The high-end Power10 server launched last year has enjoyed “fantastic” demand, according to IBM. Let’s look into how IBM Power has maintained its unique place in the processor landscape.

This article is a bit of a walk down memory lane for me, as I recall 4 years working as the VP of Marketing at IBM Power back in the 90s. The IBM Power development team is unique as many of the engineers came from a heritage of developing processors for the venerable and durable mainframe (IBMz) and the IBM AS400. These systems were not cheap, but they offered enterprises advanced features that were not available in processors from SUN or DEC, and are still differentiated versus the industry standard x86.

While a great deal has changed in the industry since I left IBM, the Power processor remains the king of the hill when it comes to performance, security, reliability, availability, OS choice, and flexible pricing models in an open platform. The new Power10 processor-based systems are optimized to run both mission-critical workloads like core business applications and databases, as well as maximize the efficiency of containerized and cloud-native applications.

What has IBM announced?

IBM introduced the high-end Power10 server last September and is now broadening the portfolio with four new systems: the scale-out 2U Power S1014, Power S1022, and Power S1024, along with a 4U midrange server, the Power E1050. These new systems, built around the Power10 processor, have twice the cores and memory bandwidth of the previous generation to bring high-end advantages to the entire Power10 product line. Supporting AIX, Linux, and IBM i operating systems, these new servers provide Enterprise clients a resilient platform for hybrid cloud adoption models.

The latest IBM Power10 processor design includes the Dual Chip Module (DCM) and the entry Single Chip Module SCM) packaging, which is available in various configurations from four cores to 24 cores per socket. Native PCIe 5th generation connectivity from the processor socket delivers higher performance and bandwidth for connected adapters. And IBM Power10 remains the only 8-way simultaneous multi-threaded core in the industry.

An example of the advanced technology offered in Power10 is the Open Memory Interface (OMI) connected differential DIMM (DDIMM) memory cards delivering increased performance, resilience, and security over industry-standard memory technologies, including the implementation of transparent memory encryption. The Power10 servers include PowerVM Enterprise Edition to deliver virtualized environments and support a frictionless hybrid cloud deployment model.

Surveys say IBM Power experiences 3.3 minutes or less of unplanned outage due to security issues, while an ITIC survey of 1,200 corporations across 28 vertical markets gives IBM Power a 99.999% or greater availability rating. Power10 also stepped up the AI Inferencing game with 5X faster inferencing per socket versus Power9 with each Power10 processor core sporting 4 Matrix Math Accelerators.

But perhaps even more telling of the IBM Power strategy is the consumption-based pricing in the Power Private Cloud with Shared Utility Capacity commercial model allowing customers to consume resources more flexibly and efficiently for all supported operating systems. As x86 continued to lower server pricing over the last two decades, IBM has rolled out innovative pricing models to keep these advanced systems more affordable in the face of ever-increasing cloud adoption and commoditization.

Conclusions

While most believe that IBM has left the hardware business, the company’s investments in underlying hardware technology at the IBM Research Labs, and the continual enhancements to IBM Power10 and IBM z demonstrate that the firm remains committed to advanced hardware capabilities while eschewing the battles for commoditized (and lower margin) hardware such as x86, Arm, and RISC-V.

Enterprises demanding more powerful, flexible, secure, and yes, even affordable innovation would do well to familiarize themselves with IBM’s latests in advanced hardware designs.

IBM is continuing its effort to democratize blockchain technology for developers. The company announced the availability of the IBM Blockchain Platform Starter Plan designed to provide developers, startups and enterprises the tools for building blockchain proofs-of-concept and an end-to-end developer experience.

“What do you get when you offer easy access to an enterprise blockchain test environment for three months?” Jerry Cuomo, VP of blockchain technology at IBM, wrote in a blog post. “More than 2,000 developers and tens of thousands of transaction blocks, all sprinting toward production readiness.”

RELATED CONTENT: Unlocking the blockchain potential

IBM has been focused on bringing the blockchain to enterprises for years. Earlier this year, the company announced IBM Blockchain Starter Services, Blockchain Acceleration Services and Blockchain Innovation Services.

The platform is powered by the open-source Hyperledger Fabric framework, and features a test environment, suite of education tools and modules, network provisioning, and $500 in credit for starting up a blockchain network. Hyperledger Fabric is an open-source blockchain framework implementation originally developed by Digital Asset and IBM.

According to the company, the Blockchain Platform was initially built for institutions working collectively towards mission-critical business goals. “And while Starter Plan was originally intended as an entry point for developers to test and deploy their first blockchain applications, users also now include larger enterprises creating full applications powered by dozens of smart contracts, eliminating many of the repetitive legacy processes that have traditionally slowed or prevented business success,” Cuomo explained.

Other features include: access to IBM Blockchain Platform Enterprise Plan capabilities, code samples available on GitHub, and Hyperledger Composer open-source technology.

“Starter Plan was introduced as a way for anyone to access the benefits of the IBM Blockchain Platform regardless of their level of blockchain understanding or production readiness. IBM has worked for several years to commercialize blockchain and harden the technology for the enterprise based on experience with hundreds clients across industries,” Cuomo wrote.

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Predictive maintenance based on machine learning has reached the point where it can benefit virtually every manufacturer, big or small, an expert will tell engineers at the upcoming Pacific Design & Manufacturing Show.

Kayed Almasarweh, IBM’s Watson and cognitive solutions lead, contends that machine learning and artificial intelligence can minimize unplanned downtime, eliminate maintenance guesswork, optimize supply chain management, and reduce warranty costs in products, if used correctly. “This is not only for big manufacturing operations; it’s for everybody,” Almasarweh told Design News. “Once you get it implemented with the right data, you can get a return on investment almost immediately.”

Kayed Almasarweh of IBM: “This is not only for big manufacturing operations; it’s for everybody.” (Image source: IBM)

Almasarweh will provide a high-level view of predictive maintenance based on machine learning in a session titled, "Applying IoT and Machine Learning for Predictive Maintenance," at the Anaheim Convention Center on February 6th. At the session, he will discuss challenges, successes, and lessons learned using real-life examples from industry.

Today, Almasarweh said, applications for predictive maintenance are widespread and growing by the day. The technology could be applied to CNC machines, assembly robots, conveyor belts, stamping machines, chain rails, locomotives, trucks, and just about any other imaginable factory asset, he noted. “As long as the asset is used by a business to generate revenue, make products, or move things, it’s a target for predictive maintenance,” he told us.

To a large degree, predictive maintenance is being fueled by the broader availability of data in virtually all kinds of businesses, Almasarweh said. Many businesses have sensors in place, as well as access to data storage in the cloud. Moreover, central processing units (CPUs) and graphics processing units (GPUs) have improved so dramatically in the past decade that many can now analyze hundreds of millions of transactions per second. Together, the sensors, storage, and computing capabilities are creating a foundation for machine learning and artificial intelligence that hasn’t been available previously.

“Data is the heart of being able to do machine learning and AI,” Almasarweh said.

To get started, some manufacturers may need to bring in past information, such as data about previous machine failures and parameters that were captured along the way to those failures. In those cases, the data may be stored on electronic media, or even on paper, in files or folders.

Once the data is available, Almasarweh said, implementation of predictive maintenance involves one of two approaches. Manufacturers can purchase a machine learning model or develop one themselves. Those who develop their own models tend to be larger enterprises with bigger engineering staffs.

Either way, he said, the potential benefits are there. “If your maintenance costs are spinning out of control and it’s keeping your plant manager up at night, then you probably need to look at predictive maintenance,” he said. “It’s something that works and something that keeps getting better with time.”

Senior technical editor Chuck Murray has been writing about technology for 34 years. He joined Design News in 1987, and has covered electronics, automation, fluid power, and auto.

Credit: IBM

Integrated services company Downer has entered into a 10-year collaboration deal with IBM Consulting to explore possibilities working with artificial intelligence (AI) and other technologies in reducing its carbon footprint across its rail and transit systems. 

Downer first began working with IBM in 2017 to modernise its technology platform, embedding digital and intelligent capabilities into its civil infrastructure operations.

The platform now uses IBM Maximo along with IBM Cognos Analytics with Watson to Excellerate availability, reliability and safety of its services and the fleets it maintains for customers.

This next phase of Downer’s digital transformation journey will involve a range of IBM technologies and services that work together to provide Downer a single view of the life, health and carbon footprint of all assets within the Rail and Transit Systems division, while working to keep it secure from cyber security threats.

“Sustainability is a critical focus for Downer and our customers. We have a clear roadmap to get to Net Zero by 2050,” Downer head of growth for rail and transit systems Adam Williams said.