[ Team LiB ]
1.2 Scope of Parallel Computing
Parallel computing has made a tremendous impact on a variety of areas ranging from
computational simulations for scientific and engineering applications to commercial applications
in data mining and transaction processing. The cost benefits of parallelism coupled with the
performance requirements of applications present compelling arguments in favor of parallel
computing. We present a small sample of the diverse applications of parallel computing.
1.2.1 Applications in Engineering and Design
Parallel computing has traditionally been employed with great success in the design of airfoils
(optimizing lift, drag, stability), internal combustion engines (optimizing charge distribution,
burn), high-speed circuits (layouts for delays and capacitive and inductive effects), and
structures (optimizing structural integrity, design parameters, cost, etc.), among others. More
recently, design of microelectromechanical and nanoelectromechanical systems (MEMS and
NEMS) has attracted significant attention. While most applications in engineering and design
pose problems of multiple spatial and temporal scales and coupled physical phenomena, in the
case of MEMS/NEMS design these problems are particularly acute. Here, we often deal with a
mix of quantum phenomena, molecular dynamics, and stochastic and continuum models with
physical processes such as conduction, convection, radiation, and structural mechanics, all in a
single system. This presents formidable challenges for geometric modeling, mathematical
modeling, and algorithm development, all in the context of parallel computers.
Other applications in engineering and design focus on optimization of a variety of processes.
Parallel computers have been used to solve a variety of discrete and continuous optimization
problems. Algorithms such as Simplex, Interior Point Method for linear optimization and Branch-
and-bound, and Genetic programming for discrete optimization have been efficiently
parallelized and are frequently used.
1.2.2 Scientific Applications
The past few years have seen a revolution in high performance scientific computing
applications. The sequencing of the human genome by the International Human Genome
Sequencing Consortium and Celera, Inc. has opened exciting new frontiers in bioinformatics.
Functional and structural characterization of genes and proteins hold the promise of
understanding and fundamentally influencing biological processes. Analyzing biological
sequences with a view to developing new drugs and cures for diseases and medical conditions
requires innovative algorithms as well as large-scale computational power. Indeed, some of the
newest parallel computing technologies are targeted specifically towards applications in
bioinformatics.
Advances in computational physics and chemistry have focused on understanding processes
ranging in scale from quantum phenomena to macromolecular structures. These have resulted
in design of new materials, understanding of chemical pathways, and more efficient processes.
Applications in astrophysics have explored the evolution of galaxies, thermonuclear processes,
and the analysis of extremely large datasets from telescopes. Weather modeling, mineral
prospecting, flood prediction, etc., rely heavily on parallel computers and have very significant
impact on day-to-day life.