STRUCTURAL MODIFICATION OF THE HUFFMAN METHOD FOR COMPRESSION OF DENSE DATA STREAMS WITHOUT LOSS ON A RCS

Abstract

Modern society demands require solving a whole range of computationally intensive tasks in real time. Such solutions require enormous computing power, broadband high-speed data transmission channels and impressive memory capacities. Such demands can be met by developing and implementing new technologies, expanding the technical infrastructure, which will require significant financial and time costs. Such a transition can be facilitated using the existing technical base by using real-time data compression algorithms. Data compression tools at the rate of receipt can increase the speed of calculations, data transfer, and reduce the occupied space during storage, using the existing infrastructure. Modern CPU-based technical platforms are not capable of providing streaming data processing at the rate of their receipt; the actual performance of such systems does not exceed 10% of the peak. Reconfigurable computing systems (RCS) based on programmable logic integrated circuits (FPGAs) can become a new platform for lossless data compression systems at the rate of receipt. However, for the efficient operation of such systems, it is necessary to develop new methods using structural calculations that allow the full potential of the FPGA resource to be unleashed. This paper presents the implementation of a modification of the dynamic Huffman coding algorithm on the RCS, which allows creating prefix codes of optimal length and processing dense data flows at the rate of receipt with a throughput of at least 128 Gbit/s. The performance of the developed modification is 5 times higher than the best known complementary implementation based on FPGA per computing pipeline