Study Of Data Compression Research Articles

Adaptive Data Compression on 3D Network-on-Chips

The three-dimensional Network-on-Chip (3D NoC) is an emerging research topic exploring the network architecture of 3D ICs that stack several wafers or dies. As such topics being extensively studied, it is found negative impacts of 3D NoC's vertical interconnects are raising concerns considering their footprint sizes and routability degradation. In our evaluation, we found such vertical bandwidth limitation can dramatically degrade system performance by up to 2.3×. Since such limitations come from physical design constraints, to mitigate performance degradation, we have no other choice but to reduce the amount of communication data on-chip, especially for those data moving vertically. In this paper, therefore, we carry out a study of data compression on 3D NoC architectures with a comprehensive set of scientific workloads. Firstly, we propose an adaptive data compression scheme for 3D NoCs, taking account of the vertical bandwidth limitation and data compressibility. Secondly, we evaluate our proposal on a 3D NoC platform and we observe that the compressibility based adaptive compression is very useful against incompressible data while the location-based adaptive compression is more effective with more layers for the 3D NoC. Thirdly, we find that in a bandwidth limited situation like a CMP with 3D NoCs having multiple connected layers, adaptive data compression with location-based control or with both compressibility and location based control is very promising if the number of layers grows.

Improving Chinese Storing Text Retrieval Systems' Security via a Novel Maximal Prefix Coding

We have seen that Huffman coding has been widely used in data, image, and video compression. In this paper novel maximal prefix coding is introduced. Relationship between the Huffman coding and the optimal maximal prefix coding are discussed. We show that all Huffman coding schemes are optimal maximal prefix coding schemes and that conversely the optimal maximal prefix coding schemes need not be the Huffman coding schemes. Moreover, it is proven that, for any maximal prefix code C, there exists an information source I = (∑ P) such that C is exactly a Huffman code for I. Therefore, it is essential to show that the class of Huffman codes is coincident with one of the maximal prefix codes. A case study of data compression is also given. Comparing the Huffman coding, the maximal prefix coding is used not only for statistical modeling but also for dictionary methods. It is also good at applying to a large information retrieval system and improving its security.

255 画像添付型レポーティングシステムにおける画像圧縮の試み

255 画像添付型レポーティングシステムにおける画像圧縮の試み

Compression within a context-sensitive commercial random access domain: An industrial case study

An industrial case study of data compression within the library automation domain is described. A context dependent approach, where the individual records require file-independent compression and expansion, is evaluated. The discussed approach favorably compares against popular compression algorithms. Comparisons were made against commercially available implementations of the conventional compression schemes. The described approach is now in use by The Library Corporation.