Better schedules for low precision training of deep neural networks
Sign Up to like & getrecommendations! Published in 2024 at "Machine Learning"
DOI: 10.1007/s10994-023-06480-0
Abstract: Low precision training can significantly reduce the computational overhead of training deep neural networks (DNNs). Though many such techniques exist, cyclic precision training (CPT), which dynamically adjusts precision throughout training according to a cyclic schedule,… read more here.
Keywords: precision; training; low precision; performance ... See more keywords
FxP-QNet: A Post-Training Quantizer for the Design of Mixed Low-Precision DNNs with Dynamic Fixed-Point Representation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3157893
Abstract: Deep neural networks (DNNs) have demonstrated their effectiveness in a wide range of computer vision tasks, with the state-of-the-art results obtained through complex and deep structures that require intensive computation and memory. In the past,… read more here.
Keywords: fxp qnet; fixed point; low precision; precision ... See more keywords
Wideband mmWave Channel Estimation for Hybrid Massive MIMO With Low-Precision ADCs
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Wireless Communications Letters"
DOI: 10.1109/lwc.2018.2870360
Abstract: In this letter, we investigate channel estimation for wideband millimeter-wave (mmWave) massive multiple-input multiple-output under hybrid architecture with low-precision analog-to-digital converters (ADCs). To design channel estimation for the hybrid structure, both analog processing components and… read more here.
Keywords: estimation hybrid; channel estimation; low precision; precision adcs ... See more keywords
CMix-NN: Mixed Low-Precision CNN Library for Memory-Constrained Edge Devices
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Circuits and Systems II: Express Briefs"
DOI: 10.1109/tcsii.2020.2983648
Abstract: Low-precision integer arithmetic is a necessary ingredient for enabling Deep Learning inference on tiny and resource-constrained IoT edge devices. This brief presents CMix-NN, a flexible open-sourceCMix-NN is available at https://github.com/EEESlab/CMix-NN. mixed low-precision (independent tensors quantization… read more here.
Keywords: cmix mixed; mixed low; low precision; precision cnn ... See more keywords
FAT: Frequency-Aware Transformation for Bridging Full-Precision and Low-Precision Deep Representations.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3190607
Abstract: Learning low-bitwidth convolutional neural networks (CNNs) is challenging because performance may drop significantly after quantization. Prior arts often quantize the network weights by carefully tuning hyperparameters such as nonuniform stepsize and layerwise bitwidths, which are… read more here.
Keywords: aware transformation; frequency; low precision; quantization ... See more keywords
Bayes-Optimal MMSE Detector for Massive MIMO Relaying With Low-Precision ADCs/DACs
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2020.2977265
Abstract: In this study, we focus on the detector design for a massive multiple-input multiple-output amplify-and-forward relaying system with low-precision analog-to-digital converters (ADCs) and digital-to-analog converters (DACs). A general relaying model with direct and relay links… read more here.
Keywords: low precision; detector; adcs dacs; precision adcs ... See more keywords
ABS: Accumulation Bit-Width Scaling Method for Designing Low-Precision Tensor Core
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Very Large Scale Integration (VLSI) Systems"
DOI: 10.1109/tvlsi.2024.3414260
Abstract: A big gap exists between deep neural network (DNN) applications’ computational demand and the computing power of DNN accelerators. Low-precision floating-point (LP-FP) computation is one of the important means to improve the performance of DNN… read more here.
Keywords: bit width; precision; low precision; dnn ... See more keywords
All-Digital LoS MIMO with Low-Precision Analog-to-Digital Conversion
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Wireless Communications"
DOI: 10.1109/twc.2022.3142305
Abstract: Line-of-sight (LoS) multi-input multi-output (MIMO) systems exhibit attractive scaling properties with increase in carrier frequency: for a fixed form factor and range, the spatial degrees of freedom increase quadratically for 2D arrays, in addition to… read more here.
Keywords: quantization; los mimo; low precision; analog digital ... See more keywords
Deep hologram converter from low-precision to middle-precision holograms.
Sign Up to like & getrecommendations! Published in 2023 at "Applied optics"
DOI: 10.1364/ao.482434
Abstract: We propose a deep hologram converter based on deep learning to convert low-precision holograms into middle-precision holograms. The low-precision holograms were calculated using a shorter bit width. It can increase the amount of data packing… read more here.
Keywords: precision holograms; low precision; hologram converter; deep hologram ... See more keywords
SpQuant-SNN: ultra-low precision membrane potential with sparse activations unlock the potential of on-device spiking neural networks applications
Sign Up to like & getrecommendations! Published in 2024 at "Frontiers in Neuroscience"
DOI: 10.3389/fnins.2024.1440000
Abstract: Spiking neural networks (SNNs) have received increasing attention due to their high biological plausibility and energy efficiency. The binary spike-based information propagation enables efficient sparse computation in event-based and static computer vision applications. However, the… read more here.
Keywords: precision; spquant snn; membrane potential; low precision ... See more keywords