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1.
Microprocess Microsyst ; 33(4): 281-289, 2009 Jun 01.
Article in English | MEDLINE | ID: mdl-20160873

ABSTRACT

The amount of biosequence data being produced each year is growing exponentially. Extracting useful information from this massive amount of data efficiently is becoming an increasingly difficult task. There are many available software tools that molecular biologists use for comparing genomic data. This paper focuses on accelerating the most widely used such tool, BLAST. Mercury BLAST takes a streaming approach to the BLAST computation by off loading the performance-critical sections to specialized hardware. This hardware is then used in combination with the processor of the host system to deliver BLAST results in a fraction of the time of the general-purpose processor alone.This paper presents the design of the ungapped extension stage of Mercury BLAST. The architecture of the ungapped extension stage is described along with the context of this stage within the Mercury BLAST system. The design is compact and runs at 100 MHz on available FPGAs, making it an effective and powerful component for accelerating biosequence comparisons. The performance of this stage is 25× that of the standard software distribution, yielding close to 50× performance improvement on the complete BLAST application. The sensitivity is essentially equivalent to that of the standard distribution.

2.
AMIA Annu Symp Proc ; 2009: 103-7, 2009 Nov 14.
Article in English | MEDLINE | ID: mdl-20351831

ABSTRACT

We propose wireless sensor networks composed of nodes using low-power 802.15.4 radios as an enabling technology for patient monitoring in general hospital wards. A key challenge for such applications is to reliably deliver sensor data from mobile patients. We propose a monitoring system with two types of nodes: patient nodes equipped with wireless pulse oximeters and relays nodes used to route data to a base station. A reliability analysis of data collection from mobile users shows that mobility leads to packet losses exceeding 30%. The majority of packet losses occur between the mobile subjects and the first-hop relays. Based on this insight we developed the Dynamic Relay Association Protocol (DRAP), an effective mechanism for discovering the right relays for patient nodes. DRAP enables highly reliable data collection from mobile subjects. Empirical evaluation showed that DRAP delivered at least 96% of data from multiple users. Our results demonstrate the feasibility of wireless sensor networks for real-time clinical monitoring.


Subject(s)
Monitoring, Physiologic/instrumentation , Software , Telemetry , Humans , Monitoring, Ambulatory/instrumentation , Monitoring, Ambulatory/methods , Monitoring, Physiologic/methods , Oximetry/instrumentation , Radio
3.
Article in English | MEDLINE | ID: mdl-19492068

ABSTRACT

Large-scale protein sequence comparison is an important but compute-intensive task in molecular biology. BLASTP is the most popular tool for comparative analysis of protein sequences. In recent years, an exponential increase in the size of protein sequence databases has required either exponentially more running time or a cluster of machines to keep pace. To address this problem, we have designed and built a high-performance FPGA-accelerated version of BLASTP, Mercury BLASTP. In this paper, we describe the architecture of the portions of the application that are accelerated in the FPGA, and we also describe the integration of these FPGA-accelerated portions with the existing BLASTP software. We have implemented Mercury BLASTP on a commodity workstation with two Xilinx Virtex-II 6000 FPGAs. We show that the new design runs 11-15 times faster than software BLASTP on a modern CPU while delivering close to 99% identical results.

4.
Article in English | MEDLINE | ID: mdl-18846267

ABSTRACT

Biosequence similarity search is an important application in modern molecular biology. Search algorithms aim to identify sets of sequences whose extensional similarity suggests a common evolutionary origin or function. The most widely used similarity search tool for biosequences is BLAST, a program designed to compare query sequences to a database. Here, we present the design of BLASTN, the version of BLAST that searches DNA sequences, on the Mercury system, an architecture that supports high-volume, high-throughput data movement off a data store and into reconfigurable hardware. An important component of application deployment on the Mercury system is the functional decomposition of the application onto both the reconfigurable hardware and the traditional processor. Both the Mercury BLASTN application design and its performance analysis are described.

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