Texas Tech Chooses SAS for Grid Computing

Grid computing at the heart of new advanced analytics and business intelligence center -- SAS, the leader in business intelligence, today announced that Texas Tech University has chosen SAS as one of the key applications to support grid computing across the campus. With grid computing, Texas Tech will be able to handle various research projects throughout the university with greater efficiency and effectiveness. Texas Tech is one of the first universities in Texas to use grids to enable professors and businesses to solve compute-intensive business intelligence (BI) projects. "Texas Tech University recently embarked on a high-performance computing initiative to use grid computing to leverage resources campus-wide,” said Peter Westfall, director of the Center for Advanced Analytics and Business Intelligence at Texas Tech. “SAS’ advanced multiprocessing capabilities are critical in driving the success of this initiative and enabling us to be innovative, such as in the creation of our advanced analytics and business intelligence center. With SAS, we are able to significantly improve the performance of particular projects that would normally require a great deal of time and resources.” Grid computing is a method of harnessing the power of many computers in a network to solve problems that require a large number of processing cycles and involve huge volumes of data. Grid computing taps the unused processor capacity of hundreds, sometimes even thousands, of computers. In this way, users can achieve much faster results on large projects at a lower cost. Added Westfall, “People here are excited when they see that whatever job they need done runs in the background, and they don’t even notice that their computer is being used.” Texas Tech has used SAS to grid-enable various applications, focusing initially on finance, but plans to expand to other areas, such as genomics, in the future. One recent Texas Tech project involved analyzing stock portfolios to highlight a methodology in selecting and managing various portfolios, a process that will benefit financial service companies. This analysis was accomplished in 14 days. Without grid, it would have required more than 500 days of continuous computing time on a dedicated machine. According to Westfall, “The SAS grid is the only viable option in which to accomplish this.” In addition, Texas Tech used grid computing to identify how anomalies (e.g., hurricanes) can affect stock prices, thus creating a process that the financial community can use to better predict and manage certain situations. The time to process this level of data was significantly decreased, reducing what would normally take more than a week to just one afternoon. "Grid computing is becoming increasingly necessary as organizations look for ways to quickly and cost-effectively process and analyze all the data available to them,” said Keith Collins, chief technology officer at SAS. “SAS’ large-scale parallel processing capabilities allow our customers to effectively handle compute-intensive applications while reducing execution time and total cost of ownership. Grid computing is becoming more mainstream, and Texas Tech is enabling that at a local level through its new business intelligence center, which can accommodate academic needs as well as more commercial requests.”