SBIR Phase I: Bioinformatic FPGA Appliance

Award Information
Agency: National Science Foundation
Branch: N/A
Contract: 0945666
Agency Tracking Number: 0945666
Amount: $150,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2009
Solicitation Year: N/A
Solicitation Topic Code: IC
Solicitation Number: NSF 09-541
Small Business Information
1604 Stone Ridge Way, Bel Air, MD, 21015
DUNS: 603014684
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Vincent Natoli
 (410) 670-4535
Business Contact
 Vincent Natoli
Title: PhD
Phone: (410) 670-4535
Research Institution
This Small Business Innovation Research (SBIR) Phase I project will investigate the technical and commercial feasibility of a Bioinformatic computing appliance based on FPGA technology. DNA sequencing machines output enormous volumes of raw data with steady year-by-year increases. The initial data processing stages of alignment and mapping are computationally intense and currently present a significant and growing bottleneck. It is believed that an opportunity exists for a new solution that addresses the growing data deluge and computational strain that it introduces. The company proposes to create an appliance using an open-source algorithm for the purpose of a feasibility study. The research objective of the work is to create a powerful and optimized engine for this algorithm that is easily operated by a user through an intuitive web interface. The work will be implemented on a PCI-e based FPGA computing board with two user FPGAs. The application will be optimized to make use of specialized features of the chip. The anticipated result is a Bioinformatic appliance running at 50x to 100x faster than the standard CPU implementation and at lower power and with a smaller physical footprint. The broader impacts of the proposed activity include the potential commercial value and the enhancement of research that will result from wider dissemination of DNA sequencing technology. Full advantages of DNA sequencing are not realized and progress has been slowed by the lack of an efficient and capable processing stage. Traditional solutions using clusters present users with a difficult administration problem. FPGA technology can reduce the size and the power consumption of the data processing stage significantly, making it available to and useful to more companies, labs and health care facilities. The technical and business risk associated with the overall vision of this effort brings with it the possibility of significant commercial impact across the industry.

* Information listed above is at the time of submission. *

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