By Klaus Gottschalk
The Leibniz Supercomputing Centre (LRZ), nestled on the outskirts of Munich in the town of Garching, was established 50 years ago by the Bavarian Academy of Science, to provide supercomputing resources to researchers and scientists across the Munich Scientific Network of universities.
Since then, the Centre has been the home of such systems as the HLRB and HLRB-II and has grown to become the premiere computing operations center for researchers across Europe, as they work to answer computational-intensive scientific questions.
By Edward Walsh
When people speak of Big Data the natural reflex is to envision a big company or government struggling to deal with massive amounts of digital information. It stands to reason that the bigger the organization, the greater the data challenges.
After all, large enterprises serve more customers, manage more employees, maintain more partnerships, and coordinate with more suppliers than small and mid-sized businesses (SMBs). All of those people are collecting, creating, sharing and replicating vast amounts of information – data – at increasing rates.
However, the number of large organizations in the U.S. is dwarfed by the millions of SMBs – the true drivers of the economy. According to the U.S. Census Bureau’s 2010 Statistics of U.S. Businesses, 17,236 firms in the country have more than 500 employees, while 5.7 million firms have less than 500. The challenges this silent majority face managing the data deluge can be far more acute than those of larger, well-resourced enterprises.