by Gary Mintchell | Dec 22, 2015 | Automation, Industrial Computers, News, Technology
Anyone who thinks PCs when the company name Dell comes up (“Hey, Dude, You’re getting a Dell.”) has missed the company’s growth over the past decade. I’ve written about its new foray into Internet of Things with a product specifically targeted at manufacturing industries. The company has announced some advances in its High Performance Computing platform.
High Performance Computing
These advances include innovative new systems designed to simplify mainstream adoption of HPC and data analytics in research, manufacturing and genomics. Dell also unveiled expansions to its HPC Innovation Lab and showcased next-generation technologies including the Intel Omni-Path Fabric.
HPC is becoming increasingly critical to how organizations of all sizes innovate and compete. Many organizations lack the in-house expertise to configure, build and deploy an HPC system without losing focus on their core science, engineering and analytic missions. As an example, according to the National Center for Manufacturing Sciences, 98 percent of all products will be designed digitally by 2020, yet 95 percent of the center’s 300,000 manufacturing companies have little or no HPC expertise.
“HPC is no longer a tool only for the most sophisticated researchers. We’re taking what we’ve learned from working with some of the most advanced, sophisticated universities and research institutions and customizing that for delivery to mainstream enterprises,” said Jim Ganthier, vice president and general manager, Engineered Solutions and Cloud, Dell. “As the leading provider of systems in this space, Dell continues to break down barriers and democratize HPC. We’re seeing customers in even more industry verticals embrace its power.”
Accelerating Mainstream Adoption
Dell HPC System Portfolio, a family of HPC and data analytics solutions, combines the flexibility of custom systems with the simplicity, reliability and value of a preconfigured, factory-built system that includes:
- Simplified design, configuration, and ordering in a matter of hours instead of weeks;
- Domain-specific design that’s designed and tuned by Dell engineers and domain experts for specific science, engineering and analytics workloads using flexible industry-standard building blocks; and,
- Fully tested and validated systems by Dell engineering with a single point of hardware support and a wide range of additional service options.
New application-specific Dell HPC System Portfolio offerings include:
- Dell HPC System for Genomic Data Analysis is designed to meet the needs of genomic research organizations to enable cost-effective bioinformatics centers delivering results and identifying treatments in clinically relevant timeframes while maintaining compliance and protecting confidential data. The platform is a result of key learnings from Dell’s relationship with Translational Genomics Research Institute (TGen) to help clinical researchers and doctors expand the reach and impact of the world’s first Food and Drug Administration-approved precision medicine trial for pediatric cancer. TGen has been able to improve outcomes for more patients by creating targeted treatments at least one week faster than they could be accomplished previously.
- Dell HPC System for Manufacturing is designed for customers running complex manufacturing design simulations using workstations, clusters or both. Applicable use cases include Finite Element Analysis for structural analysis using ANSYS Mechanical & Computational Fluid Dynamics for predicting fluid behavior in designs utilizing ANSYS Fluent or CD-adapco STAR-CCM+.
- Dell HPC System for Research is designed as a foundation, or reference architecture, for baseline research systems and numerous applications involving complex scientific analysis. This standard cluster configuration can be used as a starting point for Dell’s customers and systems engineers to quickly develop research systems that match the unique needs of research customers requiring systems for a wide variety of research agendas.
Accelerating HPC Technology Innovation and Partnerships
Dell announced a new expansion of its Dell HPC Innovation Lab in cooperation with Intel specifically for support of its Intel Scalable System Framework. This multi-million dollar expansion to the Austin, Texas, facility includes additional domain expertise, infrastructure and technologists. The lab is designed to unlock the capabilities and commercialize the benefits of advanced processing, network and storage technologies as well as enable open standards across the industry.
Beyond becoming the first major original equipment manufacturer (OEM) to join the Intel Fabric Builders program, Dell is working closely with Intel to support its Intel Scalable System Framework, which includesIntel Omni-Path Fabric technology, next-generation Intel Xeon processors, the Intel Xeon Phi processor family, and the Intel Enterprise Edition for Lustre. Announcements include:
- New Dell Networking H-Series switches and adapters for PowerEdge servers featuring the Intel Omni-Path Architecture. These provide a next-generation fabric technology designed for HPC deployments. The architecture includes advanced features such as traffic flow optimization, packet integrity protection and dynamic lane scaling allowing for finer-grained control on the fabric level to enable high resiliency, high performance and optimized traffic movement.
- Dell and Intel support for the Linux Foundation’s OpenHPC community. The community is designed to provide a common platform on which end-users can collaborate and innovate to simplify the complexity of installation, configuration and ongoing maintenance of implementing a custom software stack and easing a path to exascale.
“We’re excited to collaborate with Dell to bring advanced systems to market early next year using the Intel Scalable System Framework,” said Charles Wuischpard, vice president and general manager of HPC Platform Group at Intel. “Dell’s position as our largest and fastest-growing customer for Intel Enterprise Edition for Lustre, their work on Omni-Path Architecture and next-generation Intel Xeon Phi, and their initiatives to expand the Dell Innovation Lab demonstrate their commitment to rapidly expanding the ecosystem for HPC.”
Mellanox Partnership
Dell and Mellanox announced additional investment in Dell’s existing HPC Innovation Lab to provide an end-to-end EDR 100Gb/s InfiniBand supercomputer system. The system is designed to showcase extreme scalability by leveraging the offloading capabilities and advanced acceleration engines of the Mellanox interconnect as well as provide application specific benchmarking, and characterizations for customers and partners.
“With this new investment, Dell’s HPC Innovation Lab will now enable new levels of applications efficiency and innovative research capabilities. Together we will help build the solutions of the future,” said Gilad Shainer, vice president of marketing, Mellanox Technologies.
Availability
- The Dell HPC System for Genomic Data Analysis is available today.
- The Dell HPC Systems for Manufacturing and Research will be available in early 2016.
- The Dell Networking H-series switches, adapters and software based on the Intel Omni-Path Architecture will be available in the first half of 2016.
by Gary Mintchell | Jun 24, 2015 | Automation, Data Management, Operations Management
There are so many ways we can go to try to understand and then to make use of the Industrial Internet of Things. As my thinking coalesces I’ve come to the conclusion that the IIoT is a tool. It is a tool to be used in the service of an overall manufacturing/production strategy.
In order to properly use this tool of connected devices serving real-time data, we are going to need advances in data science.
Two database types seem to dominate in manufacturing—at least as expounded by suppliers. One is a relational (SQL) database. The other type is data historian.
I remember talking to some of the tech guys at Opto 22 about exploring semi-structured and open source variants such as NoSQL. At the time they thought that SQL would be all they need. And maybe so. But that was a couple of years ago.
All that discussion introduces an important podcast I just listened to. I subscribe to the O’Reilly Radar podcasts on iTunes. They’ve been cranking out about one per week—usually to promote an O’Reilly book or O’Reilly conference.
Data Science
Michael Stonebraker was awarded the 2014 ACM Turing Award for fundamental contributions to the concepts and practices underlying modern database systems. In this podcast, he discusses the future of data science and the importance—and difficulty—of data curation.
[Notes from the O’Reilly Website]
One size does not fit all
Stonebraker notes that since about 2000, everyone has realized they need a database system, across markets and across industries. “Now, it’s everybody who’s got a big data problem,” he says. “The business data processing solution simply doesn’t fit all of these other marketplaces.” Stonebraker talks about the future of data science — and data scientists — and the tools and skill sets that are going to be required:
It’s all going to move to data science as soon as enough data scientists get trained by our universities to do this stuff. It’s fairly clear to me that you’re probably not going to retread a business analyst to be a data scientist because you’ve got to know statistics, you’ve got to know machine learning. You’ve got to know what regression means, what Naïve Bayes means, what k-Nearest Neighbors means. It’s all statistics.
All of that stuff turns out to be defined on arrays. It’s not defined on tables. The tools of future data scientists are going to be array-based tools. Those may live on top of relational database systems. They may live on top of an array database system, or perhaps something else. It’s completely open.
Getting meaning out of unstructured data
Gathering, processing, and analyzing unstructured data presents unique challenges. Stonebraker says the problem really is with semi-structured data, and that “relational database systems are doing just fine with that”:
When you say unstructured data, you mean one of two things. You either mean text or you mean semi-structured data. Mostly, the NoSQL guys are talking about semi-structured data. When you say unstructured data, I think text. … Everybody who’s trying to get meaning out of text has an application-specific parser because they’re not interested in general natural language processing. They’re interested in specific kinds of things. They’re all turning that into semi-structured data. The real problem is on semi-structured data. Text is converted to semi-structured data. … I think relational database systems are doing just fine on that. … Most any database system is happy to ingest that stuff. I don’t see that being a hard problem.
Data curation at scale
Data curation, on the other hand, is “the 800-pound gorilla in the corner,” says Stonebraker. “You can solve your volume problem with money. You can solve your velocity problem with money. Curation is just plain hard.” The traditional solution of extract, transform, and load (ETL) works for 10, 20, or 30 data sources, he says, but it doesn’t work for 500. To curate data at scale, you need automation and a human domain expert. Stonebraker explains:
If you want to do it at scale — 100s, to 1000s, to 10,000s — you cannot do it by manually sending a programmer out to look. You’ve got to pick the low-hanging fruit automatically, otherwise you’ll never get there; it’s just too expensive. Any product that wants to do it at scale has got to apply machine learning and statistics to make the easy decisions automatically.
The second thing it has to do is, go back to ETL. You send a programmer out to understand the data source. In the case of Novartis, some of the data they have is genomic data. Your programmer sees an ICU 50 and an ICE 50, those are genetic terms. He has no clue whether they’re the same thing or different things. You’re asking him to clean data where he has no clue what the data means. The cleaning has to be done by what we could call the business owner, somebody who understands the data, and not by an IT guy. … You need domain knowledge to do the cleaning — pick the low-hanging fruit automatically and when you can’t do that, ask a domain expert, who invariably is not a programmer. Ask a human domain expert. Those are the two things you’ve got to be able to do to get stuff done at scale.
Stonebraker discusses the problem of curating data at scale in more detail in his contributed chapter in a new free ebook, Getting Data Right.
by Gary Mintchell | Feb 25, 2015 | Automation, Technology
An article in today’s Wall Street Journal, Jobs and the Clever Robot, dredges up once again the debate “will automation take away all jobs”.
In typical modern journalism style, the article offers no conclusion. It’s “he said, she said” reporting. Let’s just go out and get a few quotes on each side and fill some space. “People are always interested in whether their jobs will go away,” I’m sure some editor told a reporter.
I, for one, wish we already had driverless cars. My trips to Chicago over the past 16 years would have been so much better if I could have read or worked rather than driving. No train or bus was a feasible alternative. I don’t really want to see truck drivers lose their jobs, but every time I’m on suspect roads (slush, ice, snow, fog) and have a semi rig pass me at a high rate of speed I’d love to see automated drivers.
The problem is, we cannot foresee the types of jobs and the changes in work coming in the future. Maybe we need some science fiction writers to tackle the subject and dream up alternative scenarios. What is manufacturing going to look like in 20 years? Can we automate any more of a refinery than we do now? Should we? That would give us more to think on.
Critical reading
Speaking of “he said, she said” journalism, take this article in The New York Times from this morning, Should Athletes Eat Fat or Carbs?
The writer says that most athletes believe in building up with carbs for a workout, but maybe fats would be just as good or better. Once again the methodology was to go out and interview a bunch of people, string together truncated quotes, reach the desired word limit, hit “send” on the keyboard.
There is too much of this writing. In B2B as well as mainstream media. Let’s take a stand, or at least give a reasoned analysis.
by Gary Mintchell | Jan 13, 2015 | Automation, Education, Internet of Things, Leadership, News, Operations Management, Software, Technology
Let the debates begin! Jim Pinto has published his 2015 prognostications in the latest JimPintoBlog.
Check out his entire list and enter your thoughts on his blog. I’ll highlight some of his thoughts and add some of my own.
Automation Industry Trends
New inflection points will change the leadership lineup.
GM—I do not expect big changes in the automation leadership lineup. Mitsubishi, Rockwell Automation and Siemens are dominant in their home areas and fighting it out in China and India. Siemens has a bit of an edge having been international for a longer period of time. But as automation commoditizes, perhaps some new entrants will grab some share. If Bedrock Automation can market well, watch out for it. On the process side, Invensys is gone, absorbed by Schneider Electric. So the process automation business becomes even more of a minor part of the overall businesses, like ABB, Emerson Process Management, and Yokogawa. The only interesting situation in that market area is Honeywell Process Solutions. But I don’t really expect any change there.
I think 3D printing (additive manufacturing) is a game changer and one of the most important things from last week’s CES. It’s not strictly automation, though.
From Jim:
- Internet of Things (IoT): The Industrial Internet will transform the next decade. Intelligent sensors and networks will take measurement and control to the next level, dramatically improving productivity and efficiencies in production. Growth in 2015 will be bottom-up, not top-down.
- Smaller, Cheaper Sensors: Everyone is looking for or working on smaller, cheaper sensors for widespread use in IoT. Expect fast growth for sensors this year.
- Cloud Computing: Cloud computing technology reduces capital expenditures and IT labor costs by transferring responsibility to cloud computing providers, allowing secure and fast access for data-driven decisions. The significant gains in efficiency, cost and capability will generate continuing rapid growth in 2015.
- 3D Printing in Manufacturing: Today, do-it-yourself manufacturing is possible without tooling, large assembly lines or multiple supply chains. 3D printing is reshaping product development and manufacturing.
- Mobile Devices in Automation: The use of WiFi-connected tablets, smartphones and mobile devices is spreading quickly. Handheld devices reduce costs, improve operating efficiency, boost productivity and increases throughput. More and more employers are allowing BYOD (bring your own device).
- Robotics: Millions of small and medium-sized businesses that will benefit from cheaper robots that can economically produce a wide variety of products in small numbers. The next generation of robots will be cheaper and easier to set up, and will work with people rather than replace them.
- Control Systems Security: In spite of apprehensions over consumer security breach events, industrial cyber security has mostly been ignored due to lack of understanding of solution costs. Many companies struggle to justify what is seen as added cost to secure their operation. Major security breaches will change this attitude.
Business Technology Trends
Gartner’s top trends for 2015 (3) cover three themes: the merging of the real and virtual worlds, the advent of intelligence everywhere, and the technology impact of the digital business shift. There is a high potential for disruption to the business with the need for a major investment, or the risk of being late to adopt.
Here are the top Gartner trends:
- Computing Everywhere: As mobile devices continue to proliferate, there will be increased emphasis on the needs of the mobile users. Increasingly, the overall environment will need to adapt to the requirements of the mobile user
- 3D Printing: Worldwide shipments of 3D printers are expected to grow 98 percent in 2015, followed by a doubling of unit shipments in 2016, reaching a tipping point over the next three years.
- Advanced, Pervasive and Invisible Analytics: The volume of data generated by embedded systems generates vast pools of structured and unstructured data inside and outside the enterprise. Organizations need to deliver exactly the right information to the right person, at the right time, so analytics will become deeply, but invisibly embedded everywhere.
- Smart Machines: Advanced algorithms will allow systems to understand their environment, learn for themselves, and act autonomously.
- Cloud Computing: The convergence of cloud and mobile computing will continue to promote the growth of centrally coordinated applications that can be delivered to any device. Applications will evolve to support simultaneous use of multiple devices.
- Risk-Based Security and Self-Protection: All roads to the digital future lead through security. Organizations will increasingly recognize that it is not possible to provide a 100 percent secured environment. They will apply more-sophisticated risk assessment and mitigation tools. Every app needs to be self-aware and self-protecting.
GM—My take is that the biggest thing in this area is analytics combined with improved visualizations and dashboards that take advantage of smartphones and tablets. Cloud is here. IoT is here. Security will forever be an important part of business.
2015 Consumer Electronics Show
- Wearable Devices: The time is right for wearable devices.
- Practical green tech.
- Sustainability and transportation: Tesla Model X all-electric SUV with the doors that open like a Delorean. Electric-assisted bike technology; electric scooter with swappable batteries and dashboard analytics.
- Kid-Tech: Apps to help teach children science, math, and tech. Fun little robots that teach kids computer programming concepts. Drawing, design, and color patterns to help kids learn about robotics and computer programming.
GM—as I’ve already written, autonomous vehicles could be a game changer and 3D printing was huge. The outlier is drones. Who knows where that might go?
Future Prognostications 2015-2025
Here are ten prognostications for the next decade, picked from the World Future Society (7) forecasts, plus other readings and discussions with Futurists.
- – Education: A major shift to on-line education and certification is already happening, and will continue steadily.
- – Jobs: Advances in artificial intelligence will eliminate human workers.
- – Robot Work Force
- – Middle Class Impasse: delaying retirement, income stagnating
- – Driverless cars
- – Speak to Computers.
- – Robotic Augmentation (exoskeletons)
- – Health & Well-being: sensors everywhere
- – Brain scanning will replace juries
- -Energy: Futurist Ray Kurzweil notes that solar power has been doubling every two years for the past 30 years while costs have been dropping. He says solar energy is only six doublings (less than 14 years) away from meeting 100% percent of energy needs.
GM-There are going to be some disruptions and huge benefits from a number of these. Autonomous vehicles and health advances are fantastic. I wish education would change more quickly that it does. Even those who wish to disrupt education mainly only have the political agenda of “teachers’ unions” and driving down salaries. (Why is it a political agenda to drive down salaries. Shouldn’t we be trying to improve everyone’s lot in life?)
I’m not a fan of Kurzweil. 100% is not realistic—maybe residential, but not everything. Don’t think there’s enough volts there!
I think we are going to need those labor-saving, productivity-enhancing advancements because we’re actually facing a labor shortage in 10 years. Time to start thinking farther ahead.
Humans have a way of adapting to thrive. I am optimistic about the future!
Yes, Jim, I’m with you there!
by Gary Mintchell | Dec 18, 2014 | Automation, News, Technology
What happens when we teach a computer how to learn? Technologist Jeremy Howard shares some surprising new developments in the fast-moving field of deep learning, a technique that can give computers the ability to learn Chinese, or to recognize objects in photos, or to help think through a medical diagnosis. (One deep learning tool, after watching hours of YouTube, taught itself the concept of “cats.”) Get caught up on a field that will change the way the computers around you behave … sooner than you probably think.
That is the description of this TEDx Talk on the hubris of a technologist, er, I mean, the science fiction possibilities of technology run amok.
As much as we look back and see how much technology has aided humans, there are still those who look ahead through a darkened glass. Here is yet another technologist who believes that soon we’ll all be out of work and will just be lazy, good-for-nothing slaves to technology.
Time after time we’ve seen how technology has greatly improved the lives of humans. People have been removed from dirty, dangerous, demeaning work. Yet, there remain many other places to tackle that same problem—I can think of mining for an example. How many miners do we need to lose to cave-ins or black lung?
The main problem I see with Howard’s analysis is the old “linear extrapolation” trap. He says in effect that this technology can never stop growing exponentially. That, of course, is false. Nothing in nature continues to grow forever linearly. It will either level off or be asymptotic to some axis.
On the other hand, he does have some fascinating examples of technology helping humans.
http://www.ted.com/talks/jeremy_howard_the_wonderful_and_terrifying_implications_of_computers_that_can_learn
