Efficient computing in image processing and DSPs with ASIP based multiplier

被引:0
作者
Sharma P. [1 ]
Dubey A.K. [1 ]
Goyal A. [2 ]
机构
[1] Department of Electronics & Communication Engineering, Amity University, Noida, Uttar Pradesh
[2] Department of Electrical Engineering and Computer Science, Texas A&M University, Kingsville, TX
来源
Recent Patents on Engineering | 2019年 / 13卷 / 02期
关键词
ASIP; DSP; FPGA; Image processing; MAC; Modified booth; Multiplier; Wallace tree;
D O I
10.2174/1872212112666180810150357
中图分类号
学科分类号
摘要
Background: With the growing demand of image processing and the use of Digital Signal Processors (DSP), the efficiency of the Multipliers and Accumulators has become a bottleneck to get through. We revised a few patents on an Application Specific Instruction Set Processor (ASIP), where the design considerations are proposed for application-specific computing in an efficient way to enhance the throughput. Objective: The study aims to develop and analyze a computationally efficient method to optimize the speed performance of MAC. Methods: The work presented here proposes the design of an Application Specific Instruction Set Processor, exploiting a Multiplier Accumulator integrated as the dedicated hardware. This MAC is optimized for high-speed performance and is the application-specific part of the processor; here it can be the DSP block of an image processor while a 16-bit Reduced Instruction Set Computer (RISC) processor core gives the flexibility to the design for any computing. The design was emulated on a Xilinx Field Programmable Gate Array (FPGA) and tested for various real-time computing. Results: The synthesis of the hardware logic on FPGA tools gave the operating frequencies of the legacy methods and the proposed method, the simulation of the logic verified the functionality. Conclusion: With the proposed method, a significant improvement of 16% increase in throughput has been observed for 256 steps iterations of multiplier and accumulators on an 8-bit sample data. Such an improvement can help in reducing the computation time in many digital signal processing applications where multiplication and addition are done iteratively. © 2019 Bentham Science Publishers.
引用
收藏
页码:174 / 180
页数:6
相关论文
共 50 条
[41]   Energy-efficient and fast memristor-based serial multipliers applicable in image processing [J].
Fatemieh, Seyed Erfan ;
Bagheralmoosavi, Bahareh ;
Reshadinezhad, Mohammad Reza .
RESULTS IN ENGINEERING, 2025, 25
[42]   The Research and Design of Image Processing System Based on FPGA and DSP [J].
Chen, SuHua ;
Shu, ZhiMeng ;
Fang, Xu .
ADVANCED RESEARCH ON MATERIAL SCIENCE, ENVIROMENT SCIENCE AND COMPUTER SCIENCE III, 2014, 886 :556-+
[43]   Suitability of recent hardware accelerators (DSPs, FPGAs, and GPUs) for computer vision and image processing algorithms [J].
HajiRassouliha, Amir ;
Taberner, Andrew J. ;
Nash, Martyn P. ;
Nielsen, Poul M. F. .
SIGNAL PROCESSING-IMAGE COMMUNICATION, 2018, 68 :101-119
[44]   Membrane computing and image processing: a short survey [J].
Daniel Díaz-Pernil ;
Miguel A. Gutiérrez-Naranjo ;
Hong Peng .
Journal of Membrane Computing, 2019, 1 :58-73
[45]   Programming of homogeneous computing structures for image processing [J].
Lutsyk, AY .
VISUAL INFORMATION PROCESSING VI, 1997, 3074 :277-283
[46]   Image processing and computing for digital holography with ImageJ [J].
Castaneda, Raul ;
Piedrahita-Quintero, Pablo ;
Garcia-Sucerquia, Jorge .
OPTICA PURA Y APLICADA, 2015, 48 (02) :77-84
[47]   Membrane computing and image processing: a short survey [J].
Diaz-Pernil, Daniel ;
Gutierrez-Naranjo, Miguel A. ;
Peng, Hong .
JOURNAL OF MEMBRANE COMPUTING, 2019, 1 (01) :58-73
[48]   FPGA based efficient on-chip memory for image processing algorithms [J].
Deepa, P. ;
Vasanthanayaki, C. .
MICROELECTRONICS JOURNAL, 2012, 43 (11) :916-928
[49]   Efficient tomato harvesting robot based on image processing and deep learning [J].
Zhonghua Miao ;
Xiaoyou Yu ;
Nan Li ;
Zhe Zhang ;
Chuangxin He ;
Zhao Li ;
Chunyu Deng ;
Teng Sun .
Precision Agriculture, 2023, 24 :254-287
[50]   Efficient tomato harvesting robot based on image processing and deep learning [J].
Miao, Zhonghua ;
Yu, Xiaoyou ;
Li, Nan ;
Zhang, Zhe ;
He, Chuangxin ;
Li, Zhao ;
Deng, Chunyu ;
Sun, Teng .
PRECISION AGRICULTURE, 2023, 24 (01) :254-287