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Deployment



The wrong choice here could lock an enterprise into an architecture that is dependent on specific versions of its subsystem, and really limiting the role and value of the mainframe in term of integration. MIPS control and upgrade avoidance are the order of the day and really need to give deployment options a high priority to keep costs in line. The alternative could be as bad as increased costs, or as dramatic as total failure. The proverbial lose-lose.

It is worth noting that Linux on System z holds tremendous potential in this areas and Linux on System z deserves investigation as the place to house this workload to ensure a high-performance, low-cost execution option.

Over the past decade, three specialty engines - Integrated Facility for Linux (IFL), System z Application Assist Processor (zAAP), and System z Integrated Information Processor (zIIP) - have evolved, each one optimized as a compelling alternative to attract specific new workloads.
They offload the processing of applications from the mainframe's General Purpose Processor (GPP) and run the target workload more effectively. Specialty engines also change the economics by providing a life-cycle cost of the solution that is substantially lower than the cost of traditional mainframe software. In short, shifting transactional workloads from the GPP to specialty engines is a smart move - one that dramatically slashes the costs of mainframe integration within modern computing initiatives.

Specialty engines save money by allowing the enterprise to leverage mainframe computing power for new workloads and specific types of processing without substantially impacting the software costs associated with running and managing the mainframe environment.
By hosting specialized workloads, specialty engine processing is excluded from the overall MIPS or MSU ratings that determine mainframe software costs. Also, any work running on specialty engines frees up cycles on traditional processors; which stretches out software maintenance cycles, and, of course, reduces long-term costs.

These reductions in CPU consumption and associated costs, as well as the strong performance gains offered by specialty engine exploitation, tell a compelling story - in effect, run intensive workloads on a specialty engine and not only save money, but achieve higher performance while enhancing the relevance of a core computing platform.

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