fu... » read more

On-Device Speaker Identification For Digital Television (DTV)
By Marcus Corbin - 18 Jul, 2024 - Comments: 0

In recent years, the way we interact with our TVs has changed. Multiple button presses to navigate an on-screen keyboard have been replaced with direct interaction through our voices. While this has resulted in significant improvements to the Digital Television (DTV) user experience, more can be done to provide immersive and engaging experiences. Imagine you say, “recommend me a film” or... » read more

Using Deep Learning ADC For Defect Classification For Automatic Defect Inspection
By Onto Innovation - 14 May, 2024 - Comments: 0

In traditional semiconductor packaging, manual defect review after automated optical inspection (AOI) is an arduous task for operators and engineers, involving review of both good and bad die. It is hard to avoid human errors when reviewing millions of defect images every day, and as a result, underkill or overkill of die can occur. Automatic defect classification (ADC) can reduce the number of... » read more

Improving ML-Based Device Modeling Using Variational Autoencoder Techniques
By Technical Paper Link - 27 Sep, 2023 - Comments: 0

A technical paper titled “Improving Semiconductor Device Modeling for Electronic Design Automation by Machine Learning Techniques” was published by researchers at Commonwealth Scientific and Industrial Research Organisation (CSIRO), Peking University, National University of Singapore, and University of New South Wales. Abstract: "The semiconductors industry benefits greatly from the integ... » read more

Photonic-Electronic SmartNIC With Fast and Energy-Efficient Photonic Computing Cores (MIT)
By Technical Paper Link - 19 Sep, 2023 - Comments: 0

A technical paper titled “Lightning: A Reconfigurable Photonic-Electronic SmartNIC for Fast and Energy-Efficient Inference” was published by researchers at Massachusetts Institute of Technology (MIT). Abstract: "The massive growth of machine learning-based applications and the end of Moore's law have created a pressing need to redesign computing platforms. We propose Lightning, the first ... » read more

A Chiplet-Based FHE Accelerator Design Enabling Scalability And Higher Throughput
By Technical Paper Link - 07 Aug, 2023 - Comments: 0

A technical paper titled “REED: Chiplet-Based Scalable Hardware Accelerator for Fully Homomorphic Encryption” was published by researchers at Graz University of Technology and Samsung Advanced Institute of Technology. Abstract: "Fully Homomorphic Encryption (FHE) has emerged as a promising technology for processing encrypted data without the need for decryption. Despite its potential, its... » read more

Leveraging Large Language Models (LLMs) To Perform SW-HW Co-Design
By Technical Paper Link - 28 Jun, 2023 - Comments: 0

A technical paper titled “On the Viability of using LLMs for SW/HW Co-Design: An Example in Designing CiM DNN Accelerators” was published by researchers at University of Notre Dame. Abstract: "Deep Neural Networks (DNNs) have demonstrated impressive performance across a wide range of tasks. However, deploying DNNs on edge devices poses significant challenges due to stringent power and com... » read more

Optimizing Projected PCM for Analog Computing-In-Memory Inferencing (IBM)
By Technical Paper Link - 22 May, 2023 - Comments: 0

A new technical paper titled "Optimization of Projected Phase Change Memory for Analog In-Memory Computing Inference" was published by researchers at IBM Research. "A systematic study of the electrical properties-including resistance values, memory window, resistance drift, read noise, and their impact on the accuracy of large neural networks of various types and with tens of millions of wei... » read more

Low-Power Heterogeneous Compute Cluster For TinyML DNN Inference And On-Chip Training
By Technical Paper Link - 09 Apr, 2023 - Comments: 0

A new technical paper titled "DARKSIDE: A Heterogeneous RISC-V Compute Cluster for Extreme-Edge On-Chip DNN Inference and Training" was published by researchers at University of Bologna and ETH Zurich. Abstract "On-chip deep neural network (DNN) inference and training at the Extreme-Edge (TinyML) impose strict latency, throughput, accuracy, and flexibility requirements. Heterogeneous clus... » read more

Asynchronously Parallel Optimization Method For Sizing Analog Transistors Using Deep Neural Network Learning
By Technical Paper Link - 03 Mar, 2023 - Comments: 0

A new technical paper titled "APOSTLE: Asynchronously Parallel Optimization for Sizing Analog Transistors Using DNN Learning" was published by researchers at UT Austin and Analog Devices. Abstract "Analog circuit sizing is a high-cost process in terms of the manual effort invested and the computation time spent. With rapidly developing technology and high market demand, bringing automated s... » read more

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