Monday, March 24, 2008
Monday, March 17, 2008
Monday, March 10, 2008
Supercomputers are used for extremely calculation-intensive tasks such as weather forecasting, climate research (including research into global warming), molecular modeling (computing the structures and properties of chemical compounds, biological macromolecules, polymers, and crystals), physical simulations (such as simulation of airplanes in wind tunnels, simulation of the detonation of nuclear weapons, and research into nuclear fusion), cryptanalysis, and the like. Military and scientific agencies are important users.
Supercomputers traditionally gained their speed over conventional computers through the use of inventive designs that allow them to perform many tasks in parallel, as well as complex detail engineering. They tend to be specialized for certain types of computation, generally numerical calculations, and perform poorly at more general computing tasks. Their memory hierarchy is very carefully designed to make certain the processor is kept fed with data and instructions at all times—in fact, much of the performance difference between slower computers and supercomputers is due to the memory hierarchy design and componentry. Their I/O systems have a propensity to be designed to support high bandwidth, with latency less of an issue, because supercomputers are not used for transaction processing.
As with all highly parallel systems, Amdahl's law applies, and supercomputer designs devote huge effort to eliminating software serialization, and using hardware to accelerate the remaining bottlenecks.
Monday, March 03, 2008
Alongside this established usage, the phrase natural sciences is also sometimes used more narrowly to refer to its everyday usage, that is, related to natural history. In this sense "natural sciences" may refer to the biology and perhaps also the earth sciences, as illustrious from the physical sciences, including astronomy, physics, and chemistry.
Within the natural sciences, the word hard science is sometimes used to describe those sub-fields that rely on experimental, quantifiable data or the scientific method and focus on accuracy and objectivity. These generally include physics, chemistry and many of the sub-fields of biology. By contrast, soft science is often used to explain the scientific fields that are more reliant on qualitative research, including the social sciences.
There is some explore, collectivelly known as graphism thesis, that indicates that natural science relies on graphs more than soft sciences and mathematics do.