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December 17, 2008
Poor-man's Supercomputing Goes Commercial
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Dec. 17 -- Grid computing technology has long been the darling of cash-strapped academics in desperate need of raw processing power. Now a groundbreaking European research effort has created an industrial-strength platform already appearing in commercial applications.
The SIMDAT project has created a portfolio of tools and services that can finally bring the power of grid computing to industrial applications. Grids capture all the resources of connected computers, from storage to computation.
But up to now grids mostly languished in research labs, where they were used to provide massive processing power or to enable large-scale database management. SIMDAT developed essential business functions for grids, like industrial strength service-level agreements, management and security.
It will mean the advent of virtual organisations, a long-unfulfilled promise of information technology. Grids for business have huge applications in product development, both for data crunching and collaboration, and this was the focus of SIMDAT's work in the automotive, pharmaceutical, aerospace and weather sectors.
But that is the just the beginning, and the ground broken by SIMDAT will prove a fertile field for grid technology over the next decade. Their work and solutions are relevant to other commercial areas and other industrial sectors. SIMDAT partners are already looking at the potential of adapting their work to new industrial sectors, like shipping and media production.
The commercialisation efforts are already well underway and began months before SIMDAT completed the EU-funded part of its work. Elements of SIMDAT's wide-ranging research are already appearing in commercial applications.
Compressed data
Take data compression, for example, one small aspect of SIMDAT's vast research and development programme. SIMDAT made three improvements related to data compression. Large data transfers -- typical in grid applications -- are now more efficient.
First, it boosted basic compression by a factor of 10, a huge achievement in itself. Second, it developed meta-models. By looking at a series of related datasets, computer scientists found that it was possible to 'summarise' their results in a meta-model, and this meta-model provided an accurate analysis of the whole dataset. So data could be exchanged as a meta-model and still be accurate.
The third improvement means it is now possible to make complex queries within summaries (such as why did the behaviour change, or what caused a fault?). By combining these achievements, SIMDAT developed state-of-the-art data compression for industrial grid deployments.
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