haney - 1 hpec 10/20/2005 mit lincoln laboratory the hpec challenge benchmark suite ryan haney,...

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.

MIT Lincoln LaboratoryHaney - 2

HPEC 10/20/2005

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


HPEC 10/20/2005

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


HPEC 10/20/2005

Outline

• Introduction

• Kernel Level Benchmarks

• SAR Benchmark– Overview– System Architecture– Computational Components

• Release Information

• Summary


HPEC 10/20/2005

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


HPEC 10/20/2005

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


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


HPEC 10/20/2005

SARImage

Knowledge Formation

SARImageFiles

RawSARFile

TemplateFiles

Groups ofTemplateFiles

RawSARFiles

Kernel #2Image Storage

SARImageFiles

DetectionFiles

Kernel #3Image

Retrieval

TemplateFiles

TemplateFiles

Groups of Template

Files


Image Files

Sensor Processing

Raw SAR Data Files

ValidationDetectionsKernel #4

Detection

SARImage

Templates

Data Generation and Computational Stages

RawSAR

Templates

SARImage

TemplateInsertion


Generator

Kernel #1 Image

Formation

Templates


HPEC 10/20/2005

• 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


HPEC 10/20/2005

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


HPEC 10/20/2005

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


HPEC 10/20/2005

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


HPEC 10/20/2005

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


HPEC 10/20/2005

ValidationDetectionsKernel #4

Detection

SARImage

Templates

RawSAR

Templates

SARImage

TemplateInsertion


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


HPEC 10/20/2005

Outline

• Introduction

• Kernel Level Benchmarks

• SAR Benchmark

• Release Information

• Summary


HPEC 10/20/2005

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


HPEC 10/20/2005

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/

haney - 1 hpec 10/20/2005 mit lincoln laboratory the hpec challenge benchmark suite ryan haney,...

Documents

templates image

sar image formation

large image

mit lincoln laboratory

raw sar crossrange

template generator kernel

flight path sar overview

template max