DocumentCode :
3403418
Title :
Power aware transformation of bandlimited signals
Author :
Krishnamoorthy, P. ; Tekumalla, Ramesh
Author_Institution :
APAC SOC Design, LSI Corp., Allentown, PA, USA
fYear :
2013
fDate :
4-6 Sept. 2013
Firstpage :
178
Lastpage :
183
Abstract :
This work presents an universal, lossless, linear, low complexity data transformation algorithm based on the sampling theorem that significantly reduces the complexity of operations in data processing systems. While many lossy and lossless compression methods are in existence, the data compressed by such methods cannot be directly processed by signal processing systems without decompression due to the non linear nature of most data compression algorithms. If there were linear compression method in existence, then compressed data could directly be passed to digital signal processing systems. Doing so significantly reduces the complexity of signal processing operations including additional benefits in the form of reduced power dissipation, improved signal integrity and better bandwidth utilization. This approach can be used in applications for the storage and retrieval of data from storage mediums such as read channels, system and processor interconnects including memory buses. System level simulations show that this method not only reduces the amount of data, but also improves performance due to improved signal integrity and significant reduction in power dissipation (upto 15% reduction) associated with the processing of multimedia content.
Keywords :
bandlimited signals; data compression; power aware computing; signal sampling; bandlimited signal; data compression algorithm; data processing system; data retrieval; data storage; linear complexity data transformation algorithm; linear compression method; lossless compression method; low complexity data transformation algorithm; multimedia content; power aware transformation; power dissipation; sampling theorem; signal integrity improvement; signal processing; Adders; Complexity theory; Data compression; Decoding; Power dissipation; Signal processing; Transmitters;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
SOC Conference (SOCC), 2013 IEEE 26th International
Conference_Location :
Erlangen
ISSN :
2164-1676
Type :
conf
DOI :
10.1109/SOCC.2013.6749684
Filename :
6749684
Link To Document :
بازگشت