POV-Ray m.in.

DISTRIBUTED EXECUTION OF DYNAMICALLY
DEFINED TASKS ON MICROSOFT AZURE
Piotr Wiewiura1, Maciej Malawski1, and Monika Piwowar2
1 AGH University of Science and Technology, Department of Computer Science, Krakow, Poland
2 Jagiellonian University, Department of Bioinformatics and Telemedicine, Krakow, Poland
Background
Requirements for DTL
ExonVisualiser
Goals
 Distributed execution
 Visualization of protein regions encoded by particular exons

To evaluate suitability of Microsoft Azure as a platform
for execution of computational applications
 Install-and-forget worker service

To create a lightweight library to execute arbitrary
tasks with arbitrary data on Azure.
 Simplicity
 Allows “tracking” gene expression by identification parts of
the proteins being in relation with gene structure (codding
regions - exons).

To port existing ExonVisualizer application into Azure
 Dynamic deployment and execution
 Dynamic horizontal scaling
Windows Azure features

Virtual machines created on-demand

Blob Storage

Queue Services

Dynamic Horizontal Scalability
 Good tool for analysis proteins that are synthesized in the
alternative splicing and also in identification protein regions
created in the post-translational modifications process.
 Portability and independence from
execution platform
 Written in C#
 Support for Linux (Mono)
 Worker service auto-update
→
Result: Distributed Task Library (DTL)
Architecture of DTL
Implementation of DTL
 Microsoft Azure REST API
 Programming language and platform independence
(Mono requirement)
 Dynamic task definition
 Binaries sent with tasks. Rapid development, testing
and usage.
 Arbitrary data sources
 Byte streams, objects, files, storage services
Experiments with DTL on Azure
VM Instance creation times
POV-Ray Banchmark
ExonVisualizer
 Instantiating 1 to 20 Small Instance VMs
 Ray tracing 128x128 px benchmark scene.
 Large input size and fast execution
 First virtual machine is ready in about 235 s
and each next takes further 45 s
 Combination of 1-16 segments and workers
Conclusions
References

New Distributed Task Library (DTL)
implemented and tested


ExonVisualiser adapted to Azure using DTL
Malawski, M., Meizner, J., Bubak, M., Gepner, P.: Component
approach to computational applications on clouds. In: Proceedings of
the International Conference on Computational Science, ICCS 2011

Azure is a worthy platform for computational
applications

Piwowar, M., Porembski, K., Piwowar, P.: ExonVisualiser - application
for visualization exon unitsin 2D and 3D protein structures.
Bioinformation 8(25), 1280–2 (2012)
For additional information,
please contact:
Maciej Malawski
Department of Computer Science
AGH University of Science and
Technology
[email protected]