Performance innovations in the IBM z14 platform
| Autor: | Craig R. Walters, Michael Fee, David S. Hutton, Christine Axnix, Anthony Saporito, Edward W. Chencinski, Ralf Winkelmann, Christian Jacobi |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
010302 applied physics
General Computer Science Firmware business.industry Computer science Hypervisor Multiprocessing 02 engineering and technology computer.software_genre 01 natural sciences Microarchitecture Enterprise system Analytics 020204 information systems 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Operating system Online transaction processing IBM business computer |
| Zdroj: | IBM Journal of Research and Development. 62:7:1-7:11 |
| ISSN: | 0018-8646 |
| DOI: | 10.1147/jrd.2018.2798340 |
| Popis: | The IBM z14 platform brings together numerous innovations that collectively provide considerable performance gains over prior designs for the full spectrum of modern workloads being run on today's enterprise systems. These workloads range from traditional online transaction processing and batch workloads to Linux-based and cloud-based workloads, leveraging advances in analytics, mobile transaction processing, social data mining, cognitive applications, security (blockchain), and other areas. The performance gains in the z14 platform required advancements in the processor hardware microarchitecture, physical design, and instruction-set architecture, as well as in the firmware and hypervisor stacks. The result is a comprehensive platform solution that enables efficient multiprocessor scaling for large single-image partitions and mixed-workload multipartition environments within a single platform, while remaining responsive to the “bursty” demands of batch and transaction-based workloads. The performance gains present in the z14 are a direct result of the collaborative efforts between diverse teams within IBM working together to produce advancements in hardware, firmware, and software that outpace the gains of the individual contributions. In this paper, we discuss these results with a focus on the client value delivered through system performance and workload responsiveness. |
| Databáze: | OpenAIRE |
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