Abstract

The demand for communicating large amounts of data in real-time has raised new challenges with implementing high-speed communication paths for high definition video and sensory data. It requires the implementation of high speed data paths based on hardware. Implementation difficulties have to be addressed by applying new techniques based on data-oriented algorithms. This paper focuses on a solution for this problem by applying a lossless data compression mechanism on the communication data path. The new lossless data compression mechanism, called LCA-DLT, provides dynamic histogram management for symbol lookup tables used in the compression and the decompression operations. When the histogram memory is fully used, the management algorithm needs to find the least used entries and invalidate these entries. The invalidation operations cause the blocking of the compression and the decompression data stream. This paper proposes novel techniques to eliminate blocking by introducing a dynamic invalidation mechanism, which allows achievement of a high throughput data compression.

Highlights

  • High-speed data communication paths in computing systems are necessary to achieve higher performance

  • In order to overcome the future implementation limitation, we focus on employing a data compression mechanism on the high-speed data path

  • We have proposed a novel stream-based data compression mechanism called LCA-DLT [6]

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Summary

Introduction

High-speed data communication paths in computing systems are necessary to achieve higher performance. The LZ algorithm needs to replace data patterns and needs to frequently insert/delete variable length data patterns in the lookup table These operations inevitably require a large amount of memory for hardware implementation. Its major implementations based on hardware such as [5] must handle a small chunk of data These problems interrupt continuous compression making it difficult to perform streaming data propagation in the communication path. It overcomes the problems found with implementing conventional data compression mechanisms It provides stream-based lossless compression by generating an adaptive histogram for the symbol lookup table implemented in a fixed size memory.

Data Compression Techniques
Stream-Based Data Compression on Hardware
V 6 FRXQW
Related Works
Dynamic Histogram Management in Stream-Based Lossless Data Compression
Dynamic Invalidation for Symbol Lookup Table Management
Lazy Compression
Implementation
Performance Evaluation
Effect on the Compression Ratio
Dynamic Hardware Performance
Application Example Using Image Data
Findings
Conclusions

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