Efficient data transfer scheme using word-pair-encoding-based compression for large-scale text-data processing

Large-scale data processing is very common in many fields such as data-mining, genome mapping, etc. To accelerate such processing, Graphic Accelerator Units (GPU) and FPGAs (Feild-Programmable Gate-Array) are used. However, the large data transfer time between the accelerator and the host computer is a huge performance bottleneck. In this paper, we use a word-pair-encoding method to compress the data down to 25% of its original size. The encoded data can be decoded from any position without decoding the whole data file. For some algorithms, the encoded data can be processed without decoding. Using Burrows-Wheeler algorithm based text search, we show that the data amount and transfer time can be reduced by over 70%.