I would like too see another great search-engine like Google, I used Yahoo! for years until Google became faster and more accurate than Yahoo!

Theres 1 question ramaining unclear for me as i read this article:

Does speeding up the indexing of pages also speed up the search results? I think no. And does it mean there are better search results with the use of this grid? It only seems to be a matter of more efficient cpu-use.

Given greater CPU work for a given set of hardware, certainly costs and electical power usage are reduced. But increasing the total CPU work available can also enable new levels of data analysis and algorithms that were unfeasable without the horsepower for them. A decade ago I helped a major airline upgrade from an SGI sever to a cluster of IBM SP2 supercomputers and massive storage arrays - and they began using data an entire magnitude larger and more complete in their load forcasting calculations. They did re-write the software (had to paralleize it explicitly as they moved from SMP to MPP, and change the calculations to use more granular data), but the notion of what they were doing didn't change - just the data and ability to sift through more of it. Apparently they gained quite better results, once they tuned the new forecasting system's parameters.

Okay, so, I've not actually read the article (I might do in a minute) but I thought that there was a rule that stated all items with "Yahoo!" in the title had to have an exclamation mark after every word in the headline.....

no?

oh well.

coat, retrieved, donned, and left the building.

SMP=Symmetric Multi-Processing

MPP=Massivly Parallel Processing

With an SMP box, there is a single OS image that schedules applications across the processors. If you write threaded code, then most SMP implementations will schedule threads on seperate processors without you having to write the code to explicitly taks into account the fact that there are multiple processors.

With MPP, there are multiple OS images in the cluster, and you have to write to an API that will allow different units of work to be placed on different systems. This means you have to make the application much more aware of the shape of the cluster. This also means that if not written carefully, you may not get better performance by adding additional nodes into the cluster.

Unfortunatly, too many IBM SP/2 implementions were not really parallel processing clusters, more like lan-in-a-can systems (goodness, where did I dredge that term up from).

But what Google does is a quantum leap up from what SP/2s were capable of, and are much more like Mare Nostrum and Blue Gene/L.

Sorry, I thought that the "granulising data" was reasonabily obvious and didn't think that it needed explaining, so assumed that it was the other terms that needed explaining. My bad.