Year: 2025
Type: article
Abstract: ABSTRACT Huffman coding is foundational to data compression algorithms. We propose an advanced application‐specific integrated circuit (ASIC) design for a canonical Huffman encoder, optimised for high throughput and low power consumption. Our design introduces a high‐speed sorting circuit, an efficient Huffman tree canonisation algorithm and an innovative entropy‐based compressibility prediction mechanism. Implemented using 12 nm CMOS technology, the proposed solution achieves a remarkable throughput of 4 GB/s and sub‐microsecond latency for 4 KB pages, outperforming existing x86 software implementations by nearly two orders of magnitude and surpassing state‐of‐the‐art hardware accelerators. This advancement significantly enhances data processing capabilities in computational storage drives (CSDs), providing a scalable and energy‐efficient data compression solution for modern data centres.
Source: Electronics Letters
DOI: 10.1049/ell2.70224
Authors: Yunxin Huang, Aiguo Song, Tao Lu, Yafei Yang
Institution: Southeast University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,590
OpenAlex ID: W4408850126