Half Time in the Uber-CloudStatus of the HPC Experiment and its 20 Application TeamsWolfgang Gentzsch and Burak YenierSinc...
Weathermen            Large-scale and high-resolution weather and climate prediction Wind Turbine          CFD simulations...
obtained from an auction-like marketplace offering deeply significant cost savings over traditional on-demand hourly price...
encouraged to use other resources, and existing participants can work in new teams.Please find more information and the re...
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Half time in the Uber-Cloud Experiment

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Since its first announcement in July 2012, the Uber-Cloud Experiment has attracted over 160 industry and research organizations and individuals from 22 countries. They all have one goal: to jointly explore the end-to-end process of remotely accessing technical computing resources sitting in HPC centers and in the cloud. The focus of this experiment is on engineering simulations performed by small and medium enterprises that expect a quantum leap in innovation and competitiveness by using high performance computing. The Half Time report shows the progress of the team with their experiment in HPC in the Cloud. Learn more at www.hpcexperiment.com

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Half time in the Uber-Cloud Experiment

  1. 1. Half Time in the Uber-CloudStatus of the HPC Experiment and its 20 Application TeamsWolfgang Gentzsch and Burak YenierSince its first announcement on June 28 here on HPCwire and its official start on July 20, the Uber-Cloud Experiment attracted over 160 industry and research organizations and individuals from 22countries who all have one goal: to jointly explore the end-to-end process of remotely accessingtechnical computing resources sitting in HPC Centers and in the Cloud. The focus of this experiment ison engineering simulations performed by small and medium enterprises that expect a quantum leap ininnovation and competitiveness by using HPC.While the benefits of remote access to HPC is widely recognized and that we have and master most ofthe technology needed to access and run our engineering workloads on remote resources, we still faceother challenges more related to us, the people, like for example, trusting the resource provider; givingaway control over our applications, data, and resources; security; provider lock-in; software licensing;unfamiliar pay-per-use computing; and a general lack of clarity in distinguishing between hype andreality. To explore these hurdles in detail and to learn more about this end-to-end process, we were ableto build 20 teams, each consisting of an end-user and his/her application, the software provider, thecomputational resource provider, and an HPC and/or CAE expert who manages the team process. Thefollowing 20 teams have been set up: Team Project Description Anchor Bolt Simulating steel to concrete fastening capacity for an anchor bolt Resonance Electromagnetic simulations of NMR Probe heads Simulation of the radiofrequency field distribution inside Radiofrequency heterogeneous human body Supersonic Simulation of jet mixing in the supersonic flow with shock Liquid-Gas Two-phase flow simulation of separation columns Wing-Flow Flow around an aerospace wing Ship-Hull Simulation water flow around a hull of the ship Cement-Flows Burner simulation with different solid fuels in mining industry Sprinkler Simulating water flow through an irrigation water sprinkler Space Capsule Aerothermodynamics and stability analysis of a space capsule Car Acoustics Low frequency car acoustics Dosimetry Numerical EMC and Dosimetry with high-res models
  2. 2. Weathermen Large-scale and high-resolution weather and climate prediction Wind Turbine CFD simulations of vertical and horizontal wind turbines Combustion Simulating combustion in an IC engine Blood Flow Simulation of water/ blood flow inside rotating micro channels ChinaCFD CFD using homegrown C/C++ application Gas Bubbles Simulation of gas bubbles in a liquid mixing vessel Side impact Optimization of the side-door intrusion bars under a crash ColombiaBio Analysis of the biological diversity in a geography using R scriptsIn the meantime, all 20 teams are underway, 2 of them are busy with defining their end-user project, 15teams are in contact with the assigned computing resources and setting up the project environment, 1working on initiating and monitoring the end-user project execution, 1 is reviewing the results with theend-user, and 1 is already documenting the findings of the HPC as a Service process. To illustrate theteam process in more detail, we present two teams and their current status in the following.Simulating new probe design for a medical deviceTeam Expert: Chris Dagdigian from BioTeamOur teams end-user is faced with a common problem: a periodic need for large compute capacity inorder to simulate and refine potential product changes and improvements. The periodic nature of theHPC requirements means that it is not possible to have the desired amount of capacity internally as thecompany finds it difficult to justify capital expenditure for complex assets that may end up sitting idlefor long periods of time. To date the company has invested in a modest amount of internal HPC capacitysufficient to meet base requirements. Additional HPC resources would allow the end user to greatlyexpand the sensitivity of current simulations and may enable new product & design initiatives previouslywritten off as "untestable".Our HPC software is CST Studio (www.cst.com), a popular commercial application for electromagneticsimulations of many types. We are currently operating in the Amazon cloud and have successfullycompleted a series of architecture refinements and scaling benchmarks. Our hybrid cloud-burstingarchitecture allows local HPC resources residing at the end-user site to be utilized along with ourAmazon cloud-based resources. At this point in the project we are still exploring the scaling limits ofthe Amazon GPU-equipped EC2 instance types and are beginning new tests and scaling runs designedto test HPC task distribution via MPI. The use of MPI will allow us to leverage different EC2 instancetype configurations and scale beyond some technical limits imposed by the amount of memory residingwithin the Nvidia GPU cards. We are currently at (or very nearly at) the point in which we are routinelyrunning simulations that would not be technically possible using the local-only resources of our end user.We also intend to begin testing use of the Amazon EC2 Spot Market in which cloud-based assets can be
  3. 3. obtained from an auction-like marketplace offering deeply significant cost savings over traditional on-demand hourly prices.Multiphase flows within the cement and mineral industryTeam Expert: Ingo Seipp from science + computing agIn this project ANSYS CFX is used to simulate a flash dryer in which hot gas is used to evaporate waterfrom a solid. The team consists of FLSmidth as the end user, Bull as the resource provider with itsextreme factory (XF) HPC on demand service, ANSYS as the software provider and science + computingag as team experts.FLSmidth is the leading supplier of complete plants, equipment and services to the global minerals andcement industries. The end user needs about 4 to 5 days to complete a simulation run on the local ITinfrastructure. He would like to reduce the total throughput time of the project and, in a second step,increase the mesh size to refine the results, without investing in hardware, which may not always beutilized full-time. For this, the simulation must be run on more cores and more memory through morenodes connected by a high-speed network.XF provides 150 Tflops of computing power with Infiniband, GPUs and currently about 30 installedapplications. Others are added on demand. Users can access XF through an easy-to-use web-portal ordirect logon.In this project XF has enabled access to the end user and integrated ANSYS CFX in a web-interface forsubmitting jobs for the end user. For the course of this project licenses have been granted by ANSYS. Theend user can manage his ANSYS licenses easily through the portal.The preparations to run the jobs are almost completed now and the first test runs should be able to startshortly.We’d like to deeply thank our participants from Amazon AWS, BULL extreme factory, ANSYS, BioTeam,science + computing ag, and our industry end-users working in these two teams.Announcing Round 2 of the Uber-Cloud ExperimentWe consider Round 1 as proof of the concept that: YES, remote access to HPC resources works, and,there is a real need! YES, there are hurdles on the way, but we know how to overcome them.During the Halftime webinar we asked the attendees: Would you participate in an Uber-CloudExperiment Round 2? 97% answered with “Yes”. Therefore, we decided to start a new round of theUber-Cloud Experiment right after the end of the current round, running from mid-November to mid-February.Round 2 of the experiment will be more professional; the end-to-end process of identifying, accessingand using remote resources (hardware, software, expertise) will become more structured, standardized,and tools-based; we will handle more teams and more applications beyond CAE, and offer a list ofadditional professional services, for e.g. measuring the overall team effort. Existing teams will be
  4. 4. encouraged to use other resources, and existing participants can work in new teams.Please find more information and the registration for Round 2 on the Uber-Cloud Experiment website.

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