A Massively Parallel Architecture for Bioinformatics

Presented by Md Jamiul Jahid

Introduction

• Bioinformatics algorithms are demanding in scientific computing

• In general most of the bioinformatics algorithms are fairly simple

• Dealing with huge amount of data• The size of DNA sequence database doubles

every year

Introduction

• A typical DNA contains 3.4 billion base pairs• Maximum algorithms use only simple

operations with input data like – Arithmetic operation– String matching– String comparison

Introduction

• Standard CPUs are designed for providing a good instruction mix for almost all commonly used algorithm

• For a target class of algorithm they are not effective

• Results– High runtime– Energy– Money

Contribution

• Present a massively parallel architecture • Using low cost FPGA(Field Programmable Gate

Array)• They called it COPACOBANA 5000– Meaning Cost-Optimized Parallel Code Braker ANd

Analyzer

COPACOBANA 1000• This machine is for cryptanalysis: fast code

breaking• 120 low cost FPGAs• 20 subunits• Each has Xilinx Spartan -3 XC3S1000 FPGAs

COPACOBANA 1000

• Assumptions– Programs are

parallelizable– Demand of data

transfer is low– All node needed

very little local memory which can be served from on-chip RAM of FPGAs

COPACOBANA 5000

• Bus Concepts– Point to point connection two neighboring FPGA-

cards– Point to point connection contain 8 pairs of wire– Each 250MHz, total 2Gbit/s

COPACOBANA 5000

• Controller– Root entity of control is running on a remote host

computer– Connected to COPACOBANA5000 by LAN– Two scenario• Data on remote host• Data on COPACOBANA5000

COPACOBANA 5000

• FPGA-Card– Xilinx Spartan-3 5000 is used– Contains 8 FPGAs– All FPGAs are globally clocked

Performance Estimation

• Between– PC– COPACOBANA1000– COPACOBANA5000

Performance Estimation

Conclusion

• In this paper a new hardware for running bioinformatics algorithm is proposed

• The hardware are– Cheap– Low power consumption– Efficient

Questions

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Thank You

Reference• Gerd Pfeiffer, Stefan Baumgart, Jan Schröder, and Manfred Schimmler,

A Massively Parallel Architecture for Bioinformatics, 9th International Conference on Computational Science (ICCS 2009).