Microsoft has launched a new award program that offers Azure cloud resources to scientists whose research could benefit from running big data computations in its cloud.
The company is offering up "large allocations" of Windows Azure storage and compute resources for a period of one year under the new Windows Azure Research Award Program, announced on Tuesday.
"Science is at an inflection point where the challenges of dealing with massive amounts of data and the growing requirements of distributed multidisciplinary collaborations make moving to the Windows Azure cloud extremely attractive," wrote Dennis Gannon, director of cloud research strategy at Microsoft Research Connections, on Monday.
The program builds on the Windows Azure for Research program that Microsoft launched in 2010 to support data-driven scientific research. In Microsoft's own interests, it also sought to find out which scientific applications worked well in Azure and whether science funding agencies viewed cloud computing as an alternative to maintaining their own research computing clusters.
Some of the 80 projects that Microsoft has sponsored in the US, Europe, Asia and Australia under the previous iteration included modelling fire propagation, natural language processing for search engines (a project that used 10,000 cores in Azure), as well as projects to deliver a cloud-based coal supply chain analysis tool, and methods to discover how bacteria like e-coli spread (which used 2,000 cores).
Applicants to the new program must be affiliated with an academic institution or non-profit research laboratory and will need to submit a three page proposal that includes estimates for key resource requirements such as the number of cores and storage.
The first deadline for proposals is 15 October, but Microsoft expects to be awarding 100 projects each year and will periodically announce special targeted requests for proposals. These will cover topics including community research data services, streaming instrument data to the cloud, machine learning in the cloud, large-scale image analysis, environmental science, astronomy, genomics, and urban science.