Applying FPGA to Biological Problems - Accelerated Data Concepts

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2 Οκτ 2013 (πριν από 4 χρόνια και 12 μέρες)

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June


2006

Accelerated Data Concepts

Applying

Field Programmable
Gate Arrays

to Biological Problems


Presented by

Debbi Ryle

Daryl Popig


Accelerated Data Concepts




June


2006

Accelerated Data Concepts

Introductions


Accelerated Data Concepts


Specializing in Reconfigurable Computing Development


Debbi Ryle, Co
-
founder


Daryl Popig, Co
-
founder



Collaborations


Dr. Eric Stahlberg, OpenFPGA.org


David Pellerin, Impulse Accelerated Technologies


June


2006

Accelerated Data Concepts

FPGA Technology


FPGA (field programmable gate array) are
digital logic chips containing:


Programmable logic blocks


Programmable interconnects & switch matrices


Programmable I/O


Block RAM


PowerPC processors


used in embedded systems


June


2006

Accelerated Data Concepts

FPGA Technology


Inherently parallel device


Performs spatial processing of work


Reconfigurable
-

“Reconfigurable Computing”


Loadable sets of logic blocks


Specialized tasks


Eliminates bottlenecks associated with general
-
purpose processors


Alternative direction to exploit Moore’s Law

June


2006

Accelerated Data Concepts

Why is Digital Logic Faster Than Software?


Spatial vs. Temporal Computation


Processors divide computation across time, dedicated logic divides across space

June


2006

Accelerated Data Concepts

Using FPGAs for Acceleration


Identify algorithms that can exploit FPGA fine
-
grained parallelism


Look for candidate code using low
-
level data
parallelism


Exploit digital logic blocks ready to execute:


Computationally intensive calculations


Excessive multiple inner looping or backtracking




June


2006

Accelerated Data Concepts

Candidate Applications


Drug Docking
-

prescreening small module compounds
for drug interaction


Medical Imagining
-

Cat Scanning


Molecular Simulation


Matlab


June


2006

Accelerated Data Concepts

Computational Challenges


Smith
-
Waterman algorithm used to identify similarities
among bioinformatics sequences


Floyd
-
Warshall algorithm performing graph network
analysis


Searches through unstructured data (video, audio,
instrument signals, etc.)

June


2006

Accelerated Data Concepts

FPGA
-

Design Approach


Code application in C language


Find the computational “hot spots”


Partition the algorithm into software and hardware
processing


Use interactive optimization tools to analyze and
improve the performance of hardware
-
accelerated
functions


Use a C
-
to
-
hardware compiler to generate
synthesizable hardware


Load the resulting bitmap file to the FPGA device

June


2006

Accelerated Data Concepts

FPGA
-

Design Approach


Find the program’s “hot
spots”



Parallel threads


Computational routines


Nested N loops

June


2006

Accelerated Data Concepts

FPGA
-

Design Approach


Partition the algorithm
into software and
hardware processing



Use data streaming,
message passing and/or
shared memory to
partition the algorithm
into multiple
communicating software
and hardware processes

June


2006

Accelerated Data Concepts

FPGA
-

Design Approach


Use interactive optimization tools to analyze and
improve the performance of hardware
-
accelerated
functions



Emerging FPGA tools:


Impulse
-
C


Nallatech DimeTalk


Mitronics


SRC


June


2006

Accelerated Data Concepts

FPGA
-

Design Approach


Use a C
-
to
-
hardware
compiler to
generate
synthesizable
hardware



Load the
resulting bitmap
file to the FPGA
device

June


2006

Accelerated Data Concepts

Programming Tools


New tools simplifying FPGA programming at a
higher level of abstraction



Allows software developers to code without intense
hardware knowledge



Allows easier Hardware/Software co
-
simulation



Converts C code to a Hardware Descriptive
Language which is then converted to a net list and
then the place and route tools make a FPGA
loadable bitmap




June


2006

Accelerated Data Concepts

FPGA Hardware


Latest chip capacity denser with million gate devices


Requires less energy consumption


Reduce costs


Major Chip manufactures:


Xlinix


Altera


Available on wide variety of hardware platform:


SRC


CRAY Linux


Linux based


Windows based


June


2006

Accelerated Data Concepts

Performance Gains


Searching speed
-
up by 45x


Smith
-
Waterman implementation speed ups by
64x


Network Graph analysis problems speed ups by
30x

June


2006

Accelerated Data Concepts

Summary


General Processor limitations
-

Moores law
driving for alternatives



Hardware
-

chip capacity denser allowing more
complex algorithms



Software tools simplifying FPGA programming



World wide researcher’s interest
-

OpenFPGA.org


June


2006

Accelerated Data Concepts

Acknowledgements

Special Thanks to OCCBIO
Conference


For more information on FPGA
Technology, visit
:


http://acceleratedata.com



http://www.openfpga.org


http://implusec.com






























































































June


2006

Accelerated Data Concepts

References


Givaris, T.,
Reconfigurable Computing
,
http://www.ics.uci.edu/~dutt/ics212
-
wq05/reconfig.pdf




Lysaght, P. 2006,
FPGAs in the decade after Von Neuman Century,
DATE06 conference proceedings, Munich, Germany



Pellerin, D.,

2006
, Hardware/Software co
-
design, FPGA II,
DATE06
conference proceedings, Munich, Germany