This document describes The UberCloud, an open collaborative community experiment aimed at making high performance computing (HPC) as a service available to everyone on demand. The experiment helps engineering teams explore using remote computing resources through a guided 22 step process. Over 700 organizations from 66 countries have participated in rounds of the experiment. The document outlines benefits of the experiment for end users and how the process works. It also highlights challenges of HPC as a service and potential solutions identified through case studies of engineering teams that have participated. The ultimate goal is a marketplace to connect computing service providers with engineers and scientists seeking HPC resources.

1. The UberCloud
Paving the way to
High Performance Computing as a Service
International Conference on Utility and Cloud Computing
December 9 – 12, Dresden, Germany
Wolfgang Gentzsch and Burak Yenier

2. What is High Performance Computing ?
Modeling the World on the computer …
t   U      U  U   0
F  ma
i t   H 
E  mc 2
… in order to allow for Virtual Product Development …
2

3. What is High Performance Computing ?
… or for scientific insights
Combustion
Environment
Cosmology
Climate
3

4. HPC is needed to stay competitive
The digital manufacturing engineer has
several options to use High Performance
Computing (HPC):
 HPC on the Desktop: over 90% of engineers
 HPC on the Server: about 5% of engineers
 HPC as a Service: in the Cloud; less than 1%

5. Workstations: limited capacity
Low-end workstations and PCs are important for
daily design and development work, but
 50+ % of users are dissatisfied with their computing
capacity*
 Too slow, e.g. jobs run over night or a whole week
 Too small, detailed geometry and physics don’t fit into
memory
 Number of jobs are limited which affects the quality of
the final result
*
Source: http://www.compete.org/

6. Servers: expensive and complex
 For SMEs buying and using large scale HPC systems is
expensive and complex …

7. HPC as a Service: benefits & challenges
HPC as a Service (in the Cloud) offers flexibility, business
agility, scaling up and down, pay-per-use, OPEX instead
CAPEX, but
 It’s a new business and working paradigm
 Security, privacy, trust in service provider
 Intellectual property
 Software Licensing
 Heavy data transfers

8. UberCloud Poll about Roadblocks
The UberCloud, June 13, 2013

9. The UberCloud HPC Experiment
An open voluntary collaborative community
Objective:
Making HPC as a Service available, for everybody, on demand
How?
For SMEs and their engineering applications
to explore the end-to-end process
of using remote computing resources,
as a service, on demand, at your finger tip,
and learning how to resolve the roadblocks.

10. The End-User’s Benefits
 Free HPC Experiment, on-demand access to hardware, software,
and expertise, with a one stop resource access experience
 No hunting for resources in the complex emerging cloud market
 Professional match-making of end-users with service providers
 Perfectly tuned end-to-end, step-by-step process to HPC Cloud
 Lowering barriers & risks for frictionless entry into HPC Cloud
 Crowd sourcing: End-Users are building relationships with other
community members who actively contribute to improvements

11. How does the Experiment work?
 End-User joins the experiment
 Software Vendor joins
 We select a Team Expert
 We suggest a Resource Provider
 Team is ready to go
 … 22 steps on Basecamp’s virtual team office
 Finally, writing the Case Study

12. Where are we with the experiment
 Started August 2012: today 700+ participating organizations
and individuals
 Participants are from 66 countries
 Round 4 started September 1: already 42 new teams
 124 teams have been formed in Rounds 1-4
 Registration at:
www.hpcexperiment.com
www.cfdexperiment.com
www.compbioexperiment.com
www.bigdataexperiment.com

13. UberCloud community website
 With social network and crowdsourcing features
 Forums, Q&A, discussions, newsletters,…
 Feature stories: HPCwire, Desktop Engineering, Bio-IT…
 UberCloud University with free and paid lectures
 UberCloud HPC Experiment free trial service
 UberCloud Exhibit services directory
 List of currently ongoing team projects, their status, and
organizations involved
 List of upcoming conferences with ‘meet me there’ button

16. Finally: The UberCloud Marketplace
 Crowdsourcing and social networking: provide the
community web platform to discover and try HPCaaS,
address pain points, facilitate adoption, harness collective
intelligence
 Marketplace for computing-related services: 20+ million
engineers, scientists, and their service providers to list,
discover, try, and sell/purchase
 IaaS: HPC centers and public cloud providers
 SaaS: open source and commercial technical software
 Expertise: specialized HPC, software, technical know-how

17. Cloud Computing Reality Check
 UberCloud Compendium
sponsored by Intel
 25 selected use-cases from
60 teams in Rounds 1 & 2
 Google:
“ubercloud compendium”
17

18. Team 2: Simulating new probe design
for a medical device
Front End + 2 GPU Solvers In Action

19. Team 2: Team members
HPC Expert:
Electromagnetic Simulation
End User: Anonymous

20. Team 8: Multiphase flows within the
cement and mineral industry
Drying moist particles with hot gas

21. Team 8: Team members
Ingo Seipp
and Team
End-User
CFX

22. Team 26: Simulating Stent
Deployment
Using SIMULIA’s Abaqus/Standard and Remote Viz
Software from NICE to run CAE on SGI Cyclone™
 Assessment of a fictitious balloon expandable stent design
 deployment, physiological pulsatile loading
 and both axial and radial compression.

23. Team 26- Team members
 End User: Anonymous: Global Designer and Manufacturer of Sterile
Medical Products
 CAE Software Provider: Matt Dunbar, Chief Architect, SIMULIA
 Remote Viz Software: NICE Desktop Cloud Visualization (DCV)
 HPC/CAE Expert: Scott Shaw, Senior Applications Engineer, SGI
 Resource Provider: SGI Cyclone. Tony DeVarco, Senior Manager for
Strategic Partners and Cloud Computing at SGI. Eugene Kremenetsky,
Systems Engineering Technical Lead at SGI
 Team Mentor: Gregory Shirin from the HPC Experiment team

24. Challenges and Solutions
 Information security, privacy: protecting the users intellectual
property, guarding raw data, processing models, resulting
information: document security requirements, and select the
right provider
 Internet too slow for heavy data transfer: don’t ship every
result, just the important ones; use remote visualization; if
necessary, fedex the data over-night via USB hard drive
 Incompatible software licensing models: ISVs have to develop
compatible on-demand software licensing models

25. Challenges and Solutions, cont’d
 Reliability & availability of resource providers: seeking info on
reliability and availability of each vendor before partnering
 Lack of easy registration and administration: originally HPC
resources are not designed for the masses: use automated rules
based instant decision making capabilities
 Costs: pay-per-use billing can result in unpredictable cost,
project can easily run out of budget: use automated, policy
driven monitoring of usage and billing
 High expectations, disappointing results: we are in transition
to the cloud computing paradigm: Set goals that are
incrementally better than your current capabilities.

26. Why join?
 HPC as a Service is the next big thing, benefits are obvious
 HPC is complex; together it is easier to tackle the complexity
 Low entry barrier to HPC as a Service through an experiment
 Learning by doing; experimenting with no risk; no failure
 Becoming an active part of this growing community
 Exploring the end-to-end process and learning how this fits
into your research and/or business direction in the near future

27. Thank You
http://www.hpcexperiment.com
http://www.cfdexperiment.com
http://www.compbioexperiment.com
http://www.bigdataexperiment.com