tag: DNN

Algorithm HW Framework That Minimizes Accuracy Degradation, Data Movement, And Energy Consumption Of DNN Accelerators (Georgia Tech)
By Technical Paper Link - 31 Aug, 2022 - Comments: 0

This new research paper titled "An Algorithm-Hardware Co-design Framework to Overcome Imperfections of Mixed-signal DNN Accelerators" was published by researchers at Georgia Tech. According to the paper's abstract, "In recent years, processing in memory (PIM) based mixed-signal designs have been proposed as energy- and area-efficient solutions with ultra high throughput to accelerate DNN com... » 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

DNN-Opt, A Novel Deep Neural Network (DNN) Based Black-Box Optimization Framework For Analog Sizing
By Technical Paper Link - 19 Aug, 2022 - Comments: 0

This technical paper titled "DNN-Opt: An RL Inspired Optimization for Analog Circuit Sizing using Deep Neural Networks" is co-authored from researchers at The University of Texas at Austin, Intel, University of Glasgow. The paper was a best paper candidate at DAC 2021. "In this paper, we present DNN-Opt, a novel Deep Neural Network (DNN) based black-box optimization framework for analog sizi... » read more

Gemmini: Open-source, Full-Stack DNN Accelerator Generator (DAC Best Paper)
By Technical Paper Link - 19 Aug, 2022 - Comments: 0

This technical paper titled "Gemmini: Enabling Systematic Deep-Learning Architecture Evaluation via Full-Stack Integration" was published jointly by researchers at UC Berkeley and a co-author from MIT.  The research was partially funded by DARPA and won DAC 2021 Best Paper. The paper presents Gemmini, "an open-source, full-stack DNN accelerator generator for DNN workloads, enabling end-to-e... » read more

Edge-AI Hardware for Extended Reality
By Technical Paper Link - 20 Jul, 2022 - Comments: 0

New technical paper titled "Memory-Oriented Design-Space Exploration of Edge-AI Hardware for XR Applications" from researchers at Indian Institute of Technology Delhi and Reality Labs Research, Meta. Abstract "Low-Power Edge-AI capabilities are essential for on-device extended reality (XR) applications to support the vision of Metaverse. In this work, we investigate two representative XR w... » read more

HW/SW Co-Design to Configure DNN Models On Energy Harvesting Devices
By Technical Paper Link - 20 Jul, 2022 - Comments: 0

New technical paper titled "EVE: Environmental Adaptive Neural Network Models for Low-Power Energy Harvesting System" was published by researchers at UT San Antonio, University of Connecticut, and Lehigh University. According to the abstract: "This paper proposes EVE, an automated machine learning (autoML) co-exploration framework to search for desired multi-models with shared weights for... » read more

Novel H2H mapping algorithm with both computation and communication awareness
By Technical Paper Link - 06 May, 2022 - Comments: 0

New research paper "H2H: Heterogeneous Model to Heterogeneous System Mapping with Computation and Communication Awareness" from University of Pittsburgh, Georgia Tech. Abstract: "The complex nature of real-world problems calls for heterogeneity in both machine learning (ML) models and hardware systems. The heterogeneity in ML models comes from multi-sensor perceiving and multi-task lear... » read more

Wavelength Multiplexed Ultralow-Power Photonic Edge Computing
By Technical Paper Link - 25 Mar, 2022 - Comments: 0

Abstract "Advances in deep neural networks (DNNs) are transforming science and technology. However, the increasing computational demands of the most powerful DNNs limit deployment on low-power devices, such as smartphones and sensors -- and this trend is accelerated by the simultaneous move towards Internet-of-Things (IoT) devices. Numerous efforts are underway to lower power consumption, but ... » read more

Mapping Transformation Enabled High-Performance and Low-Energy Memristor-Based DNNs
By Technical Paper Link - 14 Mar, 2022 - Comments: 0

Abstract: "When deep neural network (DNN) is extensively utilized for edge AI (Artificial Intelligence), for example, the Internet of things (IoT) and autonomous vehicles, it makes CMOS (Complementary Metal Oxide Semiconductor)-based conventional computers suffer from overly large computing loads. Memristor-based devices are emerging as an option to conduct computing in memory for DNNs to make... » read more

Toward Software-Equivalent Accuracy on Transformer-Based Deep Neural Networks With Analog Memory Devices
By Technical Paper Link - 20 Dec, 2021 - Comments: 0

Abstract:  "Recent advances in deep learning have been driven by ever-increasing model sizes, with networks growing to millions or even billions of parameters. Such enormous models call for fast and energy-efficient hardware accelerators. We study the potential of Analog AI accelerators based on Non-Volatile Memory, in particular Phase Change Memory (PCM), for software-equivalent accurate i... » read more

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