Design and Implementation of a High-Performance VLSI Architecture for Canonical Huffman Encoding
Lavanya R1, Kartik V I2, Madhusudhan G K3, Chinnu H4, Makasud A T5
1Assistant Professor, 2Final year Student, 3Final year Student , 4Final year Student, 5Final year Student Department of Electronics and Communication Engineering,P E S institue of technology and management,Shimoga
Abstract - A key component of contemporary computer systems, data compression makes it possible for information to be stored and transmitted efficiently. A popular technique for lossless data compression, Huffman coding can drastically cut down on data size without sacrificing intensity. But conventional Huffman encoding techniques can have scalability and speed issues, especially when used in hardware. A high-throughput Very Large-Scale Integration (VLSI) design for a Canonical Huffman Encoder is shown in this study. To accomplish quick and effective encoding, the suggested approach makes use of parallel processing and improved algorithms. The system's use of the canonical Huffman algorithm lowers computational complexity and streamlines hardware implementation without sacrificing compression performance. The architecture incorporates real-time operation-optimized modules for frequency analysis, code generation, and symbol encoding. Results from simulations show that the suggested design achieves significantly higher throughput compared to conventional approaches, making it suitable for applications in data storage, multimedia, and communication systems. This study contributes to advancing VLSI designs for high-performance hardware
Key Words: Data Compression, Huffman Coding, Lossless Compression, Very Large-Scale Integration (VLSI), Canonical Huffman Encoder, High-Throughput Encoding, Parallel Processing, Efficient Encoding, Hardware Implementation, Computational Complexity, Code Generation, Symbol Encoding, Frequency Analysis, Real-Time Operation, Throughput Optimization, Multimedia Systems, Communication Systems, Data Storage, Hardware Architecture, VLSI Design, Performance Optimization, Simulations, Compression Performance, Hardware Design, Throughput Enhancement, System-Level Optimization, Power Efficiency, Resource Management, Data Transfer Efficiency, Low-Cost Implementation.
