VENUS-C is the first European distributed computing infrastructure to adopt a User-centric approach to Cloud Computing, putting the needs of end-User communities of researchers and small businesses at the forefront of development.

1. Project Overview
and perspectives
Andrea Manieri
Engineering Ingegneria Informatica SpA
Former VENUS-C Project Director
www.venus-c.eu

2. What scientists want
VENUS-C API
Account. Azure
CDMI PMES- PMES-
And Account.
Proxy COMPSs GW
Billing Connect.
VMs Interop.
Repo Toolkit
EMOTIVE ONE
Account. Account.
Connect. Connect.
TRE.
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3. User Community in VENUS-C
>=5
3-4
1-2
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4. Open Call Mgmt
• 60 proposals received
• 2 parallel evaluations
• 15 selected as pilots
• 5 more experiments
• 15 contracts subject to Italian Laws
• Monitoring of activities
– 7 internal monthly progress reports
– Monitoring Effort consumption
– Four deliverables per pilot
– Final Demo (available from web portal)
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5. Conceptual Architecture
Accounting, Billing and Monitoring
Cloud
Infrastructure
Management
Client app / Portal
Programming
Job Management
Model
Researcher
SDK
Enactment
Execution Environment
Data Traffic Cloud Data
Management Redundancy Management
SDK Elimination Interface
Storage
Local Services
Storage
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6. Venus-C API and
Component Interaction
Accounting, Billing and Monitoring
Accounting Accounting
Usage Tracker Connector Storage
Portal
Service
Application Code
VENUS-C Services & SDKs
Cloud OGF
Infrastructure RUS/UR
OGF Management
BES /JSDL
Client app / Portal OCCI
Sec. Scaling Programming
Job Management Sec. Notification Model
Researcher
SDK
Sec. Job Mngt. Enactment HD
Data Cloud Data
Management TRE Management
SDK Interface Execution Environment
SNIA CDMI Storage
Local Services
Storage
SOAP WS–*
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7. Platform Release
• Rapid release cycles:
– Incremental releases (V1.0 V1.5, V2.0)
– Central public download site: http://resources.venus-c.eu
– Feedback infrastructure http://venuscfeedback.codeplex.com
• Common Open Source license (Apache 2.0)
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8. Usage of the subsystems:
Different Execution Models
• High-Throughput Computing through
individual jobs executed by multiple Processing
users or Parameter Sweep. splitter Processing reducer Cloud-side
• Data flow, through the execution of Processing
jobs that have different stages
(communicated by files), which may
have different concurrency level. Worker Processin
• Coordination of jobs expressed as for g Workers
Accounting
Accounting
fine-grain workflows orchestrated Enactor
service
service Staging and Scaling
by an enactor. up / down resources
Submission
Submission
services
when needed, job
Client-side services
GW / grouping.
GW /
Stand-alone client
Stand-alone client COMPSs
COMPSs
or ASP
or ASP
CDMI Cloud
Local Data Mgnt
Data Mgnt Storage
Storage CDMI Client
CDMI Client Synchronization Service
Agnostic of jobs
Interface to
8 data.

9. Execution Models
T5.4 Civil T5.1 Structural
Protection and Analysis for Civil
Emergencies Engineering
T5.2 Building T5.5 Bioinformatics
Information
Management
T5.3 Data for T5.7 Drug
Science – Discovery
AquaMaps
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10. Success of the user
community
• The 7 scenarios will be demonstrated during the review.
• A VENUS-C pilots showcase event
celebrated in Pisa 27 June.
• 15 prototypes addressing new
requirements
– Matlab front-end1, Use of “R”,
Customised VMs2 and integration of
desktop computing3.
– 6 deployed in Linux, 8 in Azure and 1 in both.
• Many interesting examples of how Clouds
and VENUS-C help them solve their
problems.
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11. Earthquake Propagation
Simulation Portal
• Developed by the
Aristotle University of
Thessaloniki.
• When an earthquake
happens, it can be
used to simulate the
propagation of seismic
waves and its impact.
• Automatically it captures
the data from the seismic
registers offering in
nearly real-time, information about the areas affected.
• It will be ineffective to have a cluster of 100 nodes
dedicated for the processing of events that occur rarely.
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12. Virtual Docking in a mixed
Volunteer and cloud computing
infrastructure
• One of the most computationally
intensive tasks in Drug Design is the
identification of ligands reacting against
specific targets.
• Hundreds of thousands of molecules in
different configurations must be tested.
• Virtual docking is feasible through
widely common tools such as Autodock.
• The University of Westminster, partner of EDGI,
had a tool developed for voluntary computing that
benefits from the elastic provisioning of cloud
resources from VENUS-C to guarantee throughput.
• In this case, 180K molecules were analysed in
VENUS-C with respect to the 38 family of the
manosidase, selecting 9 candidates.
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13. Cloud for Radiotheraphy planning
brings a new exploitation model
• Radiotherapy planning based in
Monte-Carlo methods is a highly
accurate model for the estimation
of the doses
– Especially in IMRT.
• Well-known problem in research,
already adapted to Grids and clusters.
– However, research resources cannot be
used for exploitation and daily practice in
hospital environments.
– Moreover, usage ratios makes the infrastructure costs for this
purpose unaffordable.
• By the use of VENUS-C, CESGA is validating the feasibility of
exploiting this result.
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14. Benefits from the VENUS-C
Platform
• Scenarios and pilots concur on: Reduced response time;
Increased problem size and Improved Business Opportunities
– Speed-ups of up to 94x with 100 cores.
– Data increase of up to 25x.
– Users are interested in two different offering models
• “free”, accessing a reduced pool of local resources.
• “subscribers only” accessing a larger amount of resources from public Clouds.
• Finally, 4 Pilots have found that Pilots
VENUS-C enabled them to open
new research lines Scen.
– Social trends analysis through
cloud computing.
– A repository of ICU vital signs for
studying early predictors.
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15. Conclusion
• Users carried out an in-depth evaluation of the VENUS-C Platform.
– More than 1.5 Million of CPU hours in total (more than 1.3 Billion SPecInt2k
hours in EGI terms), 30 TB of cumulative data stored and 80 TB of data transfers.
• Application developers give a good score to the subsystems released
in April (from 3.92 to 4.37)
– User requirements completeness, ease of applications adaptation and
interoperability got the higher marks.
• The cooperation among the user community, developers and
infrastructure providers were very fruitful.
• VENUS-C demonstrates that public cloud infrastructures (i.e.
Windows Azure) are practical for scientific research, and that the use
of VENUS-C subsystems improves user experience.
– Open-source, private infrastructures have also been tested, with similar
conclusions regarding user experience.
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16. Thanks!
• www.venus-c.eu
• Acknowledgment:
– Goetz Brasche, European Microsoft Innovation
Center,
– Ignacio Blanquer, Univ. Politecnica de Valencia
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