1 / 8

BENCHMARK SUITE

BENCHMARK SUITE. RADAR SIGNAL & DATA PROCESSING. CERES EPC WORKSHOP 2008-10-01. THE BENCHMARK SUITE. The purpose is to evaluate processing architectures with regard to radar signal & data processing requirements The suite comprises Signal processing kernels “front-end” processing

xia
Download Presentation

BENCHMARK SUITE

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. BENCHMARK SUITE RADAR SIGNAL & DATA PROCESSING CERES EPC WORKSHOP 2008-10-01

  2. THE BENCHMARK SUITE The purpose is to evaluate processing architectures with regard to radar signal & data processing requirements The suite comprises • Signal processing kernels • “front-end” processing • data-independent, stream-oriented • Information and knowledge processing kernels • “back-end” processing • data-dependent, thread oriented • Application examples • some of the kernels are used • illustrates complications in data access/movement It is to a large extent based on the HPEC Challenge benchmark suite

  3. THE HPEC CHALLENGE BENCHMARK SUITE Created under the DARPA PCA program, introduced 2005 Nine kernel benchmarks: • Signal processing • Time-domain and frequency-domain FIR filters • QR factorization • Singular value decomposition • Constant false-alarm rate detection • Information and knowledge processing • Pattern matching • Graph optimization via genetic algorithm • Real-time database operation • Communication kernel • Corner turn (memory rearrangement) of a data matrix Metrics • Latency, throughput, efficiency

  4. MORE KERNELS Complement to the HPEC Challenge suite • Fast Fourier Transform • The free FFTW package from MIT • C subroutine library for computing the DFT in one or more dimensions • Benchmark source code and methodology are available • Interpolation kernels • Cubic interpolation • Bi-cubic interpolation • Source code is available

  5. APPLICATIONS different processing directions in chain data access/movement complications when combining kernels channel signal processing kernels range processing chain 1 processing chain 2 pulse

  6. APPLICATIONS • A simplified Doppler signal processing chain • problem: processing along different directions in data set • benchmark: Doppler filtering, pulse compression, CFAR detection • Space-Time Adaptive Processing (STAP) • problem: weight calculations based on a sliding volume in a 3D data set • benchmark: QR decompositions of matrices formed from data in a sliding volume • Synthetic Aperture Radar (SAR) processing • problem: 2D interpolations along tilted paths in memory • benchmark: elementwise addition of data from two matrices accessed along tilted lines

  7. THE PROVIDED SOURCE CODE Single processor code For comparisons/reference Excecutable ”spec” Basis for parallel code, if applicable

  8. Click to edit Master title style Click to edit Master text styles Second level Third level Fourth level Fifth level

More Related