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Sunday, October 4, 2009

SAL: Parallel Computing

Parallel computing extends to systems with more processors to obtain
speedup in code execution. The efficiency and effectiveness of the
parallelism are largely dependent on the problems to be solved with
selected algorithms and hardware architectures. Based on load
distribution and synchronization implementations, SIMD, MIMD, SPMD, and
many other "fashions" have been categorized. Recently, multi-threading
programming on SMP (Symmetrical Multiprocessor) architectures and
message-passing programming on distributed memory systems (or even
clustering systems) are becoming more and more popular. After all,
scientific applications are still the major motivation behind the
development of parallel computing technologies.

Go there for more links and info...
http://www.sai.msu.su/sal/C/

Don

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