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Bioinformatics applications such as gene and protein sequence matching algorithms are characterized by the need to process large amounts of data. While uni-processor performance growth is slowing due to an increasing gap between processor and memory speeds and a saturation of processor clock frequencies, Genbank data is doubling every 15 months. With the advent of chip multiprocessor systems, great improvements in processor performance could potentially be achieved by taking advantage of the high interprocessor communication bandwidth and new models of programming. We propose a stream chip multiprocessor micro- architecture customized for bioinformatics applications that takes advantage of the memory bandwidth available in chip multiprocessors by exploiting the data parallelism available in bioinformatics applications. The proposed stream chip multiprocessor micro architecture, on a Xilinx Virtex-5 FPGA with 60 customized MicroBlaze soft processor cores running at 80 MHz with a PCI- bus limited main memory bandwidth of 0.12 GB/s, would achieve a speed-up of 68% for the Smith-Waterman sequence matching algorithm compared to a 2.4 GHz AMD Opteron 250. An extrapolated 60 long stream CMP running at 1 GHz with a memory access rate of 2.7 GB/s would run 41.7 times faster than the 1.2 GHz Sun Niagara processor, 16.5 times faster than the 2.4 GHz AMD Opteron 250 and 12.3 times faster than the 2.4 GHz Intel Xeon processor.