Posts Tagged ‘Power Systems’

IBM Gets Serious About Open Data Science (ODS) with Anaconda

April 21, 2017

As IBM rapidly ramps up cognitive systems in various forms, its two remaining platforms, z System and POWER, get more and more interesting. This week IBM announced it was bringing the Anaconda Open Data Science (ODS) platform to its Cognitive Systems and PowerAI.

Anaconda, Courtesy Pinterest

Specifically, Anaconda will integrate with the PowerAI software distribution for machine learning (ML) and deep learning (DL). The goal: make it simple and fast to take advantage of Power performance and GPU optimization for data-intensive cognitive workloads.

“Anaconda on IBM Cognitive Systems empowers developers and data scientists to build and deploy deep learning applications that are ready to scale,” said Bob Picciano, senior vice president of IBM Cognitive Systems. Added Travis Oliphant, co-founder and chief data scientist, Continuum Analytics, which introduced the Anaconda platform: “By optimizing Anaconda on Power, developers will also gain access to the libraries in the PowerAI Platform for exploration and deployment in Anaconda Enterprise.”

With more than 16 million downloads to date, Anaconda has emerged as the Open Data Science platform leader. It is empowering leading businesses across industries worldwide with tools to identify patterns in data, uncover key insights, and transform basic data into the intelligence required to solve the world’s most challenging problems.

As one of the fastest growing fields of AI, DL makes it possible to process enormous datasets with millions or even billions of elements and extract useful predictive models. DL is transforming the businesses of leading consumer Web and mobile application companies, and it is catching on with more traditional business.

IBM developed PowerAI to accelerate enterprise adoption of open-source ML and DL frameworks used to build cognitive applications. PowerAI promises to reduce the complexity and risk of deploying these open source frameworks for enterprises on the Power architecture and is tuned for high performance, according to IBM. With PowerAI, organizations also can realize the benefit of enterprise support on IBM Cognitive Systems HPC platforms used in the most demanding commercial, academic, and hyperscale environments

For POWER shops getting into Anaconda, which is based on Python, is straightforward. You need a Power8 with IBM GPU hardware or a Power8 combined with a Nvidia GPU, in effect a Minsky machine. It’s essentially a developer’s tool although ODS proponents see it more broadly, bridging the gap between traditional IT and lines of business, shifting traditional roles, and creating new roles. In short, they envision scientists, mathematicians, engineers, business people, and more getting involved in ODS.

The technology is designed to run on the user’s desktop but is packaged and priced as a cloud subscription with a base package of 20 users. User licenses range from $500 per year to $30,000 per year depending on which bells and whistles you include. The number of options is pretty extensive.

According to IBM, this started with PowerAI to accelerate enterprise adoption of open-source ML/DL learning frameworks used to build cognitive applications. Overall, the open Anaconda platform brings capabilities for large-scale data processing, predictive analytics, and scientific computing to simplify package management and deployment. Developers using open source ML/DL components can use Power as the deployment platform and take advantage of Power optimization and GPU differentiation for NVIDIA.

Not to be left out, IBM noted growing support for the OpenPOWER Foundation, which recently announced the OpenPOWER Machine Learning Work Group (OPMLWG). The new OPMLWG includes members like Google, NVIDIA and Mellanox to provide a forum for collaboration that will help define frameworks for the productive development and deployment of ML solutions using OpenPOWER ecosystem technology. The foundation has also surpassed 300-members, with new participants such as Kinetica, Red Hat, and Toshiba. For traditional enterprise data centers, the future increasingly is pointing toward cognitive in one form or another.

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 technologywriter.com and here.

 

IBM Changes the Economics of Cloud Storage

March 31, 2017

Storage tiering used to be simple: active data went to your best high performance storage, inactive data went to low cost archival storage, and cloud storage filled in for one or whatever else was needed. Unfortunately, today’s emphasis on continuous data analytics, near real-time predictive analytics, and now cognitive has complicated this picture and the corresponding economics of storage.

In response, last week IBM unveiled new additions to the IBM Cloud Object Storage family. The company is offering clients new choices for archival data and a new pricing model to more easily apply intelligence to unpredictable data patterns using analytics and cognitive tools.

Analytics drive new IBM cloud storage pricing

By now, line of business (LOB) managers, having been exhorted to leverage big data and analytics for years, are listening. More recently, the analytics drumbeat has expanded to include not just big data but sexy IoT, predictive analytics, machine learning, and finally cognitive science. The idea of keeping data around for a few months and parking it in a long term archive to never be looked at again until it is finally deleted permanently just isn’t happening as it was supposed to (if it ever did). The failure to permanently remove expired data can become costly from a storage standpoint as well as risky from an e-discovery standpoint.

IBM puts it this way: Businesses typically have to manage across three types of data workloads: “hot” for data that’s frequently accessed and used; “cool” for data that’s infrequently accessed and used; and “cold” for archival data. Cold storage is often defined as cheaper but slower. For example, if a business uses cold storage, it typically has to wait to retrieve and access that data, limiting the ability to rapidly derive analytical or cognitive insights. As a result, there is a tendency to store data in more expensive hot storage.

IBM’s new cloud storage offering, IBM Cloud Object Storage Flex (Flex), uses a “pay as you use” model of storage tiers potentially lowering the price by 53 percent compared to AWS S3 IA1 and 75 percent compared to Azure GRS Cool Tier.2 (See footnotes at the bottom of the IBM press release linked to above. However IBM is not publishing the actual Flex storage prices.) Flex, IBM’s new cloud storage service, promises simplified pricing for clients whose data usage patterns are difficult to predict. Flex promises organizations will benefit from the cost savings of cold storage for rarely accessed data, while maintaining high accessibility to all data.

Of course, you could just lower the cost of storage by permanently removing unneeded data.  Simply insist that the data owners specify an expiration date when you set up the storage initially. When the date arrives in 5, 10, 15 years automatically delete the data. At least that’s how I was taught eons ago. Of course storage costs orders of magnitude less now although storage volumes are orders of magnitude greater and near real-time analytics weren’t in the picture.

Without the actual rates for the different storage tiers you cannot determine how much Storage Flex may save you.  What it will do, however, is make it more convenient to perform analytics on archived data you might otherwise not bother with.  Expect this issue to come up increasingly as IoT ramps up and you are handling more data that doesn’t need hot storage beyond the first few minutes of its arrival.

Finally, the IBM Cloud Object Storage Cold Vault (Cold Vault) service gives clients access to cold storage data on the IBM Cloud and is intended to lead the category for cold data recovery times among its major competitors. Cold Vault joins its existing Standard and Vault tiers to complete a range of IBM cloud storage tiers that are available with expanded expertise and methods via Bluemix and through the IBM Bluemix Garages.

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 technologywriter.com and here.

 

Open POWER-Open Compute-POWER9 at Open Compute Summit

March 16, 2017

Bryan Talik, President, OpenPOWER Foundation provides a detailed rundown on the action at the Open Compute  Summit held last week in Santa Clara. After weeks of writing about Cognitive, Machine Learning, Blockchain, and even quantum computing, it is a nice shift to conventional computing platforms that should still be viewed as strategic initiatives.

The OpenPOWER, Open Compute gospel was filling the air in Santa Clara.  As reported, Andy Walsh, Xilinx Director of Strategic Market Development and OpenPOWER Foundation Board member explained, “We very much support open standards and the broad innovation they foster. Open Compute and OpenPOWER are catalysts in enabling new data center capabilities in computing, storage, and networking.”

Added Adam Smith, CEO of Alpha Data:  “Open standards and communities lead to rapid innovation…We are proud to support the latest advances of OpenPOWER accelerator technology featuring Xilinx FPGAs.”

John Zannos, Canonical OpenPOWER Board Chair chimed in: For 2017, the OpenPOWER Board approved four areas of focus that include machine learning/AI, database and analytics, cloud applications and containers. The strategy for 2017 also includes plans to extend OpenPOWER’s reach worldwide and promote technical innovations at various academic labs and in industry. Finally, the group plans to open additional application-oriented workgroups to further technical solutions that benefits specific application areas.

Not surprisingly, some members even see collaboration as the key to satisfying the performance demands that the computing market craves. “The computing industry is at an inflection point between conventional processing and specialized processing,” according to Aaron Sullivan, distinguished engineer at Rackspace. “

To satisfy this shift, Rackspace and Google announced an OCP-OpenPOWER server platform last year, codenamed Zaius and Barreleye G2.  It is based on POWER9. At the OCP Summit, both companies put on a public display of the two products.

This server platform promises to improve the performance, bandwidth, and power consumption demands for emerging applications that leverage machine learning, cognitive systems, real-time analytics and big data platforms. The OCP players plan to continue their work alongside Google, OpenPOWER, OpenCAPI, and other Zaius project members.

Andy Walsh, Xilinx Director of Strategic Market Development and OpenPOWER Foundation Board member explains: “We very much support open standards and the broad innovation they foster. Open Compute and OpenPOWER are catalysts in enabling new data center capabilities in computing, storage, and networking.”

This Zaius and Barreleye G@ server platforms promise to advance the performance, bandwidth and power consumption demands for emerging applications that leverage the latest advanced technologies. These latest technologies are none other than the strategic imperatives–cognitive, machine learning, real-time analytics–IBM has been repeating like a mantra for months.

Open Compute Projects also were displayed at the Summit. Specifically, as reported: Google and Rackspace, published the Zaius specification to Open Compute in October 2016, and had engineers to explain the specification process and to give attendees a starting point for their own server design.

Other Open Compute members, reportedly, also were there. Inventec showed a POWER9 OpenPOWER server based on the Zaius server specification. Mellanox showcased ConnectX-5, its next generation networking adaptor that features 100Gb/s Infiniband and Ethernet. This adaptor supports PCIe Gen4 and CAPI2.0, providing a higher performance and a coherent connection to the POWER9 processor vs. PCIe Gen3.

Others, reported by Talik, included Wistron and E4 Computing, which showcased their newly announced OCP-form factor POWER8 server. Featuring two POWER8 processors, four NVIDIA Tesla P100 GPUs with the NVLink interconnect, and liquid cooling, the new platform represents an ideal OCP-compliant HPC system.

Talik also reported IBM, Xilinx, and Alpha Data showed their line ups of several FPGA adaptors designed for both POWER8 and POWER9. Featuring PCIe Gen3, CAPI1.0 for POWER8 and PCIe Gen4, CAPI2.0 and 25G/s CAPI3.0 for POWER9 these new FPGAs bring acceleration to a whole new level. OpenPOWER member engineers were on-hand to provide information regarding the CAPI SNAP developer and programming framework as well as OpenCAPI.

Not to be left out, Talik reported that IBM showcased products it previously tested and demonstrated: POWER8-based OCP and OpenPOWER Barreleye servers running IBM’s Spectrum Scale software, a full-featured global parallel file system with roots in HPC and now widely adopted in commercial enterprises across all industries for data management at petabyte scale.  Guess compute platform isn’t quite the dirty phrase IBM has been implying for months.

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 technologywriter.com and here.

 

IBM Introduces First Universal Commercial Quantum Computers

March 9, 2017

A few years ago DancingDinosaur first encountered the possibility of quantum computing. It was presented as a real but distant possibility. This is not something I need to consider I thought at the time.  By the time it is available commercially I will be long retired and probably six feet under. Well, I was wrong.

This week IBM unveiled its IBM Q quantum systems. IBM Q will be leading Watson and blockchain to deliver the most advanced set of services on the IBM Cloud platform. There are organizations using it now, and DancingDinosaur continues to be living and working still.

IBM Quantum Computing scientists Hanhee Paik (left) and Sarah Sheldon (right) examine the hardware inside an open dilution fridge at the IBM Q Lab

As IBM explains: While technologies that currently run on classical (or conventional) computers, such as Watson, can help find patterns and insights buried in vast amounts of existing data, quantum computers will deliver solutions to multi-faceted problems where patterns cannot be seen because the data doesn’t exist and the possibilities that you need to explore are too enormous to ever be processed by conventional computers.

Just don’t retire your z or Power system in favor on an IBM Q yet. As IBM explained at a recent briefing on the quantum computing the IBM Q universal quantum computers will be able to do any type of problem that conventional computers do today. However, many of today’s workloads, like on-line transaction processing, data storage, and web serving will continue to run more efficiently on conventional systems. The most powerful quantum systems of the next decade will be a hybrid of quantum computers with conventional computers to control logic and operations on large amounts of data.

The most immediate use cases will involve molecular dynamics, drug design, and materials. The new quantum machine, for example, will allow the healthcare industry to design more effective drugs faster and at less cost and the chemical industry to develop new and improved materials.

Another familiar use case revolves around optimization in finance and manufacturing. The problem here comes down to computers struggling with optimization involving an exponential number of possibilities. Quantum systems, noted IBM, hold the promise of more accurately finding the most profitable investment portfolio in the financial industry, the most efficient use of resources in manufacturing, and optimal routes for logistics in the transportation and retail industries.

To refresh the basics of quantum computing.  The challenges invariably entail exponential scale. You start with 2 basic ideas; 1) the uncertainty principle, which states that attempting to observe a state in general disturbs it while obtaining only partial information about the state. Or 2) where two systems can exist in an entangled state, causing them to behave in ways that cannot be explained by supposing that each has some state of its own. No more zero or 1 only.

The basic unit of quantum computing is the qubit. Today IBM is making available a 5 qubit system, which is pretty small in the overall scheme of things. Large enough, however, to experiment and test some hypotheses; things start getting interesting at 20 qubits. An inflexion point, IBM researchers noted, occurs around 50 qubits. At 50-100 qubits people can begin to do some serious work.

This past week IBM announced three quantum computing advances: the release of a new API for the IBM Quantum Experience that enables developers and programmers to begin building interfaces between IBM’s existing 5 qubit cloud-based quantum computer and conventional computers, without needing a deep background in quantum physics. You can try the 5 qubit quantum system via IBM’s Quantum Experience on Bluemix here.

IBM also released an upgraded simulator on the IBM Quantum Experience that can model circuits with up to 20 qubits. In the first half of 2017, IBM plans to release a full SDK on the IBM Quantum Experience for users to build simple quantum applications and software programs. Only the publically available 5 qubit quantum system with a web-based graphical user interface now; soon to be upgraded to more qubits.

 IBM Research Frontiers Institute allows participants to explore applications for quantum computing in a consortium dedicated to making IBM’s most ambitious research available to its members.

Finally, the IBM Q Early Access Systems allows the purchase of access to a dedicated quantum system hosted and managed by IBM. Initial system is 15+ qubits, with a fast roadmap promised to 50+ qubits.

“IBM has invested over decades to growing the field of quantum computing and we are committed to expanding access to quantum systems and their powerful capabilities for the science and business communities,” said Arvind Krishna, senior vice president of Hybrid Cloud and director for IBM Research. “We believe that quantum computing promises to be the next major technology that has the potential to drive a new era of innovation across industries.”

Are you ready for quantum computing? Try it today on IBM’s Quantum Experience through Bluemix. Let me know how it works for you.

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 technologywriter.com and here.

IBM Launches New IoT Collaborative Initiative

February 23, 2017

Collaboration partners can pull hundreds of millions of dollars in new revenue from IoT, according to IBM’s recent IoT announcement. Having reached what it describes as a tipping point with IoT innovation the company now boasts of having over 6,000 clients and partners around the world, many of whom are now wanting to join in its new global Watson IoT center to co-innovate. Already Avnet, BNP Paribas, Capgemini, and Tech Mahindra will collocate development teams at the IBM Munich center to work on IoT collaborations.

new-ibm-watson-iot-center

IBM Opens New Global Center for Watson IoT

The IBM center also will act as an innovation space for the European IoT standards organization EEBus.  The plan, according to Harriet Green, General Manager, IBM Watson IoT, Cognitive Engagement and Education (pictured above left), calls for building a new global IoT innovation ecosystem that will explore how cognitive and IoT technologies will transform industries and our daily lives.

IoT and more recently cognitive are naturals for the z System, and POWER Systems have been the platform for natural language processing and cognitive since Watson won Jeopardy three years ago. With the latest enhancements IBM has brought to the z in the form of on-premises cognitive and machine learning the z should assume an important role as it gathers, stores, collects, and processes IoT data for cognitive analysis. DancingDinosaur first reported on this late in 2014 and again just last week. As IoT and cognitive workloads ramp up on z don’t be surprised to see monthly workload charges rise.

Late last year IBM announced that car maker BMW will collocate part of its research and development operations at IBM’s new Watson IoT center to help reimagine the driving experience. Now, IBM is announcing four more companies that have signed up to join its special industry “collaboratories” where clients and partners work together with 1,000 Munich-based IBM IoT experts to tap into the latest design thinking and push the boundaries of the possible with IoT.

Let’s look at the four newest participants starting with Avnet. According to IBM, an IT distributor and global IBM partner, Avnet will open a new joint IoT Lab within IBM’s Watson IoT HQ to develop, build, demonstrate and sell IoT solutions powered by IBM Watson. Working closely with IBM’s leading technologists and IoT experts, Avnet also plans to enhance its IoT technical expertise through hands-on training and on-the-job learning. Avnet’s team of IoT and analytics experts will also partner with IBM on joint business development opportunities across multiple industries including smart buildings, smart homes, industry, transportation, medical, and consumer.

As reported by BNP Paribas, Consorsbank, its retail digital bank in Germany, will partner with IBM´s new Watson IoT Center. The company will collocate a team of solution architects, developers and business development personnel at the Watson facility. Together with IBM’s experts, they will explore how IoT and cognitive technologies can drive transformation in the banking industry and help innovate new financial products and services, such as investment advice.

Similarly, global IT consulting and technology services provider Capgemini will collocate a team of cognitive IoT experts at the Watson center. Together they will help customers maximize the potential of Industry 4.0 and develop and take to market sector-specific cognitive IoT solutions. Capgemini plans a close link between its Munich Applied Innovation Exchange and IBM’s new Customer Experience zones to collaborate with clients in an interactive environment.

Finally, the Indian multinational provider of enterprise and communications IT and networking technology Tech Mahindra, is one of IBM’s Global System Integrators with over 3,000 specialists focused on IBM technology around the world. The company will locate a team of six developers and engineers within the Watson IoT HQ to help deliver on Tech Mahindra’s vision of generating substantial new revenue based on IBM’s Watson IoT platform. Tech Mahindra will use the center to co-create and showcase new solutions based on IBM’s Watson IoT platform for Industry 4.0 and Manufacturing, Precision Farming, Healthcare, Insurance and Banking, and automotive.

To facilitate connecting the z to IoT IBM offers a simple recipe. It requires 4 basic ingredients and 4 steps: Texas Instrument’s SensorTag, a Bluemix account, IBM z/OS Connect Enterprise Edition, and a back-end service like CICS.  Start by exposing an existing z Systems application as a RESTful AP. This is where the z/OS Connect Edition comes in.  Then enable your SensorTag device to Watson IoT Quick Start. From there connect the Cloud to your on-premises Hybrid Cloud.  Finally, enable the published IoT data to trigger a RESTful API. Sounds pretty straightforward but—full disclosure—Dancing Dinosaur has not tried it due to lacking the necessary pieces. If you try it, please tell DancingDinosaur how it works (info@radding.net). Good luck.

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 technologywriter.com and here.

 

IBM Cheers Beating Estimates But Losing Streak Continues

January 26, 2017

It has been 19 quarters since IBM reported positive revenue in its quarterly reports but the noises coming out of IBM with the latest 4Q16 and full year 2016 financials are upbeat due to the company beating analyst consensus revenue estimates and its strategic initiatives are starting to generate serious revenue.   Although systems revenues were down again (12%) the accountants at least had something positive to say about the z: “gross profit margins improved driven by z Systems performance.”

ezsource-dashboard

EZSource: Dashboard visualizes changes to mainframe code

IBM doesn’t detail which z models were contributing but you can guess they would be the LinuxONE models (Emperor and Rock Hopper) and the z13. DancingDinosaur expects z performance to improve significantly in 2017 when a new z, which had been heavily hinted in the 3Q2016 results reported here, is expected to ship.

With it latest financials IBM is outright crowing about its strategic initiatives: Fourth-quarter cloud revenues increased 33 percent.  The annual exit run rate for cloud as-a-service revenue increased to $8.6 billion from $5.3 billion at year-end 2015.  Revenues from analytics increased 9 percent.  Revenues from mobile increased 16 percent and revenues from security increased 7 percent.

For the full year, revenues from strategic imperatives increased 13 percent.  Cloud revenues increased 35 percent to $13.7 billion.  The annual exit run rate for cloud as-a-service revenue increased 61 percent year to year.  Revenues from analytics increased 9 percent.  Revenues from mobile increased 34 percent and from security increased 13 percent.

Of course, cognitive computing is IBM’s strategic imperative darling for the moment, followed by blockchain. Cognitive, for which IBM appears to use an expansive definition, is primarily a cloud play as far as IBM is concerned.  There is, however, a specific role for the z, which DancingDinosaur will get into in a later post. Blockchain, on the other hand, should be a natural z play.  It is, essentially, extremely secure OLTP on steroids.  As blockchain scales up it is a natural to drive z workloads.

As far as IBM’s financials go the strategic imperatives indeed are doing well. Other business units, however, continue to struggle.  For instance:

  • Global Business Services (includes consulting, global process services and application management) — revenues of $4.1 billion, down 4.1 percent.
  • Systems (includes systems hardware and operating systems software), remember, this is where z and Power platforms reside — revenues of $2.5 billion, down 12.5 percent. But as noted above, gross profit margins improved, driven by z Systems performance.
  • Global Financing (includes financing and used equipment sales) — revenues of $447 million, down 1.5 percent.

A couple of decades ago, when this blogger first started covering IBM and the mainframe as a freelancer writing for any technology publication that would pay real money IBM was struggling (if $100 billion behemoths can be thought to be struggling). The buzz among the financial analysts who followed the company was that IBM should be broken up into its parts and sold off.  IBM didn’t take that advice, at least not exactly, but it did begin a rebound that included laying off tons of people and the sale of some assets. Since then it invested heavily in things like Linux on z and open systems.

In December IBM SVP Tom Rosamilia talked about new investments in z/OS and z software like DB2 and CICS and IMS, and the best your blogger can tell he is still there. (Rumors suggest Rosamilia is angling for Rometty’s job in two years.)  If the new z does actually arrive in 2017 and key z software is refreshed then z shops can rest easy, at least for another few quarters.  But whatever happens, you can follow it here.

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 technologywriter.com and here.

 

IBM Introduces New DS8880 All-Flash Arrays

January 13, 2017

Yesterday IBM introduced three new members of the DS8000 line, each an all-flash product.  The new, all-flash storage products are designed for midrange and large enterprises, where high availability, continuous up-time, and performance are critical.

ibm-flash-ds8888-mainframe-ficon

IBM envisions these boxes for more than the z’s core OLTP workloads. According to the company, they are built to provide the speed and reliability needed for workloads ranging from enterprise resource planning (ERP) and financial transactions to cognitive applications like machine learning and natural language processing. The solutions are designed to support cognitive workloads, which can be used to uncover trends and patterns that help improve decision-making, customer service, and ROI. ERP and financial transactions certainly constitute conventional OLTP but the cognitive workloads are more analytical and predictive.

The three products:

  • IBM DS8884 F
  • IBM DS8886 F
  • IBM DS8888 F

The F signifies all-flash.  Each was designed with High-Performance Flash Enclosures Gen2. IBM did not just slap flash into existing hard drive enclosures.  Rather, it reports undertaking a complete redesign of the flash-to-z interaction. As IBM puts it: through deep integration between the flash and the z, IBM has embedded software that facilitates data protection, remote replication, and optimization for midrange and large enterprises. The resulting new microcode is ideal for cognitive workloads on z and Power Systems requiring the highest availability and system reliability possible. IBM promises that the boxes will deliver superior performance and uncompromised availability for business-critical workloads. In short, fast enough to catch bad guys before they leave the cash register or teller window. Specifically:

  • The IBM DS8884 F—labelled as the business class offering–boasts the lowest entry cost for midrange enterprises (prices starting at $90,000 USD). It runs an IBM Power Systems S822, which is a 6-core POWER8 processor per S822 with 256 GB Cache (DRAM), 32 Fibre channel/FICON ports, and 6.4 – 154 TB of flash capacity.
  • The IBM DS8886 F—the enterprise class offering for large organizations seeking high performance– sports a 24-core POWER8 processor per S824. It offers 2 TB Cache (DRAM), 128 Fibre channel/FICON ports, and 6.4 – 614.4 TB of flash capacity. That’s over one-half petabyte of high performance flash storage.
  • The IBM DS8888 F—labelled an analytics class offering—promises the highest performance for faster insights. It runs on the IBM Power Systems E850 with a 48-core POWER8 processor per E850. It also comes with 2 TB Cache (DRAM), 128 Fibre channel/FICON ports, and 6.4TB – 1.22 PB of flash capacity. Guess crossing the petabyte level qualifies it as an analytics and cognitive device along with the bigger processor complex

As IBM emphasized in the initial briefing, it engineered these storage devices to surpass the typical big flash storage box. For starters, IBM bypassed the device adapter to connect the z directly to the high performance storage controller. IBM’s goal was to reduce latency and optimize all-flash storage, not just navigate a simple replacement by swapping new flash for ordinary flash or, banish the thought, HDD.

“We optimized the data path,” explained Jeff Barber IBM systems VP for HE Storage BLE (DS8, DP&R and SAN). To that end, IBM switched from a 1u to a 4u enclosure, runs on shared-nothing clusters, and boosted throughput performance. The resulting storage, he added, “does database better than anyone; we can run real-time analytics.”  The typical analytics system—a shared system running Hadoop, won’t even come close to these systems, he added. With the DS8888, you can deploy a real-time cognitive cluster with minimal latency flash.

DancingDinosaur always appreciates hearing from actual users. Working through a network of offices, supported by a team of over 850 people, Health Insurance Institute of Slovenia (Zavod za zdravstveno zavarovanje Slovenije), provides health insurance to approximately two million customers. In order to successfully manage its new customer-facing applications (such as electronic ordering processing and electronic receipts) its storage system required additional capacity and performance. After completing research on solutions capable of managing these applications –which included both Hitachi and EMC –the organization deployed the IBM DS8886 along with DB2 for z/OS data server software to provide an integrated data backup and restore system. (Full disclosure: DancingDinosaur has not verified this customer story.)

“As long-time users of IBM storage infrastructure and mainframes, our upgrade to the IBM DS8000 with IBM business partner Comparex was an easy choice. Since then, its high performance and reliability have led us to continually deploy newer DS8000 models as new features and functions have provided us new opportunities,” said Bojan Fele, CIO of Health Insurance Institute of Slovenia. “Our DS8000 implementation has improved our reporting capabilities by reducing time to actionable insights. Furthermore, it has increased employee productivity, ensuring we can better serve our clients.”

For full details and specs on these products, click here

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 technologywriter.com and here.

 

z System-Power-Storage Still Live at IBM

January 5, 2017

A mid-December briefing by Tom Rosamilia, SVP, IBM Systems, reassured some that IBM wasn’t putting its systems and platforms on the backburner after racking up financial quarterly losses for years. Expect new IBM systems in 2017. A few days later IBM announced that Japan-based APLUS Co., Ltd., which operates credit card and settlement service businesses, selected IBM LinuxONE as its mission-critical system for credit card payment processing. Hooray!

linuxone-emperor-2

LinuxONE’s security and industry-leading performance will ensure APLUS achieves its operational objectives as online commerce heats up and companies rely on cloud applications to draw and retain customers. Especially in Japan, where online and mobile shopping has become increasingly popular, the use of credit cards has grown, with more than 66 percent of consumers choosing that method for conducting online transactions. And with 80 percent enterprise hybrid cloud adoption predicted by 2017, APLUS is well positioned to connect cloud transactions leveraging LinuxONE. Throw in IBM’s expansion of blockchain capabilities and the APLUS move looks even smarter.

With the growth of international visitors spending money, IBM notes, and the emergence of FinTech firms in Japan have led to a diversification of payment methods the local financial industry struggles to respond. APLUS, which issues well-known credit cards such as T Card Plus, plans to offer leading-edge financial services by merging groups to achieve lean operations and improved productivity and efficiency. Choosing to update its credit card payment system with LinuxONE infrastructure, APLUS will benefit from an advanced IT environment to support its business growth by helping provide near-constant uptime. In addition to updating its server architecture, APLUS has deployed IBM storage to manage mission-critical data, the IBM DS8880 mainframe-attached storage that delivers integration with IBM z Systems and LinuxONE environments.

LinuxONE, however, was one part of the IBM Systems story Rosamilia set out to tell.  There also is the z13s, for encrypted hybrid clouds and the z/OS platform for Apache Spark data analytics and even more secure cloud services via blockchain on LinuxONE, by way of Bluemix or on premises.

z/OS will get attention in 2017 too. “z/OS is the best damn OLTP system in the world,” declared Rosamilia. He went on to imply that enhancements and upgrades to key z systems were coming in 2017, especially CICS, IMS, and a new release of DB2. Watch for new announcements coming soon as IBM tries to push z platform performance and capacity for z/OS and OLTP.

Rosamilia also talked up the POWER story. Specifically, Google and Rackspace have been developing OpenPOWER systems for the Open Compute Project.  New POWER LC servers running POWER8 and the NVIDIA NVLink accelerator, more innovations through the OpenCAPI Consortium, and the team of IBM and Nvidia to deliver PowerAI, part of IBM’s cognitive efforts.

As much as Rosamilia may have wanted to talk about platforms and systems IBM continues to avoid using terms like systems and platforms. So Rosamilia’s real intent was to discuss z and Power in conjunction with IBM’s strategic initiatives.  Remember these: cloud, big data, mobile, analytics. Lately, it seems, those initiatives have been culled down to cloud, hybrid cloud, and cognitive systems.

IBM’s current message is that IT innovation no longer comes from just the processor. Instead, it comes through scaling performance by workload and sustaining leadership through ecosystem partnerships.  We’ve already seen some of the fruits of that innovation through the Power community. Would be nice to see some of that coming to the z too, maybe through the open mainframe project. But that isn’t about z/0S. Any boost in CICS, DB2, and IMS will have to come from the core z team. The open mainframe project is about Linux on z.

The first glimpse we had of this came last spring in a system dubbed Minsky, which was described back then by commentator Timothy Prickett Morgan. With the Minsky machine, IBM is using NVLink ports on the updated Power8 CPU, which was shown in April at the OpenPower Summit and is making its debut in systems actually manufactured by ODM Wistron and rebadged, sold, and supported by IBM. The NVLink ports are bundled up in a quad to deliver 80 GB/sec bandwidth between a pair of GPUs and between each GPU and the updated Power8 CPU.

The IBM version, Morgan describes, aims to create a very brawny node with very tight coupling of GPUs and CPUs so they can better share memory, have fewer overall GPUs, and more bandwidth between the compute elements. IBM is aiming Minsky at HPC workloads, according to Morgan, but there is no reason it cannot be used for deep learning or even accelerated databases.

Is this where today’s z data center managers want to go?  No one is likely to spurn more performance, especially if it is accompanied with a price/performance improvement.  Whether rank-and-file z data centers are queueing up for AI or cognitive workloads will have to be seen. The sheer volume and scale of expected activity, however, will require some form of automated intelligent assist.

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 technologywriter.com and here

IBM Power System S822LC for HPC Beat Sort Record by 3.3x

November 17, 2016

The new IBM Power System S822LC for High Performance Computing servers set a new benchmark for sorting by taking less than 99 seconds (98.8 seconds) to finish sorting 100 terabytes of data in the Indy GraySort category, improving on last year’s best result, 329 seconds, by a factor of 3.3. The win proved a victory not only for the S822LC but for the entire OpenPOWER community. The team of Tencent, IBM, and Mellanox has been named the Winner of the Sort Benchmark annual global computing competition for 2016.

rack-of-new-ibm-power-systems-s822lc-for-high-performance-computing-servers-1Power System S822LC for HPC

Specifically, the machine, an IBM Power S822LC for High Performance Computing (HPC), features NVIDIA NVLink technology optimized for the Power architecture and NVIDIA’s latest GPU technology. The new system supports emerging computing methods of artificial intelligence, particularly deep learning. The combination, newly dubbed IBM PowerAI, provides a continued path for Watson, IBM’s cognitive solutions platform, to extend its artificial intelligence expertise in the enterprise by using several deep learning methods to train Watson.

Actually Tencent Cloud Data Intelligence (the distributed computing platform of Tencent Cloud) won each category in both the GraySort and MinuteSort benchmarks, establishing four new world records with its performance, outperforming the 2015 best speeds by 2-5x. Said Zeus Jiang, Vice President of Tencent Cloud and General Manager of Tencent’s Data Platform Department: “In the future, the ability to manage big data will be the foundation of successful Internet businesses.”

To get this level of performance Tencent runs 512 IBM OpenPOWER LC servers and Mellanox’100Gb interconnect technology, improving the performance of Tencent Cloud big data products with the infrastructure. Online prices for the S822LC starts at about $9600 for 2-socket, 2U with up to 20 cores (2.9-3.3Ghz), 1 TB memory (32 DIMMs), 230 GB/sec sustained memory bandwidth, 2x SFF (HDD/SSD), 2 TB storage, 5 PCIe slots, 4 CAPI enabled, up to 2 NVidia K80 GPU. Be sure to shop for volume discounts.

The 2016 Sort Benchmark Results below (apologies in advance if this table breaks apart)

Sort Benchmark Competition 20 Records (Tencent Cloud ) 2015 World Records 2016 Improvement
Daytona GraySort 44.8 TB/min 15.9 TB/min 2.8X greater performance
Indy GraySort 60.7 TB/min 18.2 TB/min 3.3X greater performance
Daytona MinuteSort 37 TB/min 7.7 TB/min 4.8X greater performance
Indy MinuteSort 55 TB/min 11 TB/min 5X greater performance

Pretty impressive, huh. As IBM explains it: Tencent Cloud used 512 IBM OpenPOWER servers and Mellanox’100Gb interconnect technology, improving the performance of Tencent Cloud big data products with the infrastructure. Then Tom Rosamilia, IBM Senior VP weighed in: “Industry leaders like Tencent are helping IBM and our OpenPOWER partners push performance boundaries for a cognitive era defined by big data and advanced analytics.” The computing record achieved by Tencent Cloud on OpenPOWER turned out to be an important milestone for the OpenPOWER Foundation too.

Added Amir Prescher, Sr. Vice President, Business Development, at Mellanox Technologies: “Real-time-analytics and big data environments are extremely demanding, and the network is critical in linking together the extra high performance of IBM POWER-based servers and Tencent Cloud’s massive amounts of data,” In effect, Tencent Cloud developed an optimized hardware/software platform to achieve new computing records while demonstrating that Mellanox’s 100Gb/s Ethernet technology can deliver total infrastructure efficiency and improve application performance, which should make it a favorite for big data applications.

Behind all of this was the new IBM Power System S822LC for High Performance Computing servers. Currently the servers feature a new IBM POWER8 chip designed for demanding workloads including artificial intelligence, deep learning and advanced analytics.  However, a new POWER9 chips has already been previewed and is expected next year.  Whatever the S822LC can do running POWER8 just imagine how much more it will do running POWER9, which IBM describes as a premier acceleration platform. DancingDinosaur covered POWER9 in early Sept. here.

To capitalize on the hardware, IBM is making a new deep learning software toolkit available, PowerAI, which runs on the recently announced IBM Power S822LC server built for artificial intelligence that features NVIDIA NVLink interconnect technology optimized for IBM’s Power architecture. The hardware-software combination provides more than 2X performance over comparable servers with 4 GPUs running AlexNet with Caffe. The same 4-GPU Power-based configuration running AlexNet with BVLC Caffe can also outperform 8 M40 GPU-based x86 configurations, making it the world’s fastest commercially available enterprise systems platform on two versions of a key deep learning framework.

Deep learning is a fast growing, machine learning method that extracts information by crunching through millions of pieces of data to detect and ranks the most important aspects of the data. Publicly supported among leading consumer web and mobile application companies, deep learning is quickly being adopted by more traditional enterprises across a wide range of industry sectors; in banking to advance fraud detection through facial recognition; in automotive for self-driving automobiles; and in retail for fully automated call centers with computers that can better understand speech and answer questions. Is your data center ready for deep learning?

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 technologywriter.com and here.

 

 

Can SDS and Flash Resurrect IBM Storage?

November 4, 2016

As part of IBM’s ongoing string of quarterly losses storage has consistently contributed to the red ink, but the company is betting on cloud storage, all-flash strategy, and software defined storage (SDS) to turn things around. Any turn-around, however, is closely tied to the success of IBM’s strategic imperatives, which have emerged as bright spots amid the continuing quarterly losses; especially cloud, analytics, and cognitive computing.

climate-data-requires-fast-access-1

Climate study needs large amounts of fast data access

As a result, IBM needs to respond to two challenges created by its customers: 1) changes like the increased adoption of cloud, analytics, and most recently cognitive computing and 2) the need by customers to reduce the cost of the IT infrastructure. The problem as IBM sees it is this: How do I simultaneously optimize the traditional application infrastructure and free up money to invest in a new generation application infrastructure, especially if I expect move forward into the cognitive era at some point? IBM’s answer is to invest in flash and SDS.

A few years ago DancingDinosaur was skeptical, for example, that flash deployment would lower storage costs except in situations where low cost IOPS was critical. Today between the falling cost of flash and new ways to deploy increasingly cheaper flash DancingDinosaur now believes Flash storage can save IT real money.

According to the Evaluator Group and cited by IBM, flash and hybrid cloud technologies are dramatically changing the way companies deploy storage and design applications. As new applications are created–often for mobile or distributed access–the ability to store data in the right place, on the right media, and with the right access capability will become even more important.

In response, companies are adding cloud to lower costs, flash to increase performance, and SDS to add flexibility. IBM is integrating these capabilities together with security and data management for faster return on investment.  Completing the IBM pitch, the company offers choice among on-premise storage, SDS, or storage as a cloud service.

In an announcement earlier this week IBM introduced six products:

  • IBM Spectrum Virtualize 7.8 with transparent cloud tiering
  • IBM Spectrum Scale 4.2.2 with cloud data sharing
  • IBM Spectrum Virtualize family flash enhancements
  • IBM Storwize family upgrades
  • IBM DS8880 High Performance Flash Enclosure Gen2
  • IBM DeepFlash Elastic Storage Server
  • VersaStack—a joint IBM-Cisco initiative

In short, these announcements address Hybrid Cloud enablement, as a standard feature for new and existing users of Spectrum Virtualize to enable data sharing to the cloud through Spectrum Scale, which can sync file and object data across on-premises and cloud storage to connect cloud native applications. Plus, more high density, highly scalable all-flash storage now sports a new high density expansion enclosure that includes new 7TB and 15TB flash drives.

IBM Storwize, too, is included, now able to grow up to 8x larger than previously without disruption. That means up to 32PB of flash storage in only four racks to meet the needs of fast-growing cloud workloads in space-constrained data centers. Similarly, IBM’s new DeepFlash Elastic Storage Server (ESS) offers up to 8x better performance than HDD-based solutions for big data and analytics workloads. Built with IBM Spectrum Scale ESS includes virtually unlimited scaling, enterprise security features, and unified file, object, and HDFS support.

The z can play in this party too. IBM’s DS8888 now delivers 2x better performance and 3x more efficient use of rack space for mission-critical applications such as credit card and banking transactions as well as airline reservations running on IBM’s z System or IBM Power Systems. DancingDinosaur first reported on the all flash z, the DS8888, when it was introduced last May.

Finally hybrid cloud enablement for existing and new on-premises storage enhancements through IBM Spectrum Virtualize, which brings hybrid cloud capabilities for block storage to the Storwize family, FlashSystem V9000, SVC, and VersaStack, the IBM-Cisco collaboration.

Behind every SDS deployment lies some actual physical storage of some type. Many opt for generic, low cost white box storage to save money.  As part of IBM’s latest SDS offerings you can choose among any of nearly 400 storage systems from IBM and others. Doubt any of those others are white box products but at least they give you some non-IBM options to potentially lower your storage costs.

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

 


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