Article 5XXS9 The First IBM Mainframe For AI Arrives

The First IBM Mainframe For AI Arrives

by
BeauHD
from Slashdot on (#5XXS9)
An anonymous reader quotes a report from ZDNet, written by Steven Vaughan-Nichols: Mainframes and AI? Isn't that something like a Model-T Ford with a Tesla motor? Actually, no. Mainframes are as relevant in 2022 as they were in the 1960s. IBM's new IBM z16, with its integrated on-chip Telum AI accelerator, is ready to analyze real-time transactions, at scale. This makes it perfect for mainframe mission-critical workloads such as healthcare and financial transactions. This 21st century Big Iron AI accelerator is built onto its core Telum processor. With this new dual-processor 5.2 GHz chip and its 16 cores, it can perform 300 billion deep-learning inferences per day with one-millisecond latency. Can you say fast? IBM can. Anthony Saporito, a senior technical staff member for IBM Z hardware development, said "One of the Telum design's key innovations is we built an AI accelerator right onto the silicon of the chip and we directly connected all of the cores and built an ecosystem up the stack. Through the hardware design, firmware, the operating systems, and the software, deep learning is built into all of the transactions." According to Patrick Moorhead, Moor Insights & Strategy's chief analyst, "The AI accelerator is a game-changer. The z16 with z/OS has a 20x response time with 19x higher throughput when inferencing compared to a comparable x86 cloud server with 60ms average network latency." The new model z16 also includes a so-called quantum-safe system to protect organizations from near-future threats that might crack today's encrypted files. This is done with the z16's support of the Crypto Express8S adapter. Built around a CCA cryptographic coprocessor and a PKCS #11 cryptographic coprocessor, it enables users to develop quantum-safe cryptography. It also works with classical cryptography. If you want your data and transactions to be safe both today and tomorrow, this deserves your attention.

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