DocumentCode :
3079608
Title :
A coprocessor architecture for fast protein structure prediction
Author :
Marolia, M. ; Khoja, R. ; Acharya, T. ; Chakrabarti, C.
Author_Institution :
Dept. of Electr. Eng., Arizona State Univ., Tempe, AZ, USA
fYear :
2005
fDate :
2-4 Nov. 2005
Firstpage :
413
Lastpage :
418
Abstract :
Predicting protein structure from amino acid sequence is computationally very intensive. In order to speed up protein sequence matching and processing, it is necessary to develop special purpose VLSI architectures that exploit the underlying computational structures. In this paper, we present a coprocessor architecture for fast protein structure prediction based on the PSIPRED algorithm. The architecture consists of systolic arrays to speed up the data intensive sequence alignment and structure prediction steps, and finite state machines for the control dominated steps. The architecture has been synthesized using synopsis DC compiler using 0.18μm CMOS technology. The synthesized architecture requires 783,228 units of gate area and 226KB of memory, and can be clocked at 100 MHz. The architecture processes amino acid sequences extremely fast; for a database of 135,000,000 amino acids, the secondary structure of a query sequence of length -150 amino acids can be predicted in -11 seconds.
Keywords :
VLSI; finite state machines; medical signal processing; proteins; systolic arrays; 0.18 mum; 100 MHz; CMOS technology; PSIPRED algorithm; VLSI architectures; amino acid sequence; coprocessor architecture; finite state machines; protein sequence matching; protein structure prediction; systolic arrays; Amino acids; Automata; CMOS technology; Clocks; Computer architecture; Coprocessors; Databases; Protein sequence; Systolic arrays; Very large scale integration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Systems Design and Implementation, 2005. IEEE Workshop on
ISSN :
1520-6130
Print_ISBN :
0-7803-9333-3
Type :
conf
DOI :
10.1109/SIPS.2005.1579904
Filename :
1579904
Link To Document :
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