1 / 12

Looking at the Sky through Clouds

Looking at the Sky through Clouds. Mihai Lucian Cristea, on behalf of SCARI e team University of Amsterdam. TERENA CONFERENCE ‘10, Vilnius, 1 June 2010. Overview. eVLBI on the Grid: SCARIe Problems when running SCARIe on Grid Workflow management: WS-VLAM Experiments Conclusions.

audrey-campbell
Download Presentation

Looking at the Sky through Clouds

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Looking at the Sky through Clouds Mihai Lucian Cristea, on behalf of SCARIe team University of Amsterdam TERENA CONFERENCE ‘10, Vilnius, 1 June 2010

  2. Overview • eVLBI on the Grid: SCARIe • Problems when running SCARIe on Grid • Workflow management: WS-VLAM • Experiments • Conclusions

  3. eVLBI

  4. eVLBI on the Grid:SCARIe Telescopes Bring the data from telescopes: Current: 4x256MBps Mid-target: 16x1Gbps Future scenario: 32x4Gbps Correlator Input nodes Requirement: constant throughput Correlator nodes Output node Result Software Correlator Architecture Research and Implementation for e-VLBI

  5. Optimizing the SCARIe application on Grid Jitter due to network congestion Telescope NE Correlator Input node Jitter due to network overload at ingress 3 80% 95% 80% 80% 1 Correlator nodes 2 Output node

  6. Network as a service in Grid • Specific services to applications: • Only the App knows how to optimally use the resources • Solutions to meet the specific network demands: • Schedule network resources (e.g., parallelize the link usage, not only the CPU usage, tradeoffs link connectivity vs. energy budget) • Application controls the network resources

  7. Workflow management: WS-VLAM

  8. Workflow management: WS-VLAM

  9. IXDP28501Gbps Experiments: Testbed 10.1.0.x 100Mbps Switch 10.1.0.28 10.1.0.27 DAS1 DAS2 10.1.0.30 10.1.0.29 DAS3 DAS4 10.1.0.32 10.1.0.31 DAS5 DAS6 10.1.0.34 10.1.0.33 DAS7 DAS8 Network Broker 10.10.0.34 10.10.0.33 10.10.0.32 10.10.0.31 10.10.0.30 10.10.0.29 10.10.0.28 10.10.0.27

  10. IXDP28501Gbps Experiments 10.1.0.x 100Mbps Switch 10.1.0.28 W1 W2 W4 W3 R2 R3 R4 R1 10.1.0.27 DAS1 DAS2 A 10.1.0.30 10.1.0.29 DAS3 DAS4 B 10.1.0.32 10.1.0.31 DAS5 DAS6 C 10.1.0.34 10.1.0.33 DAS7 DAS8 D Network Broker 10.10.0.34 10.10.0.33 E 10.10.0.32 10.10.0.31 10.10.0.30 10.10.0.29 10.10.0.28 10.10.0.27

  11. Results Playback Demos: http://staff.science.uva.nl/~gvlam/wsvlam/demos/wsvlam-dynamic-bw.html http://staff.science.uva.nl/~gvlam/wsvlam/demos/wsvlam-vlc-demo.html

  12. Conclusions • Close interactions between applications and networks enables better usage of resources • We support it in Grids by enabling networks as a service • When network resources are not transparent to applications, the interfaces between sensors, networks, and computational resources in the Grid can be managed in order to achieve an optimal interworking

More Related