Design of Data Compression Mechanism in Cache Memory of Elbrus Processors

Author(s):  
Aleksey S. Kozhin ◽  
Alexander V. Surchenko
2007 ◽  
Vol 35 (5) ◽  
pp. 17-24 ◽  
Author(s):  
Kiyofumi Tanaka ◽  
Takahiro Kawahara

2016 ◽  
Vol 78 (6-4) ◽  
Author(s):  
Muhamad Azlan Daud ◽  
Muhammad Rezal Kamel Ariffin ◽  
S. Kularajasingam ◽  
Che Haziqah Che Hussin ◽  
Nurliyana Juhan ◽  
...  

A new compression algorithm used to ensure a modified Baptista symmetric cryptosystem which is based on a chaotic dynamical system to be applicable is proposed. The Baptista symmetric cryptosystem able to produce various ciphers responding to the same message input. This modified Baptista type cryptosystem suffers from message expansion that goes against the conventional methodology of a symmetric cryptosystem. A new lossless data compression algorithm based on theideas from the Huffman coding for data transmission is proposed.This new compression mechanism does not face the problem of mapping elements from a domain which is much larger than its range.Our new algorithm circumvent this problem via a pre-defined codeword list.  The purposed algorithm has fast encoding and decoding mechanism and proven analytically to be a lossless data compression technique.


2020 ◽  
Vol 255 ◽  
pp. 120190 ◽  
Author(s):  
Douglas L.S. Mendes ◽  
Ricardo A.L. Rabelo ◽  
Artur F.S. Veloso ◽  
Joel J.P.C. Rodrigues ◽  
Jose V. dos Reis Junior

Author(s):  
Abul Hasan Fazulullah ◽  
Purva Vansia ◽  
Kartavi Patel ◽  
Dipesh Patel ◽  
Abdel-shakour A. Abuzneid

2021 ◽  
pp. 391-410
Author(s):  
Shinichi Yamagiwa

AbstractIn this chapter, we introduce aspects of applying data-compression techniques. First, we study the background of recent communication data paths. The focus of this chapter is a fast lossless data-compression mechanism that handles data streams completely. A data stream comprises continuous data with no termination of the massive data generated by sources such as movies and sensors. In this chapter, we introduce LCA-SLT and LCA-DLT, which accept the data streams, as well as several implementations of these stream-based compression techniques. We also show optimization techniques for optimal implementation in hardware.


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