Title       : Scalable Submesh Computing
Type        : Award
NSF Org     : DMS 
Latest
Amendment
Date        : August 10,  2000    
File        : a0074278

Award Number: 0074278
Award Instr.: Standard Grant                               
Prgm Manager: Jong-Shi Pang                           
              DMS  DIVISION OF MATHEMATICAL SCIENCES       
              MPS  DIRECT FOR MATHEMATICAL & PHYSICAL SCIEN
Start Date  : August 15,  2000    
Expires     : June 30,  2003       (Estimated)
Expected
Total Amt.  : $155000             (Estimated)
Investigator: Jan Mandel  (Principal Investigator current)
Sponsor     : U of Colorado Denver
              Campus Box 123 PO Box 173364
              Denver, CO  802173364    303/629-2642

NSF Program : 1271      COMPUTATIONAL MATHEMATICS
Fld Applictn: 0000099   Other Applications NEC       
Abstract:

We will develop new algorithms, mathematical foundations, and a new
programming methodology for the fast parallel solution of elliptic
problems with aspects that are crucial in practice but present serious
difficulties to existing methods. We will investigate new robust iterative
substructuring methods that perform well even in the presence of interface
roughness on element scale. The performance of existing methods
deteriorates in this case, but smooth decompositions are typically not
available in practice. We also propose to investigate fast methods for the
discretization and iterative solution of high frequency wave propagation
and scattering problems by representing the solution locally as a
combination of waves on a coarse mesh and exploiting connections with the
fast multipole method. Finally, we propose to develop new programming
approaches and prototype tools for latency tolerant implementation on
parallel machines, transforming a high level program with new directives
into multiple independent tasks queued on processors.

The project will advance the state of the art in modeling complicated
problems in Mechanical Engineering with irregular geometries on
high-performance computers with high accuracy and efficiency, improve the
technology underlying radar, sonar, and ultrasound imaging, and create a
new highly efficient methodology and prototype tools for High-Performance
Computing. Potential applications include computational analysis and
modeling of automobiles and aircrafts and accurate high resolution
ultrasound imaging. It is expected that the new methodology for
High-Performance Computing will be important for futuristic technologies,
where the speed of light is the limiting factor of communication between
the processors, as well as for more immediate distributed computing on
networks of computers.