IBM mainframe chip to run Arm and Z workloads on the same cores

IBM plans to release a dual-architecture mainframe processor that can run Arm-native Linux environments simultaneously with z/OS and Linux on IBM Z, marking the first chip of its kind. The 11-core, 5.7GHz chip includes AI inference accelerators for in-transaction fraud detection, a dedicated on-chip data processing unit for I/O acceleration, and a 3.5GB cache architecture. Christian Jacobi, CTO and IBM Fellow, IBM Systems Development, said the processor represents a significant architectural advancement for IBM Z and LinuxONE, bringing Arm natively to the platform.

IBM plans to release a dual-architecture mainframe processor that can run operating systems and applications on both IBM and Arm. The first chip of its kind, the processor can run Arm-native Linux environments simultaneously with z/OS and Linux on IBM Z. Rather than bespoke cores for either system, each is capable of concurrent operations. “As organizations modernize their application portfolios and integrate AI into core business operations, they need infrastructure that expands their options,” said Christian Jacobi, CTO and IBM Fellow, IBM Systems Development. “This processor represents a significant architectural advancement for IBM Z and LinuxONE. By bringing Arm natively to our platform, we're combining access to one of the industry's fastest-growing software ecosystems with the qualities that have made IBM systems the foundation for how businesses run today.” The 11-core, 5.7GHz chip includes AI inference accelerators for in-transaction fraud detection, a dedicated on-chip data processing unit for input/output I/O acceleration, and a 3.5GB cache architecture for demanding enterprise workloads. “As AI scales, more of the computing landscape is converging on Arm,” said Mohamed Awad, EVP, Cloud AI, Arm. “IBM Z and LinuxONE power some of the world’s most demanding workloads in highly regulated industries. Bringing Arm compute and its software ecosystem to these platforms will extend that momentum into mission-critical enterprise infrastructure to give organizations greater choice in how they deploy AI.”