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RNI reflects the distribution and latency of sourcing data from shared caches and memory, as shown in Figure 12-3. 

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Many factors influence the performance of a workload. However, these factors often are influencing is the RNI of the workload. The interaction of all these factors results in a net RNI for the workload, which in turn directly relates to the performance of the workload. 

These factors are tendencies, not absolutes. For example, a workload might have a low I/O rate, intensive processor use, and a high locality of reference, which all suggest a low RNI. But, it might be competing with many other applications within the same LPAR and many other LPARs on the processor, which tends to create a higher RNI. It is the net effect of the interaction of all these factors that determines the RNI. 

The traditional factors that were used to categorize workloads in the past are shown with their RNI tendency in Figure 12-4. 

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Little can be done to affect most of these factors. An application type is whatever is necessary to do the job. The data reference pattern and processor usage tend to be inherent to the nature of the application. The LPAR configuration and application mix are mostly a function of what must be supported on a system. The I/O rate can be influenced somewhat through buffer pool tuning. 

However, one factor, software configuration tuning , is often overlooked but can have a direct effect on RNI. This term refers to the number of address spaces (such as CICS application-owning regions [AORs] or batch initiators) that are needed to support a workload. 

