Abstract
Although microarrays are already having a tremendous impact on biomedical science, they still present great computational challenges. We examine a particular problem involving the computation of linear regressions on a large number of vector combinations in a high-dimensional parameter space, a problem that was found to be virtually intractable on a PC cluster. We observe that characteristics of this problem map particularly well to FPGAs and confirm this with an implementation that results in a 1000-fold speed-up over a serial implementation. Other contributions involve the data routing structure, the analysis of bit-width allocation, and the handling of missing data. Since this problem is representative of many in functional genomics, part of the overall significance of this work is that it points to a potential new area of applicability for FPGA coprocessors.
This work was supported in part by the National Science Foundation through CAREER award #9702483 and by a grant from the Compaq Computer Corporation.
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Van Court, T., Herbordt, M.C., Barton, R.J. (2003). Case Study of a Functional Genomics Application for an FPGA-Based Coprocessor. In: Y. K. Cheung, P., Constantinides, G.A. (eds) Field Programmable Logic and Application. FPL 2003. Lecture Notes in Computer Science, vol 2778. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45234-8_36
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DOI: https://doi.org/10.1007/978-3-540-45234-8_36
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