2. RISING DEMAND FOR
HIGH COMPUTATIONAL POWER
Simulations
Analysis of large data from optical telescopes
Gene sequencers
Gravitational wave detectors
Edge-detection for high resolution medical
image sequences
Biology-inspired algorithms
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3. HOW TO ADDRESS?
Supercomputing
Distributed Computing
Cluster Computing
Grid/Desktop-Grid Computing
Volunteer Computing
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4. EXISTING VOLUNTEER
COMPUTING FRAMEWORKS
Client Server Architecture
Server bottleneck
Single point of failure
Complexity of Configuring
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5. INTRODUCING SIYAPATH
P2P Architecture
Absence of server bottleneck
Absence of single point of failure
Gossip Protocols
Scalability
Robustness
Reliability
Simplicity in Configuring
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6. FEATURES
Job Submission
Job Scheduling User Job Processor
Task Distribution
Task Processing
Result Validation
Result Delivery
Task Task Task
Fault Tolerance Processor Processor Processor
Security
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7. DEMONSTRATION
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8. PERFORMANCE TESTING
Test 1 2 3 4 5
Users 5 10 15 20 25
Volunteers 30 30 30 30 30
Avg. Response Time (s) 52.16 89.63 136.29 211.02 249.25
Avg. Throughput (Tasks per 126.76 136.45 130.03 109.49 125.96
minute)
Average Response Time Average Throughput
300 160
250 140
120
Tasks per minute
Time (seconds)
200
100
150 80
100 60
40
50
20
0 0
1 2 3 4 5 1 2 3 4 5
8 Test
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Test
9. BEST PRACTICES
Version control system
Build Automation
Unit / Integrated testing
Logging
Continuous Integration
User friendly Website
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10. OPEN SOURCE COMPONENTS
Services Framework - Apache Thrift
Communication via a service interface
Addresses implementation details of the network
P2P nature using thrift client/server
System Monitoring – SIGAR
Apache Maven
Apache Log4j
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11. DOCUMENTATION
User manuals for the framework
User API Docs
Research publications
Project Website
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National Best Quality Software Awards, Sri Lanka - 2012
12. TEAM
Members:
Amila Manoj Silva
Nadeeshani Hewage
Mohamed Nufail
Malith Dhanushka
Supervisors:
Dr. Srinath Perera
Mrs. Vishakha Nanayakkara
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13. Questions?
Thank You!
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Notas del editor
Computational modeling - generate accurate models of the structures of crystalline and amorphous solidsClimate simulations model the past and future global climate with input from observational data and mathematical models. Advanced computational techniques and computer capabilities allow researchers to increase the resolution and refine the grids for climate simulations that enable better regional and global predictions.Bio-inspired algorithms such as genetic and evolutionary algorithms, ant colonies, and immune systems are routinely applied to hard and large problems in a variety of areas. Some examples are optimization through genetic algorithms, new ideas for developing routing algorithms in wireless networks inspired by honey bee behaviour, resource discovery and data mining computations in Grid and P2P frameworks achieved by ant-inspired algorithms, and so on.
Computational power volunteered by general publicLarge resource poolself-financing / self-maintainingVolunteer Computing FrameworksExisting frameworksBOINCBayanihanJADIF
Task scheduling/distribution > interface – priority, securityTask processing > iface – any kind of task, different tasks