Local and Parallel Mixed‐Precision Finite Element Methods for the Time‐Dependent Incompressible Flows
Sign Up to like & getrecommendations! Published in 2025 at "International Journal for Numerical Methods in Fluids"
DOI: 10.1002/fld.5388
Abstract: In this article, a local and parallel mixed‐precision finite element method is applied for solving the time‐dependent incompressible flows. We decompose the solution into the large eddy components and small eddy components based on two‐grid… read more here.
Keywords: parallel mixed; time; precision; local parallel ... See more keywords
Mixed-Precision Implementation of the Density Matrix Renormalization Group.
Sign Up to like & getrecommendations! Published in 2022 at "Journal of chemical theory and computation"
DOI: 10.1021/acs.jctc.2c00632
Abstract: The mixed-precision optimization is an effective emerging technique for quantum chemistry methods to obtain better computational performance and maintain the chemical accuracy. Here, we developed a two-level mixed-precision implementation for the density matrix renormalization group… read more here.
Keywords: mixed precision; accuracy; implementation density; precision ... See more keywords
Mixed-Precision Quantization for CNN-Based Remote Sensing Scene Classification
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2020.3007575
Abstract: Extensive convolutional neural network (CNN)-based methods have been widely used in remote sensing scene classification. However, the dense operation and huge memory storage of the state-of-the-art models hinder their deployment on low-power embedded devices. In… read more here.
Keywords: classification; quantization; method; remote sensing ... See more keywords
CMQ: Crossbar-Aware Neural Network Mixed-Precision Quantization via Differentiable Architecture Search
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems"
DOI: 10.1109/tcad.2022.3197495
Abstract: The RRAM-based accelerators have become very popular candidates for neural network acceleration due to they perform matrix-vector multiplication in-memory with high storage density and low latency. Many related works have used fixed-precision quantization to achieve… read more here.
Keywords: network; mixed precision; accuracy; precision quantization ... See more keywords
SUN: Dynamic Hybrid-Precision SRAM-Based CIM Accelerator With High Macro Utilization Using Structured Pruning Mixed-Precision Networks
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems"
DOI: 10.1109/tcad.2024.3358583
Abstract: Convolutional neural networks (CNNs) play a key role in many deep learning applications; however, these networks are resource intensive. The parallel computing ability of computing-in-memory (CIM) enables high energy efficiency in artificial intelligence accelerators. When… read more here.
Keywords: sram based; precision; hybrid precision; mixed precision ... See more keywords
Layer-Specific Optimization for Mixed Data Flow With Mixed Precision in FPGA Design for CNN-Based Object Detectors
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2020.3020569
Abstract: Convolutional neural networks (CNNs) require both intensive computation and frequent memory access, which lead to a low processing speed and large power dissipation. Although the characteristics of the different layers in a CNN are frequently… read more here.
Keywords: layer specific; mixed precision; data flow; chip ... See more keywords
MiniFloats on RISC-V Cores: ISA Extensions With Mixed-Precision Short Dot Products
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Emerging Topics in Computing"
DOI: 10.1109/tetc.2024.3365354
Abstract: Low-precision floating-point (FP) formats have recently been intensely investigated in the context of machine learning inference and training applications. While 16-bit formats are already widely used, 8-bit FP data types have lately emerged as a… read more here.
Keywords: minifloats risc; precision; isa extensions; mixed precision ... See more keywords
MBFQuant: A Multiplier-Bitwidth-Fixed, Mixed-Precision Quantization Method for Mobile CNN-Based Applications
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2023.3268562
Abstract: Deploying Convolutional Neural Network (CNN)-based applications to mobile platforms can be challenging due to the conflict between the restricted computing capacity of mobile devices and the heavy computational overhead of running a CNN. Network quantization… read more here.
Keywords: mixed precision; quantization; cnn; precision quantization ... See more keywords
EMWQ: An Efficient Mixed Precision Weight Quantization Method for Large Language Models
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2025.3585677
Abstract: Large language models (LLMs) have gained a lot of attention and achievements recently because of their significant comprehension and generative abilities. However, the large-scale parameters of LLMs require considerable computational resources in the training and… read more here.
Keywords: large language; method; precision; quantization ... See more keywords
Mixed-precision weights network for field-programmable gate array
Sign Up to like & getrecommendations! Published in 2021 at "PLoS ONE"
DOI: 10.1371/journal.pone.0251329
Abstract: In this study, we introduced a mixed-precision weights network (MPWN), which is a quantization neural network that jointly utilizes three different weight spaces: binary {−1,1}, ternary {−1,0,1}, and 32-bit floating-point. We further developed the MPWN… read more here.
Keywords: precision weights; network; implementation; point ... See more keywords