LANL Sends Environmental Management to the Cloud

By Nicole Hemsoth

July 19, 2011

Purveyor of cloud-based environmental management software, Locus Technologies, recently announced that it had been selected to manage environmental information and data for Los Alamos National Laboratory (LANL).

The company claimed the contract to manage the lab’s data in their cloud was worth up to $2 million. Their Locus EIM software will help LANL organize and manage all future environmental compliance and monitoring activities using a SaaS model. Locus says this will better position LANL to address legacy site contamination, both chemical and radioactive, across a number of locations and streamline views into the bigger picture of environmental management at the facility.

The cloud-based software will fulfill a number of functions, including organization of a number of media types, comparison of historical and new contamination levels, planning, sampling and processing environmental data and more generally handling all coordination, integration and community of that data.

Locus says they’ve designed their software  “specifically to meet challenging water-quality management issues, covering both analytical chemistry and the management of radionuclides data in a complex hydro-geological setting.” They say their EIM software will also provide a web-based GIS system for Los Alamos data that will be available to the general public, bringing ease of use and complete transparency to complex data sets. “

We recently interviewed Locus Technologies’ president and CEO, Neno Duplan about the contract and got to the heart of what is involved with these types of software solutions in cloud environments.

HPCc: Can you describe your cloud and what made this an attractive option for LANL—after all, there are a number of other possibilities. Is this an on-demand cloud or public resource like Amazon’s or SaaS or some combination of all? Please be very specific.

Duplan: Locus offers its on-demand services through its own Cloud platform that has been serving customers in this industry since 1999. Locus Cloud is true Software as a Service (SaaS) and that requires some explanation.  We have noticed over the last year or so lots of confusion about this term and it is important to define it.  The myriad terms used by software and service companies to describe the delivery of on-premise applications is confusing—and that confusion is by design. As more and more companies move to SaaS solutions and cloud computing, legacy software vendors will continue to confuse the conversation.

Cloud, software-as-a-service (SaaS), on-demand, application service provider (ASP), business process outsourcing (BPO), outsourced—what do all these words mean? Are they really all the same? Many legacy on-premise application providers would like you to believe so, but there are vast differences. The distinction between SaaS and earlier applications delivered over the Internet, or applications that environmental consultants would deliver over Internet today, is that SaaS solutions were developed specifically to leverage web technologies such as the browser, thereby making them web-native.

The data design and architecture of SaaS applications are specifically built with a single instance of software shared among all customers accessing it and ‘multi-tenant’ backend, thus enabling multiple customers or users to access a shared data model. Locus EIM is one such application.  Systems developed as client servers also could be delivered via web, but they don’t qualify as SaaS applications as they were not natively developed for the web. Those are kind of drinking of “nonalcoholic wine”. Now with definition out of the way, let’s focus on Locus Cloud apps.

Locus Cloud has the following characteristics:

•    Customer implementations off premise and in shared datacenters
•    Pay-as-you-go pricing model
•    All customers on the same software code line
•    Customer sharing of data center resources
•    Application delivery is one-to-many model (single instance, multi-tenant architecture) [as opposed to  a one-to-one model, including architecture, pricing, partnering, and management characteristics]
•    Centralized and rolling feature updating, which obviates the need for end-users to download patches and upgrades?
•    Frequent integration into a larger network of communicating software—either as part of a mashup or a plugin to a platform as a service
•    Updates included with the service

By having every customer on the same line of code and the same version of software, Locus’ SaaS provides real business value: lower cost, better service, and greater customer intimacy.

HPCc: Provide us with the hardware specs for this particular cloud service—we are a bit confused; do you have a cluster upon which you host customer data/applications? Again, be as specific and detailed as possible.

Duplan: Locus Cloud is delivered through a redundant professionally managed data centers in clustered environment. Both application(s) and data are hosted on Locus cloud. Our server farms are highly scalable and we can expand to meet any customer demand. We use standard server technology and there is nothing proprietary about hardware. It is commodity hardware.

EIM software is quite sophisticated—can you go a bit beyond the press release and tell us first what this will entail data-wise/what the software will accomplish and also, what the computational requirements are for something at the scale LANL requires.

Yes, EIM is a sophisticated application dealing with complex data sets and complex workflow processes. In addition to expected functionality to deal with complex domain of analytical chemistry and radionuclides management EIM also provides:

•    Meshups with Google Maps for GIS-based data mapping
•    Ability to quickly incorporate more feature requests from users, since there is frequently no marginal cost for requesting new features
•    Faster new feature releases, since the entire community of users benefits (the wisdom of the crowd syndrome along the rolling upgrade program)
•    Embodiment of recognized best practices, since the user community drives Locus to support best practice
•    Automation of data collection via a single file EDD (Electronic Data Deliverable) format
•    Proven record of scalability to millions analytical records managed from a single code instance in real time
•    Embedded Long Term Monitoring Optimization Module
•    Full and embedded data validation module
•    Fully integrated modules offered through Single Sign On with no third party software add-ons.

HPCc: LANL has its own clusters; why did they decide to outsource this type of computing?

Duplan: LANL has its own clusters of servers on premises. But that does not make LANL experts in environmental database development. LANL wanted off-the shelf solution delivered in the cloud to accelerate implementation and bring all their data into the single system. Locus EIM cloud allowed them to do exactly that. Another reason is cost. There is little upfront cost to deploy solution in the cloud as opposed to deploying custom applications on premises.  The third reason is subject matter knowledge. Locus has this in spades and we have the only module in the market that deals with radionuclides (See more in: Japan quake data should be stored in the cloud here or here.)

Locus’ software enabled LANL to organize and validate all key environmental information in a single system, which includes radionculides data, analytical data for water, air and soil, weather data, sustainability, compliance and environmental content. Since Locus software is delivered via Cloud there was no hardware to procure, no large, up-front license fee, and no complex set-ups.

HPCc: Let’s move outside of LANL for a moment—what are some of the most sophisticated use cases are there for your cloud computing service in terms of data size/movement/computational requirements.

Duplan: All Locus deployments are large and complex as our software is designed to deal with huge data sets in the real time. Our applications offered through the cloud are very different from the ones that we see in consumer world such as Google, Amazon, Facebook and alike. Common for consumer web and some business applications are very large number of users, high traffic, retrieving relatively simple and small data sets to perform a simple action on them such as buy or befriend or “like”. In Locus’ case, our user base is much smaller, but much more sophisticated and demanding. It is not atypical that average EIM or ePortal user performs queries that produce millions of records that need to quickly be interpreted with assistance of intelligent databases, charted, contoured, mapped and reported while making sure that myriad of requirements from many regulatory frameworks are met  in the process.

Most of Locus applications dwarf consumer web requirements in terms of complexity and size of databases. For that and other reasons companies like ExxonMobil, Chevron, Honeywell or Exelon all selected Locus’ Cloud to deal with their environmental, energy and sustainability data and information. And that is the reason that if you type in Google a common term “environmental data management”, the link to Locus’ website will be among the top few of the first page of the (unpaid) search results. Significant amount of intelligence and Expert System technology is built in the Locus apps.
 
HPCc: Do you think most users are deploying your service to replace on-site hardware or is this more of a “bursty” needs-driven market to supplement existing HPC?

Duplan: It is more “bursty” needs-driven, but not to replace existing HPC, but to replace non-existent or spreadsheet driven processes that resulted in information overflow that is impossible to manage without paying big bucks to consultants who created the problems in the first place.

Environmental and energy data is collected from a variety of sources: from consultants, contractors, labs, suppliers, customer’s own field employees, or as is more increasingly true, by remote wireless sensors. It is stored in remote locations, such as the supplier’s spreadsheets or other files on the desktop, laptop, or network server of suppliers. The customer usually has no access to, or ownership of, such data. Such large, dispersed volumes of information are difficult to track and very costly to audit without relational databases, and content or document management solutions software. If the customer does adopt environmental information management systems, the systems typically fall into one of two categories:

•    Stand-alone systems that project-level consultants and staff engineers love, but that do not enable managers to perform corporate governance, data-mining, or forecasting tasks, or share information across a large organization or the web.

•    High-end, all-encompassing extensions of ERP systems, such as SAP, that can scale to support the needs of hundreds or thousands of users, but environmental managers refuse to use because they are complex and require costly additional programming to manage environmental or energy data. Such enterprise systems are often characterized as being “a mile wide and inch deep” because they typically lack domain depth, are not offered over the web, are expensive and difficult to install and integrate, cannot be used by suppliers, and are not particularly user-friendly.

As a result, too many businesses and governmental agencies are “flying blind” when it comes to managing their environmental, water or energy information.

Companies with these types of problems should consider the Cloud Computing Model. The model exactly fits the way environmental information needs to be managed through mashups of various databases and technologies, and has the potential to completely upend the way corporations manage their environmental liability data or energy and resource consumption. 

Enterprises that have large portfolios of properties can use Cloud Computing as a very low-cost, no-commitment way to quickly take control of their mission critical environmental data and information and get new services and capabilities to take control of their compliance needs by entirely circumventing the IT department.

Many companies that do not have control or ownership of their critical environmental data, and most today don’t, and rely on an army of consultants and their spreadsheets to meet their reporting requirements, can continue trying to ignore Cloud Computing as it is just in its infancy, but doing so may be a mistake as Cloud Computing is looking more and more a classic disruptive technology.

How quickly can a company get control of its analytical data that sits scattered in consulting offices and consolidate it in to a usable database? Four weeks? Eight weeks? 10 months? For many enterprises, the answer is even longer. Today, the businesses need to respond in Internet time with new services, capabilities, and offerings to stay on top of their environmental compliance requirements. Yet, most companies aren’t well equipped to respond with speed. Most companies still have a “procure and provision” approach to the infrastructure that supports their services. Even if the decision has been made to purchase enterprise software to organize and manage large quantities of environmental and energy information and compliance activities in house, lengthy approval processes often kill many of these systems before they can be deployed.  The reason is that these can be a lengthy process of actions involving everyone from storage, networking, security, and sometimes facilities.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

GDPR’s Impact on Scientific Research Uncertain

May 24, 2018

Amid the angst over preparations—or lack thereof—for new European Union data protections entering into force at week’s end is the equally worrisome issue of the rules’ impact on scientific research. Among the Read more…

By George Leopold

Intel Pledges First Commercial Nervana Product ‘Spring Crest’ in 2019

May 24, 2018

At its AI developer conference in San Francisco yesterday, Intel embraced a holistic approach to AI and showed off a broad AI portfolio that includes Xeon processors, Movidius technologies, FPGAs and Intel’s Nervana Neural Network Processors (NNPs), based on the technology it acquired in 2016. Read more…

By Tiffany Trader

Pattern Computer – Startup Claims Breakthrough in ‘Pattern Discovery’ Technology

May 23, 2018

If it weren’t for the heavy-hitter technology team behind start-up Pattern Computer, which emerged from stealth today in a live-streamed event from San Francisco, one would be tempted to dismiss its claims of inventing Read more…

By John Russell

HPE Extreme Performance Solutions

HPC and AI Convergence is Accelerating New Levels of Intelligence

Data analytics is the most valuable tool in the digital marketplace – so much so that organizations are employing high performance computing (HPC) capabilities to rapidly collect, share, and analyze endless streams of data. Read more…

IBM Accelerated Insights

Mastering the Big Data Challenge in Cognitive Healthcare

Patrick Chain, genomics researcher at Los Alamos National Laboratory, posed a question in a recent blog: What if a nurse could swipe a patient’s saliva and run a quick genetic test to determine if the patient’s sore throat was caused by a cold virus or a bacterial infection? Read more…

Silicon Startup Raises ‘Prodigy’ for Hyperscale/AI Workloads

May 23, 2018

There's another silicon startup coming onto the HPC/hyperscale scene with some intriguing and bold claims. Silicon Valley-based Tachyum Inc., which has been emerging from stealth over the last year and a half, is unveili Read more…

By Tiffany Trader

Intel Pledges First Commercial Nervana Product ‘Spring Crest’ in 2019

May 24, 2018

At its AI developer conference in San Francisco yesterday, Intel embraced a holistic approach to AI and showed off a broad AI portfolio that includes Xeon processors, Movidius technologies, FPGAs and Intel’s Nervana Neural Network Processors (NNPs), based on the technology it acquired in 2016. Read more…

By Tiffany Trader

Pattern Computer – Startup Claims Breakthrough in ‘Pattern Discovery’ Technology

May 23, 2018

If it weren’t for the heavy-hitter technology team behind start-up Pattern Computer, which emerged from stealth today in a live-streamed event from San Franci Read more…

By John Russell

Silicon Startup Raises ‘Prodigy’ for Hyperscale/AI Workloads

May 23, 2018

There's another silicon startup coming onto the HPC/hyperscale scene with some intriguing and bold claims. Silicon Valley-based Tachyum Inc., which has been eme Read more…

By Tiffany Trader

Japan Meteorological Agency Takes Delivery of Pair of Crays

May 21, 2018

Cray has supplied two identical Cray XC50 supercomputers to the Japan Meteorological Agency (JMA) in northwestern Tokyo. Boasting more than 18 petaflops combine Read more…

By Tiffany Trader

ASC18: Final Results Revealed & Wrapped Up

May 17, 2018

It was an exciting week at ASC18 in Nanyang, China. The student teams braved extreme heat, extremely difficult applications, and extreme competition in order to cross the cluster competition finish line. The gala awards ceremony took place on Wednesday. The auditorium was packed with student teams, various dignitaries, the media, and other interested parties. So what happened? Read more…

By Dan Olds

Spring Meetings Underscore Quantum Computing’s Rise

May 17, 2018

The month of April 2018 saw four very important and interesting meetings to discuss the state of quantum computing technologies, their potential impacts, and th Read more…

By Alex R. Larzelere

Quantum Network Hub Opens in Japan

May 17, 2018

Following on the launch of its Q Commercial quantum network last December with 12 industrial and academic partners, the official Japanese hub at Keio University is now open to facilitate the exploration of quantum applications important to science and business. The news comes a week after IBM announced that North Carolina State University was the first U.S. university to join its Q Network. Read more…

By Tiffany Trader

Democratizing HPC: OSC Releases Version 1.3 of OnDemand

May 16, 2018

Making HPC resources readily available and easier to use for scientists who may have less HPC expertise is an ongoing challenge. Open OnDemand is a project by t Read more…

By John Russell

MLPerf – Will New Machine Learning Benchmark Help Propel AI Forward?

May 2, 2018

Let the AI benchmarking wars begin. Today, a diverse group from academia and industry – Google, Baidu, Intel, AMD, Harvard, and Stanford among them – releas Read more…

By John Russell

How the Cloud Is Falling Short for HPC

March 15, 2018

The last couple of years have seen cloud computing gradually build some legitimacy within the HPC world, but still the HPC industry lies far behind enterprise I Read more…

By Chris Downing

Russian Nuclear Engineers Caught Cryptomining on Lab Supercomputer

February 12, 2018

Nuclear scientists working at the All-Russian Research Institute of Experimental Physics (RFNC-VNIIEF) have been arrested for using lab supercomputing resources to mine crypto-currency, according to a report in Russia’s Interfax News Agency. Read more…

By Tiffany Trader

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Deep Learning at 15 PFlops Enables Training for Extreme Weather Identification at Scale

March 19, 2018

Petaflop per second deep learning training performance on the NERSC (National Energy Research Scientific Computing Center) Cori supercomputer has given climate Read more…

By Rob Farber

AI Cloud Competition Heats Up: Google’s TPUs, Amazon Building AI Chip

February 12, 2018

Competition in the white hot AI (and public cloud) market pits Google against Amazon this week, with Google offering AI hardware on its cloud platform intended Read more…

By Doug Black

US Plans $1.8 Billion Spend on DOE Exascale Supercomputing

April 11, 2018

On Monday, the United States Department of Energy announced its intention to procure up to three exascale supercomputers at a cost of up to $1.8 billion with th Read more…

By Tiffany Trader

Lenovo Unveils Warm Water Cooled ThinkSystem SD650 in Rampup to LRZ Install

February 22, 2018

This week Lenovo took the wraps off the ThinkSystem SD650 high-density server with third-generation direct water cooling technology developed in tandem with par Read more…

By Tiffany Trader

Leading Solution Providers

SC17 Booth Video Tours Playlist

Altair @ SC17

Altair

AMD @ SC17

AMD

ASRock Rack @ SC17

ASRock Rack

CEJN @ SC17

CEJN

DDN Storage @ SC17

DDN Storage

Huawei @ SC17

Huawei

IBM @ SC17

IBM

IBM Power Systems @ SC17

IBM Power Systems

Intel @ SC17

Intel

Lenovo @ SC17

Lenovo

Mellanox Technologies @ SC17

Mellanox Technologies

Microsoft @ SC17

Microsoft

Penguin Computing @ SC17

Penguin Computing

Pure Storage @ SC17

Pure Storage

Supericro @ SC17

Supericro

Tyan @ SC17

Tyan

Univa @ SC17

Univa

Google Chases Quantum Supremacy with 72-Qubit Processor

March 7, 2018

Google pulled ahead of the pack this week in the race toward "quantum supremacy," with the introduction of a new 72-qubit quantum processor called Bristlecone. Read more…

By Tiffany Trader

CFO Steps down in Executive Shuffle at Supermicro

January 31, 2018

Supermicro yesterday announced senior management shuffling including prominent departures, the completion of an audit linked to its delayed Nasdaq filings, and Read more…

By John Russell

HPE Wins $57 Million DoD Supercomputing Contract

February 20, 2018

Hewlett Packard Enterprise (HPE) today revealed details of its massive $57 million HPC contract with the U.S. Department of Defense (DoD). The deal calls for HP Read more…

By Tiffany Trader

Deep Learning Portends ‘Sea Change’ for Oil and Gas Sector

February 1, 2018

The billowing compute and data demands that spurred the oil and gas industry to be the largest commercial users of high-performance computing are now propelling Read more…

By Tiffany Trader

Nvidia Ups Hardware Game with 16-GPU DGX-2 Server and 18-Port NVSwitch

March 27, 2018

Nvidia unveiled a raft of new products from its annual technology conference in San Jose today, and despite not offering up a new chip architecture, there were still a few surprises in store for HPC hardware aficionados. Read more…

By Tiffany Trader

Hennessy & Patterson: A New Golden Age for Computer Architecture

April 17, 2018

On Monday June 4, 2018, 2017 A.M. Turing Award Winners John L. Hennessy and David A. Patterson will deliver the Turing Lecture at the 45th International Sympo Read more…

By Staff

Part One: Deep Dive into 2018 Trends in Life Sciences HPC

March 1, 2018

Life sciences is an interesting lens through which to see HPC. It is perhaps not an obvious choice, given life sciences’ relative newness as a heavy user of H Read more…

By John Russell

Google I/O 2018: AI Everywhere; TPU 3.0 Delivers 100+ Petaflops but Requires Liquid Cooling

May 9, 2018

All things AI dominated discussion at yesterday’s opening of Google’s I/O 2018 developers meeting covering much of Google's near-term product roadmap. The e Read more…

By John Russell

  • arrow
  • Click Here for More Headlines
  • arrow
Share This