Grid Computing Papers

Storage performance is the most critical component of implementing SAS in a distributed grid environment. This paper provides an introduction to basic storage terminology and concerns. It also describes the best practices used during successful testing with SAS and several clustered file systems. This paper can be used as a reference guide when configuring a distributed environment that will perform and scale to meet the needs of your organization.    Available in PDF

Grid computing promises many benefits, including improved performance of applications, higher resource utilization, lower cost of ownership, and flexibility for your IT infrastructure. This paper describes many of the business issues that can be addressed by SAS Grid Computing, as well as provide code examples of how to implement SAS applications on the grid. Learn how you can use SAS Grid Computing to modernize your existing SAS® environment and add new value to your existing applications with little or no change.    Available in PDF. Presentation available in PPS.

SAS® Data Integration Studio and SAS® Grid Manager add capabilities to the SAS® product suite to distribute workloads across a grid of computers and thereby allow large processes to complete more quickly than previously possible. SAS Grid Manager has been incorporated into SAS Data Integration Studio to facilitate using grid resources for any long-running task that can be processed in parallel to another task. This paper discusses typical data integration workloads, how to scale them on typical grid computing hardware, and the new capability to load balance multiple data integration tasks across grid resources.    Available in PDF. Presentation available in PPS.

This paper introduces the PROC SCAPROC procedure, the SAS Code Analyzer that is new in Release 9.2 of Base SAS® Software. We will examine the advantages of using the procedure, its syntax and phases of execution, and the output that the procedure can produce. This procedure greatly facilitates grid enabling your existing SAS programs.    Available in PDF. Presentation available in PPS.

This paper will address a variety of SAS® servers and how they can be used to balance workload and work together to provide scalability in a SAS Enterprise deployment. We will discuss a variety of servers including stored process servers, workspace servers, data step batch servers, and grid servers. We also will discuss the options for using these servers to balance load and provide solutions that can leverage a scale-out architecture.   Available in PDF. Presentation available in PPS.

SAS Grid Computing is a scale-out SAS solution that enables SAS applications to better utilize computing resources. When architecting a SAS Grid Computing solution it is important to understand the components required to ensure a scalable and high optimized solution. This paper details some of the components necessary to architect and tune a SAS Grid Computing solution.   Available in PDF

The time has come when a $2,000,000 SMP UNIX server can be replaced by a $200,000 grid of even greater performance, reliability, and fault tolerance. We'll discuss the considerations made in selecting the key grid components: grid node hardware, network in frastructure, and storage strategy. We'll look at detailed performance metrics of our pilot grid, which executes single-threaded and massively parallel SAS workloads using SAS Grid Manager software on Linux. We'll discuss details down to the MB/s and how you can choose the right hardware for your processing needs, given your budget. Finally, we'll discuss the business challenges of implementing a grid, including convincing your leadership of a grid's value, working with the IT Department, and software licensing.    Available in PDF.

This presentation gives guidelines and best practices for creating a successful SAS grid architecture. A key component to the success of Enterprise grids accessing large amounts of data is a high performance shared file infrastructure. Examples are given of running a SAS grid with different shared filesystems that provide scalable and sustainable I/O throughput as the size of the grid increases. The goal of this information is to present a variety of viable architectures for a SAS grid environment.    Available in PPS

Grid computing is quickly growing in importance as a way to harness the power of distributed computing resources. This white paper focuses on the evolution of grid computing with SAS and discusses the benefits it can bring to your organization, including increased performance, massive scalability and greater availability. The paper also includes several real-world examples of the power of SAS Grid Computing.    Available in PDF

Learn how grid computing and scheduling have been incorporated and automated to deliver value in a highly efficient manner for SAS analytics, data integration (ETL), data mining and business intelligence. Also learn about advanced configuration options that you can use to fine-tune your SAS grid environment and allow multiple applications to efficiently and dynamically use a virtual IT infrastructure.   Available in PDF

The world of data warehousing, data marts, and data integration continues to progress as more complex Business Intelligence environments become more widespread. This paper discusses the new and improved capabilities of SAS Data Integration Server including parallel execution of processes in a grid and working with parallel storage.    Available in PDF

Grid computing is about leveraging your available resources and idle processor cycles to more quickly solve a problem while at the same time maximizing efficiency and reducing your total cost of ownership. This paper will discuss how SAS works in a grid, the types of applications that are well suited to grid computing and success stories using SAS in a grid.   Available in PDF

This paper introduces MP CONNECT technology and how it can be used to run portions of your applications in parallel to reduce the total elapsed time required to complete your job.  Available in PDF

This paper describes how to use MP CONNECT and the SAS macro facility to accomplish grid or high performance computing. A "divide and conquer" approach was taken to leverage the processing power of a variety of machines, using them in parallel to dramatically reduce the processing time of a Monte Carlo simulation. You can also download this ZIP file, which contains the SAS file used in the Monte Carlo simulation discussed in this paper.   Available in PDF

As data proliferates, organizations are taking advantage of data mining techniques to develop tactical and strategic insight into these vast data stores. Read how SAS parallel scoring can support an enterprise-class data mining operation.   Available in PDF