The IBM Z®platform and the underlying processor chip designs supporting it are optimized for processing vast amounts of data and transactions, while delivering consistent system performance, throughput, and response latencies with a sustained processor utilization of over 90 % under all workload conditions in a highly virtualized and secured computing environment. The IBM Telum® series of processor chip designs that support the platform introduced the industry to a novel modular scalable heterogeneous processor compute framework with an integrated multi-tier unified cache hierarchy all within one chip. The processor chip design leverages a unique approach to ensure all elements work in unison to continuously deliver performance to the evolving needs of mission critical workloads running on the platform while responding to those changing demands at processor clock speeds. This paper will detail the varying compute, accelerator, and cache units within the IBM Telum II processor chip design, how they adaptively work in unison without generating a cacophony of agents competing for scarce hardware resources, and how this forms the backbone of the scalable multi-processor system that our modern economy is built upon.

The IBM Z® platform is optimized for processing vast amounts of data and transactions with low latency in a highly virtualized and secured environment. The platform and its microprocessor chip are designed to deliver consistent system performance, throughput, and response latencies with sustained processor utilization of over $\mathbf{9 0 \%}$ under all workload conditions. The IBM Telum® and IBM Telum® ${ }^{\circledR}$ II designs introduced a novel modular and scalable cache hierarchy to the industry that is extendable to future platform generations, the adoption of emerging technologies, and new architecture enhancements, all of which are required to meet the continuously evolving needs of the mission critical workloads that run on the platform. This paper demonstrates the flow of processor fetch events and how the adaptive horizontal cache persistence algorithms work in this novel design. It explores the performance and system effects of cache size changes in this architecture. Finally, the paper explores how the resulting application of solutions leveraging these effects enhances the robustness of the next generation IBM Z caching solution embedded in the IBM Telum® II Processor, which improves mission critical workload performance while simultaneously enabling the generative AI capability.

Larger cache sizes closer to processor cores increase processing efficiency, but physical limitations restrict cache sizes at a given latency. Effective cache capacity can be expanded via the inline compression of data as it enters a lower level cache. Using the IBM Telum®processor cache hierarchy as a comparative baseline, this paper presents a custom compression scheme designed for small, line-sized data blocks, examines op-timal compressor/decompressor placement, solutions to common compression drawbacks, and proposes a tiered design blueprint to facilitate product integration. The impact of compression and prediction-assisted adaptive compression on effective cache capacity, hit rate and access latency across several typical industry workloads is explored.