Posts Tagged ‘POWER8’

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 technologywriter.com and here.

 

IBM Power and z Platforms Show Renewed Excitement

June 30, 2017

Granted, 20 consecutive quarters of posting negative revenue numbers is enough to get even the most diehard mainframe bigot down. If you ran your life like that your house and your car would have been seized by the bank months ago.

Toward the end of June, however, both z and Power had some good news. First,  a week ago IBM announced that corporate enterprise users ranked the IBM z  enterprise servers as the most reliable hardware platform available on the market today. In its enterprise server category the survey also found that IBM Power Systems achieved the highest levels of reliability and uptime when compared with 14 server hardware options and 11 server hardware virtualization platforms.

IBM links 2 IBM POWER8 with NVIDIA NVLink with 4 NVIDIA Tesla P100 accelerators

The results were compiled and reported by the ITIC 2017 Global Server Hardware and Server OS Reliability survey, which polled 750 organizations worldwide during April/May 2017. Also among the survey finding:

  • IBM z Systems Enterprise mainframe class systems, had zero percent incidents of more than four hours of per server/per annum downtime of any hardware platform. Specifically, IBM z Systems mainframe class servers exhibit true mainframe fault tolerance experiencing just 0.96 minutes of minutes of unplanned per server, per annual downtime. That equates to 8 seconds per month of “blink and you miss it,” or 2 seconds of unplanned weekly downtime. This is an improvement over the 1.12 minutes of per server/per annum downtime the z Systems servers recorded in ITIC’s 2016 – 2017 Reliability poll nine months ago.
  • IBM Power Systems has the least amount of unplanned downtime, with 2.5 minutes per server/per year of any mainstream Linux server platforms.
  • IBM and the Linux operating system distributions were either first or second in every reliability category, including virtualization and security.

The survey also highlighted market reliability trends. For nearly all companies surveyed, having four nines (99.99%) of availability, equating to less than one hour of system downtime per year was a key factor in its decision.

Then consider the increasing costs of downtime. Nearly all survey respondents claimed that one hour of downtime costs them more than $150k, with one-third estimating that the same will cost their business up to $400k.

With so much activity going on 24×7, for an increasing number of businesses, 4 nines of availability is no longer sufficient.  These businesses are adopting carrier levels of availability; 5 nines or 6 nines (or 99.999 to 99.9999 percent) availability, which translates to downtime per year of 30 seconds (6 nines) or 5 minutes (5 nines) of downtime per year.

According to ITIC’s 2016 report: IBM’s z Enterprise mainframe customers reported the least amount of unplanned downtime and the highest percentage of five nines (99.999%) uptime of any server hardware platform.

Just this week, IBM announced that according to results from International Data Corporation (IDC) Worldwide Quarterly Server Tracker® (June, 2017) IBM exceeded market growth by 3x compared with the total Linux server market, which grew at 6 percent. The improved performance are the result of success across IBM Power Systems including IBM’s OpenPOWER LC servers and IBM Power Systems running SAP HANA as well as the OpenPOWER-Ready servers developed through the OpenPOWER Foundation.

As IBM explains it: Power Systems market share growth is underpinned by solutions that handle fast growing applications, like the deep learning capabilities within the POWER8 architecture. In addition these are systems that expand IBM’s Linux server portfolio, which have been co-developed with fellow members of the OpenPOWER Foundation

Now all that’s needed is IBM’s sales and marketing teams to translate this into revenue. Between that and the new systems IBM has been hinting at for the past year maybe the consecutive quarterly losses might come to an end this year.

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 Shows Off POWER and NVIDIA GPU Setting High Performance Record 

May 4, 2017

The record achievement used 60 Power processors and 120 GPU accelerators to shatter the previous supercomputer record, which used over a 700,000 processors. The results point to how dramatically the capabilities of high performance computing (HPC) has increase while the cost of HPC systems has declined. Or put another way: the effort demonstrates the ability of NVIDIA GPUs to simulate one billion cell models in a fraction of the time, while delivering 10x the performance and efficiency.

Courtesy of IBM: Takes a lot of processing to take you into a tornado

In short, the combined success of IBM and NVIDIA puts the power of cognitive computing within the reach of mainstream enterprise data centers. Specifically the project performed reservoir modeling to predict the flow of oil, water, and natural gas in the subsurface of the earth before they attempt to extract the maximum oil in the most efficient way. The effort, in this case, involved a billion-cell simulation, which took just 92 minutes using 30 for HPC servers equipped with 60 POWER processors and 120 NVIDIA Tesla P100 GPU accelerators.

“This calculation is a very salient demonstration of the computational capability and density of solution that GPUs offer. That speed lets reservoir engineers run more models and ‘what-if’ scenarios than previously,” according to Vincent Natoli, President of Stone Ridge Technology, as quoted in the IBM announcement. “By increasing compute performance and efficiency by more than an order of magnitude, we’re democratizing HPC for the reservoir simulation community,” he added.

“The milestone calculation illuminates the advantages of the IBM POWER architecture for data-intensive and cognitive workloads.” said Sumit Gupta, IBM Vice President, High Performance Computing, AI & Analytics in the IBM announcement. “By running Stone Ridge’s ECHELON on IBM Power Systems, users can achieve faster run-times using a fraction of the hardware.” Gupta continued. The previous record used more than 700,000 processors in a supercomputer installation that occupies nearly half a football field while Stone Ridge did this calculation on two racks of IBM Power Systems that could fit in the space of half a ping-pong table.”

This latest advance challenges perceived misconceptions that GPUs could not be efficient on complex application codes like reservoir simulation and are better suited to simple, more naturally parallel applications such as seismic imaging. The scale, speed, and efficiency of the reported result disprove this misconception. The milestone calculation with a relatively small server infrastructure enables small and medium-size oil and energy companies to take advantage of computer-based reservoir modeling and optimize production from their asset portfolio.

Billion cell simulations in the industry are rare in practice, but the calculation was accomplished to highlight the performance differences between new fully GPU-based codes like the ECHELON reservoir simulator and equivalent legacy CPU codes. ECHELON scales from the cluster to the workstation and while it can simulate a billion cells on 30 servers, it can also run smaller models on a single server or even on a single NVIDIA P100 board in a desktop workstation, the latter two use cases being more in the sweet spot for the energy industry, according to IBM.

As importantly, the company notes, this latest breakthrough showcases the ability of IBM Power Systems with NVIDIA GPUs to achieve similar performance leaps in other fields such as computational fluid dynamics, structural mechanics, climate modeling, and others that are widely used throughout the manufacturing and scientific community. By taking advantage of POWER and GPUs organizations can literally do more with less, which often is an executive’s impossible demand.

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 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.

 

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.

 

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

Revamped IBM Power Systems LC Takes on x86

September 9, 2016

To hear IBM, its revamped and refreshed Power Systems LC lineup will undermine x86 (Intel), HPE, Dell/EMC, and any other purveyor of x86-based systems. Backed by accelerators provided by OpenPower community members, IBM appears ready extend the x86 battle to on premises, in the cloud, and the hybrid cloud. It promises to deliver better performance at lower cost for all the hot workloads too: artificial intelligence, deep learning, high performance data analytics, and compute-heavy workloads.

ibm-power-systems-s821lc

Two POWER8 processors, 1U config, priced 30% less than an x86 server

Almost a year ago, Oct. 2015, DancingDinosaur covered IBM previous Power Systems LC announcement here. The LC designation stands for Linux Community, and the company is tapping accelerators and more from the OpenPower community, just as it did with its recent announcement of POWER9 expected in 2017, here.

The new Power LC systems feature a set of community delivered technologies IBM has dubbed POWERAccel, a family of I/O technologies designed to deliver composable system performance enabled by accelerators. For GPU acceleration the NVDIA NVLink delivers nearly 5x better integration between POWER processors and the NVIDIA GPUs.  For FPGA acceleration IBM tapped its own CAPI architecture to integrate accelerators that run natively as part of the application.

This week’s Power Systems LC announcement features three new machines:

  • S821LC (pictured above)—includes 2 POWER8 sockets in a 1U enclosure and intended for environments requiring dense computing.
  • S822LC—brings 2 POWER8 sockets for big data workloads and adds big data acceleration through CAPI and GPUs.
  • S822LC—intended for high performance computing, it incorporates the new POWER8 processor with the NVDIA NVLink to deliver 2.8x the bandwidth to GPU accelerators and up to 4 integrated NVIDIA Pascal GPUs.

POWER8 with NVLink delivers 2.8 x the bandwidth compared to a PCle data pipe. According to figures provided by IBM comparing the price-performance of the Power S822LC for HPC (20-core, 256 GB, 4x Pascal) with a Dell C4130 (20-core, 256 GB 4xK80) and measured by total queries per hour (gph) the Power System delivered 2.1x better price-performance.  The Power Systems server cost more ($66,612) vs. the Dell ($57,615) but the Power System delivered 444 qph vs. Dell’s 185 qph.

The story plays out similarly for big data workloads running MongoDB on the IBM Power S8221LC for big data (20-core, 128 GB) vs. an HP DL380 (20-core, 128 GB). Here the system cost (server, OS, MongoDB annual subscription) came to $24,870 for IBM Power and $29,915 for HP.  Power provided 40% more performance at a 31% lower hardware/maintenance cost.

When it comes to the cloud the new IBM Power Systems LC offerings get even more interesting from a buyer’s standpoint. IBM declared the cloud a strategic imperative about 2 years ago and needs to demonstrate adoption that can rival the current cloud leaders; AWS, Google, and Microsoft (Azure). To that end IBM has started to tack on free cloud usage.

For example, during the industry analyst launch briefing IBM declared: Modernize your Power infrastructure for the Cloud, get access to IBM Cloud for free and cut your current operating costs by 50%. Whether you’re talking on-premises cloud or hybrid infrastructure the freebies just come. The free built-in cloud deployment service options include:

  • Cloud Provisioning and Automation
  • Infrastructure as a Service
  • Cloud Capacity Pools across Data Centers
  • Hybrid Cloud with BlueMix
  • Automation for DevOps
  • Database as a Service

These cover both on-premises, where you can transform your traditional infrastructure with automation, self-service, and elastic consumption models or a hybrid infrastructure where you can securely extend to Public Cloud with rapid access to compute services and API integration. Other freebies include open source automation, installation and configuration recipes, cross data center inventory, performance monitoring via the IBM Cloud, optional DR as a service for Power, and free access and capacity flexibility with SolfLayer (12 month starter pack).

Will the new LC line and its various cloud freebies get the low cost x86 monkey off IBM’s back? That’s the hope in Armonk. The new LC servers can be acquired at a lower price and can deliver 80% more performance per dollar spent over x86-based systems, according to IBM. This efficiency enables businesses and cloud service providers to lower costs and combat data center sprawl.

DancingDinosaur has developed TCO and ROI analyses comparing mainframe and Power systems to x86 for a decade, maybe more.  A few managers get it, but most, or their staff, have embedded bias and will never accept non-x86 machines. To them, any x86 system always is cheaper regardless of the specs and the math. Not sure even free will change their minds.

The new Power Systems LC lineup is price-advantaged over comparatively configured Intel x86-based servers, costing 30% less in some configurations.  Online LC pricing begins at $5999. Additional models with smaller configurations sport lower pricing through IBM Business Partners. All but the HPC machine are available immediately. The HPC machine will ship Sept. 26.

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

 

Oracle Aims at Intel and IBM POWER

July 8, 2016

In late June Oracle announced the SPARC S7 processor, a new 20nm, 4.27 GHz, 8-core/64-thread SPARC processor targeted for scale-out Cloud workloads that usually go to Intel x86 servers. These are among the same workloads IBM is aiming for with POWER8, POWER9, and eventually POWER10, as reported by DancingDinosaur just a couple of weeks ago.

oracle roadmap trajectory

Oracle 5-year SPARC trajectory (does not include newly announced S series).

According to Oracle, the latest additions to the SPARC platform are built on the new 4.27 GHz, 8-core/64-thread SPARC S7 microprocessor with what Oracle calls Software-in-Silicon features such as Silicon Secured Memory and Data Analytics Accelerators, which enable organizations to run applications of all sizes on the SPARC platform at commodity price points. All existing commercial and custom applications will also run on the new SPARC enterprise cloud services and solutions unchanged while experiencing improvements in security, efficiency, and simplicity.

By comparison, the IBM POWER platform includes with the POWER8, which is delivered as a 12-core, 22nm processor. The POWER9, expected in 2017, will be delivered as 14nm processor with 24 cores and CAPI and NVlink accelerators, which ensure delivery of more performance with greater energy efficiency.  By 2018, the IBM roadmap shows POWER8/9 as a 10nm, maybe even a 7nm, processor, based on the existing micro-architecture. And an even beefier POWER10 is expected to arrive around 2020.

At the heart of the Oracle’s new scale-out, commodity-priced server, the S7. According to Oracle, the SPARC S7 delivers balanced compute performance with 8 cores per processor, integrated on-chip DDR4 memory interfaces, a PCIe controller, and coherency links. The cores in the SPARC S7 are optimized for running key enterprise software, including Java applications and database. The SPARC S7–based servers use very high levels of integration that increase bandwidth, reduce latencies, simplify board design, reduce the number of components, and increase reliability, according to Oracle. All this promises an increase in system efficiency with a corresponding improvement in the economics of deploying a scale-out infrastructure when compared to other vendor solutions.

Oracle’s SPARC S7 processor, based on Oracle enterprise class M7 servers, is optimized for horizontally scalable systems with all the key functionality included in the microprocessor chip. Its Software-in-Silicon capabilities, introduced with the SPARC M7 processor, are also available in the SPARC S7 processor to enable improved data protection, cryptographic acceleration, and analytics performance. These features include Security-in-Silicon, which provides Silicon Secured Memory and cryptographic acceleration, and Data Analytics Accelerator (DAX) units, which provide In-memory query acceleration and in-line decompression

SPARC S7 processor–based servers include single- and dual-processor systems that are complementary to the existing mid-range and high-end systems based on Oracle’s SPARC M7 processor. SPARC S7 processor–based servers include two rack-mountable models. The SPARC S7-2 server uses a compact 1U chassis, and the SPARC S7-2L server is implemented in a larger, more expandable 2U chassis. Uniformity of management interfaces and the adoption of standards also should help reduce administrative costs, while the chassis design provides density, efficiency, and economy as increasingly demanded by modern data centers. Published reports put the cost of the new Oracle systems at just above $11,000 with a single processor, 64GB of memory and two 600GB disk drives, and up to about $50,000 with two processors and a terabyte of memory.

DancingDinosaur doesn’t really have enough data to compare the new Oracle system with the new POWER8 and upcoming POWER9 systems. Neither Oracle nor IBM have provided sufficient details. Oracle doesn’t even offer a roadmap at this point, which might tell you something.

What we do know about the POWER machines is this: POWER9 promises a wealth of improvements in speeds and feeds. Although intended to serve the traditional Power Server market, it also is expanding its analytics capabilities and is being optimized for new deployment models like hyperscale, cloud, and technical computing through scale-out deployment. Available for either clustered or multiple formats, it will feature a shorter pipeline, improved branch execution, and low latency on the die cache as well as PCI gen 4.

According to IBM, you can expect a 3x bandwidth improvement with POWER9 over POWER8 and a 33% speed increase. POWER9 also will continue to speed hardware acceleration and support next gen NVlink, improved coherency, enhance CAPI, and introduce a 25 GPS high speed link. Although the 2-socket chip will remain, IBM suggests larger socket counts are coming. It will need that to compete with Intel.

At least IBM showed its POWER roadmap. There is no comparable information from Oracle. At best, DancingDinosaur was able to dig up the following sketchy details for 2017-2019: Next Gen Core, 2017 Software-in-Silicon V1, Scale Out fully integrated Software-in-Silicon V1 or 2; 2018- 2019 Core Enhancements, Increased Cache, Increased Bandwidth, Software-in-Silicon V3.

Both Oracle and IBM have made it clear neither really wants to compete in the low cost, scale out server market. However, as both companies’ large clients turn to scale out, hyperscale Intel-based systems they have no choice but to follow the money. With the OpenPOWER Foundation growing and driving innovation, mainly in the form of accelerators, IBM POWER may have an advantage driving a very competitive price/performance story against Intel. With the exception of Fujitsu as an ally of sorts, Oracle has no comparable ecosystem as far as DancingDinosaur can tell.

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

 

IBM Fires a Shot at Intel with its Latest POWER Roadmap

June 17, 2016

In case you worry that IBM will abandon hardware in the pursuit of its strategic initiatives focusing on cloud, mobile, analytics and more; well, stop worrying. With the announcement of its POWER Roadmap at the OpenPOWER Summit earlier this spring, it appears POWER will be around for years to come. But IBM is not abandoning the strategic initiatives either; the new Roadmap promises to support new types of workloads, such as real time analytics, Linux, hyperscale data centers, and more along with support for the current POWER workloads.

power9b

Pictured above: POWER9 Architecture, courtesy of IBM

Specifically, IBM is offering a denser roadmap, not tied to technology and not even tied solely to IBM. It draws on innovations from a handful of the members of the Open POWER Foundation as well as support from Google. The new roadmap also signals IBM’s intention to make a serious run at Intel’s near monopoly on enterprise server processors by offering comparable or better price, performance, and features.

Google, for example, reports porting many of its popular web services to run on Power systems; its toolchain has been updated to output code for x86, ARM, or Power architectures with the flip of a configuration flag. Google, which strives to be everything to everybody, now has a highly viable alternative to Intel in terms of performance and price with POWER. At the OpenPOWER Summit early in the spring, Google made it clear it plans to build scale-out server solutions based on OpenPower.

Don’t even think, however, that Google is abandoning Intel. The majority of its systems are Intel-oriented. Still, POWER and the OpenPOWER community will provide a directly competitive processing alternative.  To underscore the situation Google and Rackspace announced they were working together on Power9 server blueprints for the Open Compute Project, designs that reportedly are compatible with the 48V Open Compute racks Google and Facebook, another hyperscale data center, already are working on.

Google represents another proof point that OpenPOWER is ready for hyperscale data centers. DancingDinosaur, however, really is interested most in what is coming from OpenPOWER that is new and sexy for enterprise data centers, since most DancingDinosaur readers are focused on the enterprise data center. Of course, they still need ever better performance and scalability too. In that regard OpenPOWER has much for them in the works.

For starters, POWER8 is currently delivered as a 12-core, 22nm processor. POWER9, expected in 2017, will be delivered as 14nm processor with 24 cores and CAPI and NVlink accelerators. That is sure to deliver more performance with greater energy efficiency.  By 2018, the IBM roadmap shows POWER8/9 as a 10nm, maybe even 7nm, processor, based on the existing micro-architecture.

The real POWER future, arriving around 2020, will feature a new micro-architecture, sport new features and functions, and bring new technology. Expect much, if not almost all, of the new functions to come from various OpenPOWER Foundation partners,

POWER9, only a year or so out, promises a wealth of improvements in speeds and feeds. Although intended to serve the traditional Power Server market, it also is expanding its analytics capabilities and bringing new deployment models for hyperscale, cloud, and technical computing through scale out deployment. This will include deployment in both clustered or multiple formats. It will feature a shorter pipeline, improved branch execution, and low latency on the die cache as well as PCI gen 4.

Expect a 3x bandwidth improvement with POWER9 over POWER8 and a 33% speed increase. POWER9 also will continue to speed hardware acceleration and support next gen NVlink, improved coherency, enhance CAPI, and introduce a 25 GPS high speed link. Although the 2-socket chip will remain, IBM suggests larger socket counts are coming. It will need that to compete with Intel.

As a data center manager, will a POWER9 machine change your data center dynamics?  Maybe, you decide: a dual-socket Power9 server with 32 DDR4 memory slots, two NVlink slots, three PCIe gen-4 x16 slots, and a total 44 core count. That’s a lot of computing power in one rack.

Now IBM just has to crank out similar advances for the next z System (a z14 maybe?) through the Open Mainframe Project.

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

 

IBM Advances SSD with Phase-Change Memory Breakthrough

May 20, 2016

Facing an incessant demand to speed data through computers the latest IBM storage memory advance, announced earlier this week, will ratchet up the speed another notch or two. Scientists at IBM Research have demonstrated storing 3 bits of data per cell using phase-change memory (PCM). Until now, PCM had been tried but had never caught on for a variety of reasons. By storing 3 bits per cell, IBM can boost PCM capacity and speed and lower the cost.

TLCPCMSmall (1)

IBM multi-bit PCM chip connected to a standard integrated circuit board.

Pictured above, the chip consists of a 2 × 2 Mcell array with a 4- bank interleaved architecture, IBM explained. The memory array size is 2 × 1000 μm × 800 μm. The PCM cells are based on doped-chalcogenide alloy and were integrated into the prototype chip serving as a characterization vehicle in 90 nm CMOS baseline technology.

Although PCM has been around for some years only with this latest advance is it attracting the industry’s attention as a potential universal memory technology based on its combination of read/write speed, endurance, non-volatility, and density. Specifically, PCM doesn’t lose data when powered off, unlike DRAM, and the technology can endure at least 10 million write cycles, compared to an average flash USB stick, which tops out at 3,000 write cycles.  Primary use cases will be capturing massive volumes of data expected from mobile devices and the Internet of Things.

PCM, in effect, adds another tier to the storage/memory hierarchy, coming in between DRAM and Flash at the upper levels of the storage performance pyramid. The IBM researchers envision both standalone PCM and hybrid applications, which combine PCM and flash storage together. For example, PCM can act as an extremely fast cache by storing a mobile phone’s operating system and enabling it to launch in seconds. For enterprise data centers, IBM envisions entire databases could be stored in PCM for blazing fast query processing of time-critical online applications, such as financial transactions.

As reported by CNET, PCM fits neatly between DRAM and flash. DRAM is 5-10x faster at retrieving data than PCM, while PCM is about 70x faster than flash. IBM reportedly expects PCM to be cheaper than DRAM, eventually becoming as cheap as flash (or course flash keeps getting cheaper too). PCM’s ability to hold three bits of data rather than 2 bits, PCM’s previous best, enables packing more data into a chip, which lowers the cost of PCM storage and boosts its competitive position against technologies like Flash and DRAM.

Phase change memory is the first instantiation of a universal memory with properties of both DRAM and flash, thus answering one of the grand challenges of our industry,” wrote Haris Pozidis, key researcher and manager of non-volatile memory research at IBM Research –in the published announcement. “Reaching 3 bits per cell is a significant milestone because at this density the cost of PCM will be significantly less than DRAM and closer to flash.”

IBM explains how PCM works: PCM materials exhibit two stable states, the amorphous (without a clearly defined structure) and crystalline (with structure) phases, of low and high electrical conductivity, respectively. In digital systems, data is stored as a 0 or a 1. To store a 0 or a 1 on a PCM cell, a high or medium electrical current is applied to the material. A 0 can be programmed to be written in the amorphous phase or a 1 in the crystalline phase, or vice versa. Then to read the bit back, a low voltage is applied.

To achieve multi-bit storage IBM scientists have developed two innovative enabling technologies: 1) a set of drift-immune cell-state metrics and 2) drift-tolerant coding and detection schemes. These new cell-state metrics measure a physical property of the PCM cell that remains stable over time, and are thus insensitive to drift, which affects the stability of the cell’s electrical conductivity with time. The other measures provide additional robustness of the stored data. As a result, the cell state can be read reliably over long time periods after the memory is programmed, thus offering non-volatility.

Combined these advancements address the key challenges of multi-bit PCM—drift, variability, temperature sensitivity and endurance cycling, according to IBM. From there, the experimental multi-bit PCM chip used by IBM scientists is connected to a standard integrated circuit board

Expect to see PCM first in Power Systems. At the 2016 OpenPOWER Summit in San Jose, CA, last month, IBM scientists demonstrated PCM attached to POWER8-based servers (made by IBM and TYAN® Computer Corp.) via the CAPI (Coherent Accelerator Processor Interface) protocol, which speeds the data to storage or memory. This technology leverages the low latency and small access granularity of PCM, the efficiency of the OpenPOWER architecture, and the efficiency of the CAPI protocol, an example of the OpenPower Foundation in action. Pozidis suggested PCM could be ready by 2017; maybe but don’t bet on it. IBM still needs to line up chip makers to produce it in commercial quantities among other things.

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

 

 


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