scholarly journals Energy-Efficient NoC-Based Systems for Real-Time Multimedia Applications using Approximate Computing

2021 ◽  
Author(s):  
Wagner I. Penny ◽  
Daniel M. Palomino ◽  
Marcelo S. Porto ◽  
Bruno Zatt
Keyword(s):  
Real Time ◽  
Video Processing ◽  
Energy Efficient ◽  
Processing System ◽  
Schedulability Analysis ◽  
Multimedia Applications ◽  
Timing Constraints ◽  
Approximate Computing ◽  
Processing Elements ◽  
Fractional Motion Estimation

This work presents an energy-efficient NoC-based system for real-time multimedia applications employing approximate computing. The proposed video processing system, called SApp-NoC, is efficient in both energy and quality (QoS), employing a scalable NoC architecture composed of processing elements designed to accelerate the HEVC Fractional Motion Estimation (FME). Two solutions are proposed: HSApp-NoC (Heuristc-based SApp-NoC), and MLSApp-NoC (Machine Learning-based SApp-NoC). When compared to a precise solution processing 4K videos at 120 fps, HSApp-NoC and MLSApp-NoC reduce about 48.19% and 31.81% the energy consumption, at small quality reduction of 2.74% and 1.09%, respectively. Furthermore, a set of schedulability analysis is also proposed in order to guarantee the meeting of timing constraints at typical workload scenarios.

Design of a real-time video processing system with FPGA

2002 ◽  
Author(s):  
Wei Liu ◽  
Zeying Chi ◽  
Wenjian Chen
Keyword(s):  
Real Time ◽  
Video Processing ◽  
Processing System

Distributed Video Coding and Content Analysis for Resource Constraint Multimedia Applications

2012 ◽  
pp. 251-273
Author(s):  
Praveen Kumar ◽  
Amit Pande ◽  
Ankush Mittal ◽  
Abhisek Mudgal
Keyword(s):  
Video Coding ◽  
Real Time ◽  
Video Processing ◽  
Mobile Agents ◽  
Video Transmission ◽  
Moving Objects ◽  
Individual Case ◽  
Multimedia Applications ◽  
Real Time Processing ◽  
Laboratory Setup

Video coding and analysis for low power and low bandwidth multimedia applications has always been a great challenge. The limited computational resources on ubiquitous multimedia devices like cameras along with low and varying bandwidth over wireless network lead to serious bottlenecks in delivering real-time streaming of videos for such applications. This work presents a Content-based Network-adaptive Video-transmission (CbNaVt) framework which can waive off the requirements of low bandwidth. This is done by transmitting important content only to the end user. The framework is illustrated with the example of video streaming in the context of remote laboratory setup. A framework for distributed processing using mobile agents is discussed with the example of Distributed Video Surveillance (DVS). In this regard, the increased computational costs due to video processing tasks like object segmentation and tracking are shared by the cameras and a local base station called as Processing Proxy Server (PPS).However, in a distributed scenario like traffic surveillance, where moving objects is tracked using multiple cameras, the processing tasks needs to be dynamically distributed. This is done intelligently using mobile agents by migrating from one PPS to another for tracking an individual case object and transmitting required information to the end users. Although the authors propose a specific implementation for CbNaVt and DVS systems, the general ideas in design of such systems exemplify the way information can be intelligently transmitted in any ubiquitous multimedia applications along with the use of mobile agents for real-time processing and retrieval of video signal.

scholarly journals Limited Non-Preemptive EDF Scheduling for a Real-Time System with Symmetry Multiprocessors

Symmetry ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 172 ◽  
Author(s):  
Hoyoun Lee ◽  
Jinkyu Lee
Keyword(s):  
Real Time ◽  
Scheduling Algorithm ◽  
Schedulability Analysis ◽  
Timing Constraints ◽  
Limited Information ◽  
Time System ◽  
Real Time System ◽  
System A ◽  
The Future ◽  
Earliest Deadline

In a real-time system, a series of jobs invoked by each task should finish its execution before its deadline, and EDF (Earliest Deadline First) is one of the most popular scheduling algorithms to meet such timing constraints of a set of given tasks. However, EDF is known to be ineffective in meeting timing constraints for non-preemptive tasks (which disallow any preemption) when the system does not know the future job release patterns of the tasks. In this paper, we develop a scheduling algorithm for a real-time system with a symmetry multiprocessor platform, which requires only limited information about the future job release patterns of a set of non-preemptive tasks, called LCEDF. We then derive its schedulability analysis that provides timing guarantees of the non-preemptive task set on a symmetry multiprocessor platform. Via simulations, we demonstrate the proposed schedulability analysis for LCEDF significantly improves the schedulability performance in meeting timing constraints of a set of non-preemptive tasks up to 20.16%, compared to vanilla non-preemptive EDF.

The Design of Real-Time and High-Speed Video Processing Platform for Aerial UAV Based on DM642

2014 ◽  
Vol 1061-1062 ◽  
pp. 1186-1189
Author(s):  
Ming Zhe Wei ◽  
Wan Wei Tang
Keyword(s):  
Real Time ◽  
Video Processing ◽  
High Speed ◽  
Rapid Development ◽  
Processing System ◽  
Video Signal ◽  
Good Effect ◽  
Time Data ◽  
Spatial Interference ◽  
On Chip

With the rapid development of aerial UAV (Unmanned Aerial Vehicle), the design of real-time data acquisition and transmission system for the video signal has a new applied field. It is different from traditional video acquisition and processing system, aerial video signal has the problems of screen jitter and spatial interference. The processing algorithm of aerial UAV airborne video signal is put forward in the paper, and the platform of high speed procession is constructed based on chip TMS320DM642, and get a good effect.

scholarly journals FPGA-Based Stereo-Vision System Mimicking Human Binocular Vision

2021 ◽  
Author(s):  
Gvarami Labartkava
Keyword(s):  
Real Time ◽  
Binocular Vision ◽  
Video Processing ◽  
High Performance ◽  
Moving Objects ◽  
Peripheral Vision ◽  
Vision System ◽  
Processing System ◽  
Object Motion ◽  
Human Vision

Human vision is a complex system which involves processing frames and retrieving information in a real-time with optimization of the memory, energy and computational resources usage. It can be widely utilized in many real-world applications from security systems to space missions. The research investigates fundamental principles of human vision and accordingly develops a FPGA-based video processing system with binocular vision, capable of high performance and real-time tracking of moving objects in 3D space. The undertaken research and implementation consist of: 1. Analysis of concepts and methods of human vision system; 2. Development stereo and peripheral vision prototype of a system-on-programmable chip (SoPC) for multi-object motion detection and tracking; 3. Verification, test run and analysis of the experimental results gained on the prototype and associated with the performance constraints; The implemented system proposes a platform for real-time applications which are limited in current approaches.

scholarly journals Approximate LSTM Computing for Energy-Efficient Speech Recognition

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2004
Author(s):  
Junseo Jo ◽  
Jaeha Kung ◽  
Youngjoo Lee
Keyword(s):  
Speech Recognition ◽  
Energy Efficient ◽  
Short Term Memory ◽  
Recognition System ◽  
Similarity Score ◽  
Cmos Process ◽  
Approximate Computing ◽  
Processing Elements ◽  
On Chip ◽  
Computing Method

This paper presents an approximate computing method of long short-term memory (LSTM) operations for energy-efficient end-to-end speech recognition. We newly introduce the concept of similarity score, which can measure how much the inputs of two adjacent LSTM cells are similar to each other. Then, we disable the highly-similar LSTM operations and directly transfer the prior results for reducing the computational costs of speech recognition. The pseudo-LSTM operation is additionally defined for providing the approximate computation with reduced processing resolution, which can further relax the processing overheads without degrading the accuracy. In order to verify the proposed idea, in addition, we design an approximate LSTM accelerator in 65 nm CMOS process. The proposed accelerator newly utilizes a number of approximate processing elements (PEs) to support the proposed skipped-LSTM and pseudo-LSTM operations without degrading the energy efficiency. Moreover, sparsity-aware scheduling is introduced by introducing the small-sized on-chip SRAM buffer. As a result, the proposed work provides an energy-efficient but still accurate speech recognition system, which consumes 2.19 times less energy than the baseline architecture.

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