Sonar Challenge Problem

1. Sonar Challenge Problem Updated May 23, 2001

2. System Overview • Use existing MFP demo design • Insert adaptive front end (MSEDR) between incoming data stream and existing matched field design • it will adapt the weights used in the existing k-w beamformer • Use the PE1 and PE2 subvoxel beamformers as-is as much as possible.

3. Challenge Overview • Form covariance matrix at 3KHz rate • Requires 96GB/sec memory bandwidth !!!!!! • Inversion of covariance matrix happens every 3-5 seconds • Don’t do inversion • Determine K smallest eigenvalues • K << N, K ~= 10? • Use Lanczos’ method to find eigenvalues • A subspace method which hopefully gives good approximation to R • Do this part on Pentium

4. Forming Covariance Matrix (R) • Forming the covariance matrix (R) • 16MB memory locations updated @ 3KHz rate • Requires 96GB/sec memory bandwidth • SV2 has 6GB/sec memory bandwidth • Solutions • Downsample input data • Multiple boards • 8 SV2 boards can form R 10 PE’s per SV2 read/MAC/write is kernel (2 cycles) pack 2 data elements per memory location one SV2 can do 10 X 1 kernel per cycle = 1500M kernels/sec requirement is 4M kernels @ 3KHz rate = 12000M kernels/sec

5. Forming Covariance Matrix (continued) • Bernecky has recently (since the Midway meeting) suggested a way of doing the R matrix computation in 50x50 chunks, and avoiding most off-chip memory accesses • This is an interesting idea that may or may not work better than the previous slide’s approach. It will be investigated.

6. Rest of Algorithm • Normalization may be required with this algorithm • to be determined by NUWC • prior work (2 years ago) showed normalization doubled computation required, may be the case here • Other things may be need to be included depending on results of NUWC Matlab experiments

7. Statement of 1-Year Goals • Do a lab demonstration of AMFP system • Use recorded data at NUWC • In the absence of a full-up lab demo, have enough of the pieces completed (sizing, design, simulation, or execution) to make a case for or against the approach.

8. Demonstration Architecture • 5 SV2 boards • 4 for creating/updating R (PE0 replacement) • 1 for subvoxel interpolation (PE1 & PE2 replacement) • External Pentium • Requires ACS API + Myrinet

9. Tasks • Determine whether subspace methods will work in this problem (NUWC) • Determine time requirements for Lanczos method on a Pentium (Athanas) • Determine effects of 2X downsampling on algorithm performance (NUWC) • End-to-end MATLAB simulation (NUWC)

10. More Tasks • MSEDR floating point requirements • Formats, rounding modes, etc. (VTech/BYU) • Determine communications requirements/patterns (all) • Create single board MSEDR FPGA design (BYU) • Expand to 4 boards (VTech) • Port 4K subvoxel beamformer design to SV2 (NUWC)

11. Yet More Tasks • Integrate Lanzcos code (VTech) • System integration/test (NUWC)

12. Schedule • Determine whether subspace methods will work in this problem (NUWC) (2 months) • Determine time requirements for Lanczos method on a Pentium (Athanas) (2 months) • Determine effects of 2X downsampling on algorithm performance (NUWC) (3 months) • End-to-end MATLAB simulation (NUWC) (3 months)

13. More Schedule • MSEDR floating point requirements • Formats, rounding modes, etc. (VTech/BYU) (3 months) • Determine communications requirements/patterns (all) (3 months) • Virtex-II JHDL support (3 months) • Create single board MSEDR FPGA design (BYU) (4 months) • Expand to 4 boards (VTech) (10 months) • Port 4K subvoxel beamformer design to SV2 (NUWC) (10 months)

14. Yet More Schedule • Integrate Lanzcos code (VTech) (11 months) • System integration/test (VTech/NUWC) (12 months)