haney - 1 hpec 10/20/2005 mit lincoln laboratory the hpec challenge benchmark suite ryan haney,...
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Haney - 1 HPEC 10/20/2005
MIT Lincoln Laboratory
The HPEC Challenge Benchmark Suite
Ryan Haney, Theresa Meuse, Jeremy Kepner and James Lebak
Massachusetts Institute of TechnologyLincoln Laboratory
HPEC 2005
This work is sponsored by the Defense Advanced Research Projects Agency under Air Force Contract FA8721-05-C-0002. Opinions, interpretations, conclusions, and recommendations are those of the authors and are not necessarily endorsed by the United States Government.
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Acknowledgements
• Lincoln Laboratory PCA Team– Matthew Alexander– Jeanette Baran-Gale– Hector Chan– Edmund Wong
• Shomo Tech Systems– Marti Bancroft
• Silicon Graphics Incorporated– William Harrod
• Sponsor– Robert Graybill, DARPA PCA and HPCS Programs
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HPEC Challenge Benchmark Suite
• PCA program kernel benchmarks– Single-processor operations– Drawn from many different DoD applications– Represent both “front-end” signal processing and “back-end”
knowledge processing
• HPCS program Synthetic SAR benchmark– Multi-processor compact application– Representative of a real application workload– Designed to be easily scalable and verifiable
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Outline
• Introduction
• Kernel Level Benchmarks
• SAR Benchmark– Overview– System Architecture– Computational Components
• Release Information
• Summary
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Spotlight SAR System
• Intent of Compact App:
– Scalable
– High Compute Fidelity
– Self-Verifying
• Principal performance goal: Throughput
– Maximize rate of results
– Overlapped IO and computing
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SARImages
Front-End Sensor Processing
TemplateFiles
Back-End Knowledge Formation
Validation
TemplateFiles
Groups ofTemplateFiles
RawSAR
Files
SARImage
Scalable Data and Template
Generator
Kernel #2Image Storage
Groups of Template
Files
Sub-ImageDetectionFiles
Image Files
Sub-ImageDetectionFiles
DetectionsKernel #4 Detection
SARImage
TemplateInsertion
Kernel #3Image
Retrieval Templates
RawSARFile
SARImageFiles
SARImageFiles
Kernel #1 Data Readand Image Formation
Templates
TemplateFiles
SAR System Architecture
Raw SAR Data Files
ComputationFile IO
HPEC community has traditionally
focused on Computation …
… but File IO performance is
increasingly important
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SARImage
Knowledge Formation
SARImageFiles
RawSARFile
TemplateFiles
Groups ofTemplateFiles
RawSARFiles
Kernel #2Image Storage
SARImageFiles
DetectionFiles
Kernel #3Image
Retrieval
TemplateFiles
TemplateFiles
Groups of Template
Files
Sub-ImageDetectionFiles
Image Files
Sensor Processing
Raw SAR Data Files
ValidationDetectionsKernel #4
Detection
SARImage
Templates
Data Generation and Computational Stages
RawSAR
Templates
SARImage
TemplateInsertion
Scalable Data and Template
Generator
Kernel #1 Image
Formation
Templates
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• Radar captures echo returns from a ‘swath’ on the ground
• Notional linear FM chirp pulse train, plus two ideally non-overlapping echoes returned from different positions on the swath
• Summation and scaling of echo returns realizes a challengingly long antenna aperture along the flight path
SAR Overview
. . .
pulses swath
mntpmnuts )),(),(),(
delayed transmitted SAR waveform
reflection coefficient scale factor, different for each return from the swathreceived
‘raw’ SAR
Cross-Range, Y = 2Y0
Fixed to Broadside
Range, X = 2X0
Synthetic Aperture, L
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Scalable Synthetic Data Generator
• Generates synthetic raw SAR complex data
• Data size is scalable to enable rigorous testing of high performance computing systems
– User defined scale factor determines the size of images generated
• Generates ‘templates’ that consist of rotated and pixelated capitalized letters
Cross-RangeR
ang
e
Spotlight SAR Returns
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Kernel 1 — SAR Image Formation
s(,ku) f(x,y)
F(kx,ky)
Interpolationkx = sqrt(4k2 –ku
2)ky = ku
Matched Filtering
Fourier Transform(t,u)(ku)
Inverse Fourier Transform
(kx,ky) (x,y)
s*0(,ku)
s(t,u)
Received Samples Fit a Polar Swath
Processed SamplesFit a Rectangular Swath f
o
kx
ky
Range, Pixels
Cro
ss-R
ang
e, P
ixel
s
Spotlight SAR Reconstruction
Spatial Frequency Domain Interpolation
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Template Insertion(untimed)
• Inserts rotated pixelated capital letter templates into each SAR image
– Non-overlapping locations and rotations– Randomly selects 50%– Used as ideal detection targets in Kernel 4
Y P
ixel
s
Y P
ixel
s
X Pixels X Pixels
If inserted with %100 Templates
Image only inserted with %50 random Templates
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Kernel 4 — Detection
• Detects targets in SAR images1. Image difference2. Threshold3. Sub-regions 4. Correlate with every template
max is target ID
• Computationally difficult– Many small correlations over
random pieces of a large image• 100% recognition no false alarms
Image Difference
Image A
Image B
Sub-regionThresholded Difference
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ValidationDetectionsKernel #4
Detection
SARImage
Templates
RawSAR
Templates
SARImage
TemplateInsertion
Scalable Data and Template
Generator
Kernel #1 Image
Formation
Templates
Benchmark Summary andComputational Challenges
• Pulse compression• Polar Interpolation• FFT, IFFT (corner turn)
• Sequential store• Non-sequential retrieve• Large & small IO
• Large Images difference & Threshold
• Many small correlations on random pieces of large image
• Scalable synthetic data generation
Front-End Sensor Processing
Back-End Knowledge Formation
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Outline
• Introduction
• Kernel Level Benchmarks
• SAR Benchmark
• Release Information
• Summary
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HPEC Challenge Benchmark Release
• http://www.ll.mit.edu/HPECChallenge/ – Future site of documentation and
software
• Initial release is available to PCA, HPCS, and HPEC SI program members through respective program web pages
– Documentation– ANSI C Kernel Benchmarks– Single processor MATLAB SAR System
Benchmark
• Complete release will be made available to the public in first quarter of CY06
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Summary
• The HPEC Challenge is a publicly available suite of benchmarks for the embedded space
– Representative of a wide variety of DoD applications
• Benchmarks stress computation, communication and I/O
• Benchmarks are provided at multiple levels– Kernel: small enough to easily understand and optimize
– Compact application: representative of real workloads
– Single-processor and multi-processor
• For more information, see http://www.ll.mit.edu/HPECChallenge/