Posts Tagged ‘AI’

Get a Next-Gen Datacenter with IBM-Nutanix POWER8 System

July 14, 2017

First announced by IBM on May 16 here, this solution, driven by client demand for a simplified hyperconverged—combined server, network, storage, hardware, software—infrastructure, is designed for data-intensive enterprise workloads.  Aimed for companies increasingly looking for the ease of deployment, use, and management that hyperconverged solutions promise. It is being offered as an integrated hardware and software offering in order to deliver on that expectation.

Music made with IBM servers, storage, and infrastructure

IBM’s new POWER8 hyperconverged solutions enable a public cloud-like experience through on-premises infrastructure with top virtualization and automation capabilities combined with Nutanix’s public and on-premises cloud capabilities. They provide a combination of reliable storage, fast networks, scalability and extremely powerful computing in modular, scalable, manageable building blocks that can be scaled simply by adding nodes when needed.

Over time, IBM suggests a roadmap of offerings that will roll out as more configurations are needed to satisfy client demand and as feature and function are brought into both the IBM Cognitive Systems portfolio and the Nutanix portfolio. Full integration is key to the value proposition of this offering so more roadmap options will be delivered as soon as feature function is delivered and integration testing can be completed.

Here are three immediate things you might do with these systems:

  1. Mission-critical workloads, such as databases, large data warehouses, web infrastructure, and mainstream enterprise apps
  2. Cloud native workloads, including full stack open source middleware, enterprise databases
    and containers
  3. Next generation cognitive workloads, including big data, machine learning, and AI

Note, however, the change in IBM’s pricing strategy. The products will be priced with the goal to remain neutral on total cost of acquisition (TCA) to comparable offerings on x86. In short, IBM promises to be competitive with comparable x86 systems in terms of TCA. This is a significant deviation from IBM’s traditional pricing, but as we have started to see already and will continue to see going forward IBM clearly is ready to play pricing flexibility to win the deals on products it wants to push.

IBM envisions the new hyperconverged systems to bring data-intensive enterprise workloads like EDB Postgres, MongoDB and WebSphere into a simple-to-manage, on-premises cloud environment. Running these complex workloads on IBM Hyperconverged Nutanix POWER8 system can help an enterprise quickly and easily deploy open source databases and web-serving applications in the data center without the complexity of setting up all of the underlying infrastructure plumbing and wrestling with hardware-software integration.

And maybe more to IBM’s ultimate aim, these operational data stores may become the foundational building blocks enterprises will use to build a data center capable of taking on cognitive workloads. These ever-advancing workloads in advanced analytics, machine learning and AI will require the enterprise to seamlessly tap into data already housed on premises. Soon expect IBM to bring new offerings to market through an entire family of hyperconverged systems that will be designed to simply and easily deploy and scale a cognitive cloud infrastructure environment.

Currently, IBM offers two systems: the IBM CS821 and IBM CS822. These servers are the industry’s first hyperconverged solutions that marry Nutanix’s one-click software simplicity and scalability with the proven performance of the IBM POWER architecture, which is designed specifically for data-intensive workloads. The IBM CS822 (the larger of the two offerings) sports 22 POWER8 processor cores. That’s 176 compute threads, with up to 512 GB of memory and 15.36 TB of flash storage in a compact server that meshes seamlessly with simple Nutanix Prism management.

This server runs Nutanix Acropolis with AHV and little endian Linux. If IBM honors its stated pricing policy promise, the cost should be competitive on the total cost of acquisition for comparable offerings on x86. DancingDinosaur is not a lawyer (to his mother’s disappointment), but it looks like there is considerable wiggle room in this promise. IBM Hyperconverged-Nutanix Systems will be released for general availability in Q3 2017. Specific timelines, models, and supported server configurations will be announced at the time of availability.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at and here.


IBM Resurrects Moore’s Law

June 23, 2017

Guess Moore’s Law ain’t as dead as we were led to believe. On Jun 5 IBM and Research Alliance partners GLOBALFOUNDRIES and Samsung, along with equipment suppliers announced the development of an industry-first process to build silicon nano sheet transistors that will enable 5nm chips. Previously, IBM announced a 7nm process using a silicon germanium (SiGe) alloy.

As DancingDinosaur wrote in early Oct. 2015, the last z System that conformed to the expectations of Moore’s Law was the zEC12, introduced Aug 2012. IBM could boast then it had the fastest commercial processor available.  The subsequent z13 didn’t match it in processor speed.  The z13 chip runs a 22 nm core at 5 GHz, one-half a GHz slower than the zEC12, which ran its 32nm core at 5.5 GHz. IBM compensated for the slower chip speed by adding more processors throughout the system to boost I/O and other functions and optimizing the box every way possible.

5nm silicon nano-sheet transistors delivers 40% performance gain

By 2015, the z13 delivered about a 10 percent performance bump per core thanks to the latest tweaks in the core design, such as better branch prediction and better pipelining. But even at one-half Ghz slower, the z13 was the first system to process 2.5 billion transactions a day.  Even more importantly for enterprise data centers, z13 transactions are persistent, protected, and auditable from end-to-end, adding assurance as mobile transactions grow to an estimated 40 trillion mobile transactions per day by 2025. The z13 also received and continues to receive praise for its industry leading security ratings as well as its scalability and flexibility.

Just recently Hitachi announced a partnership with IBM to develop a version of the z13 to run its own operating system, VOS3. The resulting z13 will run the next generation of Hitachi’s AP series.

But IBM isn’t back in pursuit of Moore’s Law just to deliver faster traditional mainframe workloads. Rather, the company is being driven by its strategic initiatives, mainly cognitive computing. As IBM explained in the announcement: The resulting increase in performance will help accelerate cognitive computing, the Internet of Things (IoT), and other data-intensive applications delivered in the cloud. The power savings could also mean that the batteries in smartphones and other mobile products could last two to three times longer than today’s devices, before needing to be charged.

Scientists working as part of the IBM-led Research Alliance at the SUNY Polytechnic Institute Colleges of Nanoscale Science and Engineering’s NanoTech Complex in Albany, NY achieved the breakthrough by using stacks of silicon nanosheets as the device structure of the transistor instead of the standard FinFET architecture, which is the blueprint for the semiconductor industry up through 7nm node technology. “For business and society to meet the demands of cognitive and cloud computing in the coming years, advancement in semiconductor technology is essential,” said Arvind Krishna, senior vice president, Hybrid Cloud, and director, IBM Research in the announcement. “That’s why IBM aggressively pursues new and different architectures and materials that push the limits of this industry, and brings them to market in technologies like mainframes and our cognitive systems.”

Compared to the leading edge 10nm technology available in the market, according to IBM, a nanosheet-based 5nm technology can deliver 40 percent performance enhancement at fixed power, or 75 percent power savings at matched performance. This improvement enables a significant boost to meeting the future demands of artificial intelligence (AI) systems, virtual reality, and mobile devices.

These may not sound like the workloads you are running on your mainframe now, but systems with these chips are not going to be shipped in the next mainframe either. So, you have a couple of years. The IBM team expects to make progress toward commercializing 7nm in 2018. By the time they start shipping 5nm systems you might be desperate for a machine to run such workloads and others like them.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at and here.


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