Parallelization of FM-Index

A parallel design and implementation of FM-index is presented in this paper. In applications, the performance of the FM-index is crucial, which is a self-contained, highly compressed indexing algorithm. With the popularity of multi-core processors, parallel computing allows the FM-index to run faster by performing multiple computations simultaneously when possible. Our approach works by splitting input data into overlapping blocks with equal size, and running them through the FM-index algorithm simultaneously on multiple processors. After analyzing and refactoring the sequential version, we organize the data flows of all operations according to a unified parallel framework. The experimental results show that, in general our approach has achieved a significant and sub-linear speedup on widespread symmetrical multi-processing architectures. This will greatly reduce the running time of executing operations on large data sets.