International Conference on Computer and Knowledge Engineering

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Pruning and Mixed Precision Techniques for Accelerating Neural Network

Authors :

Mahsa Zahedi¹ Mohammad Sediq Abazari Bozhgani² Abdorreza Savadi³

1- Department of Computer Engineering Ferdowsi University of Mashhad Mashhad, Iran 2- Department of Computer Engineering Ferdowsi University of Mashhad Mashhad, Iran 3- Department of Computer Engineering Ferdowsi University of Mashhad Mashhad, Iran

Keywords :

Prune،Mixed Precision،Neural Network،Machine Learning،image processing

Abstract :

This study investigates the use of pruning and mixed precision techniques to enhance neural network performance, focusing on the AlexNet model trained on the MNIST dataset. Pruning removes unnecessary components, while mixed precision optimizes memory and computation efficiency. The study applies structured pruning to create a pruned model, which achieves improved inference time compared to the baseline. Automatic mixed precision is also employed, further enhancing inference speed. Combining pruning and mixed precision in a single model yields superior performance, surpassing the individual approaches. The combined model achieves significantly faster inference time by leveraging both techniques. The research highlights the potential of combining pruning and mixed precision for faster and more efficient neural network computations, reducing network size, optimizing memory utilization, and accelerating computations. The findings provide valuable insights for integrating these techniques into the AlexNet model and lay the groundwork for future exploration in larger and more complex models. This work holds promise for developing faster and more efficient deep learning models to meet the demands of real-world applications, particularly in resource-constrained environments

Papers List

List of archived papers

CSI-Based Human Activity Recognition using Convolutional Neural Networks

Parisa Fard Moshiri - Mohammad Nabati - Reza Shahbazian - Seyed Ali Ghorashi

Improve the utility of tensor cores by compacting sparse matrix technique

Mohammad.S Abazari - Mahsa Zahedi - Abdorreza Savadi

Semi-automatic Detection of Persian Stopwords using FastText Library

Mohammad Dehghani - Mohammad Manthouri

Using Deep Learning for Classification of Lung Cancer on CT Images in Ardabil Province

Mohammad Ali Javadzadeh Barzaki - Jafar Abdollahi - Mohammad Negaresh - Maryam Salimi - Hadi Zolfeghari - Mohsen Mohammadi - Asma Salmani - Rona Jannati - Firouz Amani

Trust Management Enhancement for the Internet of Things: a Smart Contract Approach

Amin Rouzbahani - Fattaneh Taghiyareh

An effective hybrid algorithm for locating splicing forgery image

Seyed Hesamoddin Hosseini - Amene Vatanparast - Amir Hossein Taherinia

Dynamic Knowledge Enhanced Neural Fashion Trend Forecasting with Quantile Loss

Fatemeh Rooholamini - Reza Azmi - Mobina Khademhossein - Maral Zarvani

Hybrid Vision Transformer for Detection of Dentigerous Cysts in Dental Radiography Images

Reza Tavasoli - Arya VarastehNezhad - Hamed Farbeh

A Chaotic Crow Search Algorithm for Overlapping Clustering

Mostafa Sabzekar - Seyed Vahid Mousavainejad

Generating Hand-Written Symbols With Trajectory Planning Using A Robotic Arm

Arya Parvizi - Armin Salimi-Badr

Samin Hamayesh - Version 41.7.6