![]() ![]() In summary, 1) SAS ® 9.3 ® foundational application performance scales well with added processor count on Intel ® E7 platforms provided the servers are well balanced and configured 2) Proper storage and operating system settings can significantly improve I/O and unlock scalability storage tuning work resulted in 3.0x gains OS configurations yielded 1.5x gains. ![]() ![]() As dataset sizes and analytic complexity and integration grow exponentially in the business analytics field, hardware solutions – multi-core servers, solid state disks, increased memory capacity-evolve to face the challenge In this paper, we present a case study on performance scalability and tuning techniques for SAS ® 9.3 ® analytics applications to address questions SAS BI customers face, namely: Will performance scale if processors / cores are added to servers in an environment with increased dataset sizes and more applications? What factors inhibit performance, and what can be done about it? Our results and analysis – obtained working with IBM x3850* 4-and 8-socket platforms with Intel ® Xeon ® E7 family processors-provide first-hand tangible insights for SAS customers as well as others running similar analytics workloads. ![]()
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