A lot has changed Since 2014. Check-out the updated publication that compares and contrasts this article definition of a SAS grid to 2019 by clicking below:
The Life Science and SAS Grid Collaboration: Past, Present, and Future
June 2014 - most life sciences and healthcare organizations, "Big Data" means big trouble. Although a growing amount of pressure is being placed on both sectors to both speed up and improve the accuracy of data analysis, our economic climate tends to make it almost impossible to actually achieve these objectives. Data is rapidly and continuously pouring in from numerous platforms, making it imperative that IT be able to instantaneously capture, organize, and interpret information in such a way that it can be shared and used to cut costs and improve efficiency without sacrificing the quality of patient care.
Unfortunately, many organizations struggle with constraints on processing power, budget cuts, and the limitations of existing computing infrastructures, which yields higher costs, replicate runs of identical tasks, reduced performance rates, and decreased accuracy. As a result, a growing number of companies are beginning to realize the benefits of grid computing, with a lot of attention being given to SAS® GRID computing. Could this be the solution you've been looking for? In this post, we'll take an objective look at grid computing with SAS, its practical uses, and its benefits.
What is SAS GRID computing?
The belief behind grid computing with SAS is that pharmaceutical manufacturers, hospitals, insurance agencies, and other related healthcare operations should be able to obtain faster results, and should be empowered to make more efficient use of the compute power that they already have. SAS GRID computing enables users to develop a controlled, shared environment that's dedicated to processing large volumes of data and analytic programs - fast. This is accomplished through the use of dynamic, resource-based load balancing.
What this does is create a secure, networked environment that allows for the coordinated sharing of heterogeneous computing resources. This means that all users are able to access useful information and obtain their answers quicker and more efficiently. Individual SAS jobs can also be split and run parallel to one another across multiple nodes. Ultimately, this reduces time, labor, and costs while allowing for a more flexible and scalable infrastructure.
Which applications are suitable for grid computing with SAS?
In order to take on a realistic approach to discussing the advantages and outcomes of utilizing SAS grid computing, it's important to first define the specific types of applications that actually lend themselves to this type of compute grid implementation. As a general rule of thumb, applications that require many hours (or multiple days or weeks) to run can be considered strong candidates for grid computing. Such a long run time may be indicative of the application demanding replicate runs of the same fundamental task, the processing of extremely large amounts of data, or the decomposition of the application into execution units, data subsets, or both. If any of these characteristics are applicable to your existing applications, compute grid implementation could be the ideal solution.
What are the benefits of SAS grid computing?
Grid computing with SAS is capable of offering significant benefits, such as:
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Cost savings through faster and more efficient analysis, as well as leveraging and exploiting under or unutilized computing resources within the network.
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Improved business agility through reducing processing times and delivering faster results. This allows your operation to make better, more accurate business decisions for a fraction of the time and cost.
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Enhanced collaboration is encouraged, enabling valuable resources to be shared and utilized collectively, efficiently, and effectively. In this way organizations are better equipped to accomplish their goals to reduce costs and improve productivity.
After all has been said and done, the bottom line is this: if you're working in either the life science or healthcare sector and your current applications require the ongoing organization and analysis of extremely large sets of data that are not currently being harnessed in a timely or cost-efficient manner, you could benefit from grid compute implementation. Reach out to a professional to discuss your specific needs and options, and to determine whether the SAS grid is ideal for your enterprise.
