Distributed Out-of-Core Preprocessing of Very Large Microscopy Images for Efficient Querying

We present a combined task- and data-parallel approach for distributed execution of pre-processing operations to support efficient evaluation of polygonal aggregation queries on digitized microscopy images. Our approach targets out-of-core, pipelined processing of very large images on active storage clusters. Our experimental results show that the proposed approach is scalable both in terms of number of processors and the size of images