UberCloud Marketplace for HPC as a Service Goes Live

By Wolfgang Gentzsch and Burak Yenier

January 29, 2014

UberCloud is the online community and marketplace where engineers and scientists can discover, try and buy the computing power and expertise on demand they need for their computational and data-intensive tasks.

With the limits of their desktop workstations often unable to provide enough computing power and memory, simulations taking too long, and the number of jobs too small to get quality results, engineers and scientists are looking for additional computing power beyond their desktop workstations. The UberCloud Marketplace provides access to a wide variety of computing providers, software vendors, enabling tools, and independent experts to simplify and ease the search for the most suitable service providers and expertise, out of hundreds that joined UberCloud in the last 18 months.

The process is simple. End-users register at the UberCloud website and complete a form to “Request a Quote from Resource Providers”. They provide information about their application, software and licenses, network interconnect, main memory per node, number of parallel cores, total CPU usage, MIC/GPUs needed, storage, remote visualization, and instructions about timing, urgency, and location of resources. And they can ask any question via UberCloud’s LiveChat feature. Then, the UberCloud takes care of the reset: automatically searching for suitable resource providers; collecting up to three quotes and sending them to the end-user; then the end-user is free to contact any or all of them to discuss the details. That’s it.

UberCloud Marketplace Video

About the UberCloud

Successful companies use high performance computing to build better products, faster, cheaper. They have the options to use desktop workstation, HPC cluster, and cloud computing resources. For organizations looking for ways to speed up their product design and development cycles, or increase productivity of their engineers and researchers, the UberCloud helps to understand how they can access high performance computers at professional data centers.

The UberCloud started in July 2012 with the free voluntary HPC Experiment which today has over 1000 participating organizations and individuals, from 68 countries. We believe that on demand access to remote computing resources (like HPC Clouds) will become an indispensable part of the engineers and scientists R&D work in the near future, for organization in HPC, computational fluid dynamics, finite element material analysis, multi-physics, chemistry, life sciences, biology, big data, and others.

To explore the challenges of the end-to-end process for an end-user to access and use remote computing resources, we are building “Teams of Four”, i.e. industry end-user, software provider, resource provider, and HPC expert, to work together on the end-user’s application, defining the requirements, getting the licenses and implementing the software on the remote system, running and monitoring it, getting the results back to the end-user, and writing a short case study about their experience, lessons learned, and recommendations, for the benefit of our community. So far, we were able to build 125 international teams and published the UberCloud Compendium with the 25 best case studies about CAE in the Cloud, sponsored by Intel. We invite everybody to join the UberCloud HPC Experiment.

In addition, the UberCloud offers a services directory, case study discussion forums, technology and services webinars, a monthly newsletter, and other detailed information, to discover how to utilize HPC as a Service. And finally, for those who are ready to use HPC as a Service in production, the UberCloud now offers the public marketplace for engineers, scientists, and their service providers.

Why Do We Need an HPC Marketplace?

The benefits of using HPC within design and development processes can be huge; such as better quality products; high Return on Investment (ROI); reducing product failure early in design; and shorten time to market. Potentially, this leads to increased competitiveness and innovation. Why then are many engineers and scientists running simulations just on their workstations, although many are regularly dissatisfied with the performance? The main reason is that the other alternatives are still coming with a lot of challenges.

The first alternative of buying an HPC server comes with high Total Cost of Ownership (TCO) as has been demonstrated by IDC already in 2007: in addition to server cost, expenses for staffing, training, software, downtime, and maintenance easily sum up to the ten-fold of the server cost over three years. Also, there are often long and painful internal procurement and approval processes. And for many, the ROI is not clear, although it is expected to be huge according to a recent IDC study on ROI in HPC.

The second alternative is recently offered by cloud computing. HPC in the Cloud (or HPC as a Service) allows engineers and scientists to continue using their own desktop system for daily design and development, and to submit (burst) the larger, more complex, time-consuming jobs into the cloud. Benefits of HPC Cloud (in addition to HPC in general) are among others on-demand access to ‘infinite’ resources, pay per use, reduced capital expenditure (CAPEX), greater business agility, and dynamically scaling resources up and down as needed.

However, HPC as a Service (in the Cloud) comes with challenges too: it is a new business and working paradigm, for the manager as well as for the engineer; security, privacy, and trust in service providers is an issue; conservative software licensing is only slowly including the pay-per-use service model; Internet bandwidth is often not able to accommodate the heavy data transfer needs; unpredictable costs of cloud computing can be a major problem in securing a budget for a given project; and there is often a lack of easy, intuitive self-service access and use of cloud resources.

And here comes the UberCloud community and marketplace which provides a platform for engineers and researchers to discover, explore, and understand the end-to-end process of accessing and using HPC Cloud resources, and to identify and resolve the roadblocks as described above. After recognizing the strategic benefits and implications for their business, end-users then can buy HPC as a Service, on demand. The marketplace assures best matching of resources from the many participating providers with the end-user’s requirements, and then offering a selection of suitable resource providers to the end-user.

Final UberCloud Marketplace figure1

Fig. 1 – The image on the right shows the temperature field of the room, while the left image shows the velocity field at a certain time of the transient simulation.

UberCloud Case Study: Fluid Dynamics Simulation with Heat Transfer in the Cloud

In many engineering problems fluid dynamics is coupled with heat transfer and many other multiphysics scenarios. The simulation produces large numerical models to be solved, so that big computational power is required in order for simulation cycles to be affordable. For SME companies in particular it is hard to implement this kind of technology in-house, because of its high investment cost and the IT specialization needed.

Biscarri Consultoria in Spain decided to explore the capabilities of cloud computing for performing highly coupled computational mechanics simulations, as an alternative to the acquisition of new computing servers to increase the computing power available. UberCloud Team 30 consisted of members Lluís M. Biscarri and Pierre Lafortune from Biscarri Consultoria in Spain, Wibke Sudholt and Nicola Fantini from CloudBroker GmbH in Switzerland, Joël Cugnoni, researcher and developer of CAELinux, and Peter Råback from CSC in Finland. CloudBroker used Amazon’s IaaS cloud offerings EC2 for compute and S3 for storage resources for this experiment.

The validation case was a room with a cold air inlet on the roof, a warm section on the floor and an outlet on a lateral wall near the floor. The initial air temperature was 25ºC. The submission of jobs to be run at AWS was done through the web interface of the CloudBroker Platform. The team’s case study reports quite some challenges which had to be overcome before the jobs ran smoothly on AWS, details are described in the UberCloud Compendium. Simulation results are shown in Figures 1 and 2.

Final UberCloud Marketplace figure2

Fig. 2 – Streamline on the inlet section.

“The main lesson learned at Biscarri Consultoria arising from participation in the UberCloud Experiment is that collaborative work over the Internet, using on-line resources like cloud computing hardware, Open Source software such as Elmer and CAElinux, and middleware platforms like CloudBroker, is a very interesting alternative to in-house calculation servers,” said Lluís Biscarri, Director at Biscarri Consultoria SL. “A backbone network such as 10Gbit Ethernet connecting computational nodes of a cloud computing platform seems not to be suitable for computational mechanics calculations that need to be run on more than one large AWS Cluster Compute node in parallel. Infiniband is necessary when running in parallel on more than one AWS Cluster Compute instance with 16 cores, to reduce latency and increase bandwidth.”

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!

ExxonMobil, NCSA, Cray Scale Reservoir Simulation to 700,000+ Processors

February 17, 2017

In a scaling breakthrough for oil and gas discovery, ExxonMobil geoscientists report they have harnessed the power of 717,000 processors – the equivalent of 22,000 32-processor computers – to run complex oil and gas reservoir simulation models. Read more…

By Doug Black

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

Drug Developers Use Google Cloud HPC in the Fight Against ALS

February 16, 2017

Within the haystack of a lethal disease such as ALS (amyotrophic lateral sclerosis / Lou Gehrig’s Disease) there exists, somewhere, the needle that will pierce this therapy-resistant affliction. Read more…

By Doug Black

HPE Extreme Performance Solutions

Object Storage is the Ideal Storage Method for CME Companies

The communications, media, and entertainment (CME) sector is experiencing a massive paradigm shift driven by rising data volumes and the demand for high-performance data analytics. Read more…

Weekly Twitter Roundup (Feb. 16, 2017)

February 16, 2017

Here at HPCwire, we aim to keep the HPC community apprised of the most relevant and interesting news items that get tweeted throughout the week. Read more…

By Thomas Ayres

Alexander Named Dep. Dir. of Brookhaven Computational Initiative

February 15, 2017

Francis Alexander, a physicist with extensive management and leadership experience in computational science research, has been named Deputy Director of the Computational Science Initiative at the U.S. Read more…

Here’s What a Neural Net Looks Like On the Inside

February 15, 2017

Ever wonder what the inside of a machine learning model looks like? Today Graphcore released fascinating images that show how the computational graph concept maps to a new graph processor and graph programming framework it’s creating. Read more…

By Alex Woodie

Azure Edges AWS in Linpack Benchmark Study

February 15, 2017

The “when will clouds be ready for HPC” question has ebbed and flowed for years. Read more…

By John Russell

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

Drug Developers Use Google Cloud HPC in the Fight Against ALS

February 16, 2017

Within the haystack of a lethal disease such as ALS (amyotrophic lateral sclerosis / Lou Gehrig’s Disease) there exists, somewhere, the needle that will pierce this therapy-resistant affliction. Read more…

By Doug Black

Azure Edges AWS in Linpack Benchmark Study

February 15, 2017

The “when will clouds be ready for HPC” question has ebbed and flowed for years. Read more…

By John Russell

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling was pretty much the exclusive realm of the Cray-2 and IBM mainframe class products. That’s changing. We are now seeing an emergence of x86 class server products with exotic plumbing technology ranging from Direct-to-Chip to servers and storage completely immersed in a dielectric fluid. Read more…

By Steve Campbell

Cray Posts Best-Ever Quarter, Visibility Still Limited

February 10, 2017

On its Wednesday earnings call, Cray announced the largest revenue quarter in the company’s history and the second-highest revenue year. Read more…

By Tiffany Trader

HPC Cloud Startup Launches ‘App Store’ for HPC Workflows

February 9, 2017

“Civilization advances by extending the number of important operations which we can perform without thinking about them,” Read more…

By Tiffany Trader

Intel and Trump Announce $7B for Fab 42 Targeting 7nm

February 8, 2017

In what may be an attempt by President Trump to reset his turbulent relationship with the high tech industry, he and Intel CEO Brian Krzanich today announced plans to invest more than $7 billion to complete Fab 42. Read more…

By John Russell

For IBM/OpenPOWER: Success in 2017 = (Volume) Sales

January 11, 2017

To a large degree IBM and the OpenPOWER Foundation have done what they said they would – assembling a substantial and growing ecosystem and bringing Power-based products to market, all in about three years. Read more…

By John Russell

US, China Vie for Supercomputing Supremacy

November 14, 2016

The 48th edition of the TOP500 list is fresh off the presses and while there is no new number one system, as previously teased by China, there are a number of notable entrants from the US and around the world and significant trends to report on. Read more…

By Tiffany Trader

Lighting up Aurora: Behind the Scenes at the Creation of the DOE’s Upcoming 200 Petaflops Supercomputer

December 1, 2016

In April 2015, U.S. Department of Energy Undersecretary Franklin Orr announced that Intel would be the prime contractor for Aurora: Read more…

By Jan Rowell

D-Wave SC16 Update: What’s Bo Ewald Saying These Days

November 18, 2016

Tucked in a back section of the SC16 exhibit hall, quantum computing pioneer D-Wave has been talking up its new 2000-qubit processor announced in September. Forget for a moment the criticism sometimes aimed at D-Wave. This small Canadian company has sold several machines including, for example, ones to Lockheed and NASA, and has worked with Google on mapping machine learning problems to quantum computing. In July Los Alamos National Laboratory took possession of a 1000-quibit D-Wave 2X system that LANL ordered a year ago around the time of SC15. Read more…

By John Russell

Enlisting Deep Learning in the War on Cancer

December 7, 2016

Sometime in Q2 2017 the first ‘results’ of the Joint Design of Advanced Computing Solutions for Cancer (JDACS4C) will become publicly available according to Rick Stevens. He leads one of three JDACS4C pilot projects pressing deep learning (DL) into service in the War on Cancer. Read more…

By John Russell

HPC Startup Advances Auto-Parallelization’s Promise

January 23, 2017

The shift from single core to multicore hardware has made finding parallelism in codes more important than ever, but that hasn’t made the task of parallel programming any easier. Read more…

By Tiffany Trader

IBM Wants to be “Red Hat” of Deep Learning

January 26, 2017

IBM today announced the addition of TensorFlow and Chainer deep learning frameworks to its PowerAI suite of deep learning tools, which already includes popular offerings such as Caffe, Theano, and Torch. Read more…

By John Russell

CPU Benchmarking: Haswell Versus POWER8

June 2, 2015

With OpenPOWER activity ramping up and IBM’s prominent role in the upcoming DOE machines Summit and Sierra, it’s a good time to look at how the IBM POWER CPU stacks up against the x86 Xeon Haswell CPU from Intel. Read more…

By Tiffany Trader

Leading Solution Providers

Nvidia Sees Bright Future for AI Supercomputing

November 23, 2016

Graphics chipmaker Nvidia made a strong showing at SC16 in Salt Lake City last week. Read more…

By Tiffany Trader

BioTeam’s Berman Charts 2017 HPC Trends in Life Sciences

January 4, 2017

Twenty years ago high performance computing was nearly absent from life sciences. Today it’s used throughout life sciences and biomedical research. Genomics and the data deluge from modern lab instruments are the main drivers, but so is the longer-term desire to perform predictive simulation in support of Precision Medicine (PM). There’s even a specialized life sciences supercomputer, ‘Anton’ from D.E. Shaw Research, and the Pittsburgh Supercomputing Center is standing up its second Anton 2 and actively soliciting project proposals. There’s a lot going on. Read more…

By John Russell

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

Dell Knights Landing Machine Sets New STAC Records

November 2, 2016

The Securities Technology Analysis Center, commonly known as STAC, has released a new report characterizing the performance of the Knight Landing-based Dell PowerEdge C6320p server on the STAC-A2 benchmarking suite, widely used by the financial services industry to test and evaluate computing platforms. The Dell machine has set new records for both the baseline Greeks benchmark and the large Greeks benchmark. Read more…

By Tiffany Trader

IDG to Be Bought by Chinese Investors; IDC to Spin Out HPC Group

January 19, 2017

US-based publishing and investment firm International Data Group, Inc. (IDG) will be acquired by a pair of Chinese investors, China Oceanwide Holdings Group Co., Ltd. Read more…

By Tiffany Trader

What Knights Landing Is Not

June 18, 2016

As we get ready to launch the newest member of the Intel Xeon Phi family, code named Knights Landing, it is natural that there be some questions and potentially some confusion. Read more…

By James Reinders, Intel

KNUPATH Hermosa-based Commercial Boards Expected in Q1 2017

December 15, 2016

Last June tech start-up KnuEdge emerged from stealth mode to begin spreading the word about its new processor and fabric technology that’s been roughly a decade in the making. Read more…

By John Russell

Intel and Trump Announce $7B for Fab 42 Targeting 7nm

February 8, 2017

In what may be an attempt by President Trump to reset his turbulent relationship with the high tech industry, he and Intel CEO Brian Krzanich today announced plans to invest more than $7 billion to complete Fab 42. Read more…

By John Russell

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