Parallel Audio Quick Search on Shared-Memory Multiprocessor Systems

Audio search plays an important role in analyzing audio data and retrieving useful audio information. In this paper, a partially overlapping block-parallel active search method (POBPAS) is proposed to perform audio quick search on shared-memory multiprocessor systems (SMPs). This method uses a proper data segmentation to achieve parallelism and performs a high level of parallelism with little additional work. Several techniques including I/O optimization, proper data partition and dynamic scheduling are also introduced to maximize its scalability performance. In addition, we conduct a detailed performance characterization analysis of the parallel implementation of the POBPAS for three data sets on two Intel Xeon SMPs. Experimental results indicate that there are no obvious parallel limiting factors in the implementation except memory bandwidth. As a result, it can achieve 11.3X speedup for a larger data set (searching a 15 seconds' clip in a 27 hours' audio stream) on the 16-way processor system.