Multiple pattern matching is widely used in computational biology to locate any number of nucleotides in genome databases. Processing data of this size often requires more computing power than a sequential computer can provide. A viable and cost-effective solution that can offer the power required by computationally intensive applications at low cost is to share computational tasks among the processing nodes of a high performance hybrid distributed and shared memory platform that consists of

more »

... ster workstations and multi-core processors. This paper presents experimental results and a theoretical performance model of the hybrid implementations of the Commentz-Walter, Wu-Manber, Set Backward Oracle Matching and the Salmela-Tarhio-Kytöjoki family of multiple pattern matching algorithms when executed in parallel on biological sequence databases.