For batch processes in a CPU-limited system, input/output (I/O) makes a bad situation worse. Generally the lowest priority in the system, a batch workload barely runs when there's a CPU bottleneck, as it competes with online transactions. With every I/O, a job gives up the CPU and higher-priority work takes it over. Even if the I/O process is completed quickly, the batch job must climb up the dispatcher chain for another chance at the processor, which slows down the workload's completion.
Online transactions typically get the necessary CPU time. The I/O process won't slow down a Customer Information Control System (CICS) or Information Management System (IMS) workload because each performs asynchronous I/O.
However, the effect of CPU bottlenecks on individual transactions may be the same as for batch. With CICS, once the I/O completes the transaction, it has to climb CICS' dispatcher chain before it proceeds. This is especially noticeable in CICS workloads that have deep dispatch queues.
Transactions with IMS run in Message Processing Regions (MPR's) take a different path, but the results are the same. Once the database I/O is complete, IMS posts the MPR, which then competes with all the other address spaces on the mainframe before it can do more work.
The fastest I/O is the one you don't do. Therefore, to prevent a bottleneck in a CPU-limited environment, take advantage of data in-memory wherever possible. In-memory data includes buffer pools, reference tables, caching or data spaces and other options.
About the author:
Robert Crawford spent 29 years as a systems programmer, covering CICS technical support, Virtual Storage Access Method, IBM DB2, IBM IMS and other mainframe products. He programmed in Assembler, Rexx, C, C++, PL/1 and COBOL. Crawford is currently an operations architect based in south Texas, establishing mainframe strategy for a large insurance company.
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