User Scenarios in VENUS-C Focus on Structural Analysis Ignacio Blanquer I3M - UPV

Seven scenarios Structural Analsys Building Inf. Manag. Biodiversity Aquamaps Fire Risk Propagat. Bioinform. System Biology Drug Discovery

COMPUTATIONAL RESOURCES MADE AVAILABE IN A DESKTOP Why cloud computing?

Accessing Computing: Alignment of Metagenomes Goal: Analyzing the sequences of a metagenome with BLAST. Settings – Input file: Sargasso’s Sea metagenome: 800 MB. – Reference: NR GenBank (prokaryotes): 1,3 GB. – Algorithm: blastx. – e-Value: 0,01 – Sequential estimated time: 1,3 CPU years. – Response time (50 x Azure): 12,8 days Azure cores Days Total CPU time Supercomputer Azure Azure cores Response time Days Supercomputer Azure 50 Tirant nodes

ENHANCING THE DEVELOPMENT AND DEPLOYMENT OF SOFTWARE AS A SERVICE FOR RESEARCH Why VENUS-C?

Assisting SaaS Development Programming Models – Bag of Jobs. – Map / Reduce. – Data Flows. – Elasticity. Data Objects – Binary Files. – Message Queues. Security framework – Security and Accounting. E-Science Application Wrapper Cloud A SDK Cloud B SDK CDMI Service Cloud Storage A User Code Cloud A SDK Cloud Storage B CDMI Library

User Scenario Case #1 Simulation of Building Structures Structural analysis: – Process to determine the response of a structure to different external loads or actions (such as earthquakes). – This response is usually measured by establishing displacements and tensions at any point of the structural elements. – Uses Architrave as tool on the Cloud ( Developed by DMMCTE & GRyCAP from the UPV.

Use Case The user draws the structure model and define the structural properties. Then the model is loaded in a GUI Application where the user can see the results of the simulation – The response of the structure is simulated by using Finite Elements. The user can modify the structure properties and repeat the simulation – Until a trade-off between construction costs and building safety is achieved.

Expected benefits of VENUS-C Traditional approach: – To analyse the structure with high simulation times. – To simplify the problem. Reduced accuracy and the reliability of the results. – To limit the size of the structures. – To reduce the number of structural solutions to be analysed. – To increase the quantity of employed constructive materials and the final cost of the building. Potential benefits: – To reduce the time involved in the structural analysis. – To tackle in a realistic way large- scale structural problems, providing highly reliable results. – To analyze complex structural systems under static and dynamic loads. – To simulate concurrently a large number of different structural solutions reducing the time and cost for designing building and civil engineering structures and increasing the results reliability.

Requirements to be fulfilled by VENUS-C component Execution – Data-driven Bag of Jobs. – Support for Multi-core jobs. – Elasticity Management. – Execution Status (Pull) / Notification (Push). Data Objects – Binary Files and Message Queues. Security – Data Ownership. – User Login Authorisation, Logging andAccounting.

Web Services provided – Two Web Services has been implemented: One for client application and another for administration. – Accessible directly from the Architrave GUI or through a web client.

Use Case Building structural analysis: 1.User sends binary files: Building structure (AVE) + Simulation (one or more) parameters. 2.The Data Manager stores the data into the Blob Storage. 3.The Accounting Manager writes the appropriate information in the database. 4.The Service Manager adds the tasks into the Task Queue (1 task per earthquake). 5.The Elasticity Manager checks rules. 6.A Structural Analysis Worker executes the simulation, and stores the results on the Blob Storage. 1.Worker notifies its progress writing into the Response Queue. 7.The user will periodically invoke the method to retrieve the results. 8.The Accounting Manager will log the simulations executed by the user, the amount of data generated, the resources consumed, etc.

Conclusions Cloud Computing is perceived as an enabling technology opening the access to computing resources for end-users who cannot access them. It can also provide a seamlessly transition from local, small-scale resources to remote, large-scale ones. VENUS-C provides a platform to ease the use of cloud programming models and data objects.