IBM laying foundation for mainframe as ultimate AI server

“It will truly change what customers are able to do with AI,” Stowell said.

IBM’s mainframe processors

The next generation of processors is expected to continue a long history of generation-to-generation improvements, IBM stated in a new white paper on AI and the mainframe.

“They are projected to clock in at 5.5 GHz. and include ten 36 MB level 2 caches. They’ll feature built-in low-latency data processing for accelerated I/O as well as a completely redesigned cache and chip-interconnection infrastructure for more on-chip cache and compute capacity,” IBM wrote. 

Today’s mainframes also have extensions and accelerators that integrate with the core systems. These specialized add-ons are designed to enable the adoption of technologies such as Java, cloud and AI by accelerating computing paradigms that are essential for high-volume, low-latency transaction processing, IBM wrote. 

“The next crop of AI accelerators are expected to be significantly enhanced—with each accelerator designed to deliver 4 times more compute power, reaching 24 trillion operations per second (TOPS),” IBM wrote. “The I/O and cache improvements will enable even faster processing and analysis of large amounts of data and consolidation of workloads running across multiple servers, for savings in data center space and power costs. And the new accelerators will provide increased capacity to enable additional transaction clock time to perform enhanced in-transaction AI inferencing.”

In addition, the next generation of the accelerator architecture is expected to be more efficient for AI tasks. “Unlike standard CPUs, the chip architecture will have a simpler layout, designed to send data directly from one compute engine, and use a range of lower- precision numeric formats. These enhancements are expected to make running AI models more energy efficient and far less memory intensive. As a result, mainframe users can leverage much more complex AI models and perform AI inferencing at a greater scale than is possible today,” IBM stated.



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