A SOFTWARE DEFINED NETWORKING ARCHITECTURE FOR HIGH PERFORMANCE CLOUDS 1

Multi-tenant clouds with resource virtualization offer elasticity of resources and elimination of initial cluster setup cost and time for applications. However, poor network performance, performance variation and noisy neighbors are some of the challenges for execution of high performance applications on public clouds. Utilizing these virtualized resources for scientific applications, which have complex communication patterns, require low latency communication mechanisms and a rich set of communication constructs. To minimize the virtualization overhead, a novel approach for low latency networking for HPC Clouds is proposed and implemented over a multi-technology software defined network. The efficiency of the proposed low-latency SDN is analyzed and evaluated for high performance applications. The results of the experiments show that the latest Mellanox FDR InfiniBand interconnect and Mellanox OpenStack plugin gives the best performance for implementing virtual machine based high performance clouds with large message sizes.

[1]  Dhabaleswar K. Panda,et al.  TupleQ: Fully-asynchronous and zero-copy MPI over InfiniBand , 2009, 2009 IEEE International Symposium on Parallel & Distributed Processing.

[2]  Paul Rad,et al.  ZeroVM: secure distributed processing for big data analytics , 2014, 2014 World Automation Congress (WAC).

[3]  Yong Zhao,et al.  Cloud Computing and Grid Computing 360-Degree Compared , 2008, GCE 2008.

[4]  Xiaowei Yang,et al.  High performance network virtualization with SR-IOV , 2010, HPCA - 16 2010 The Sixteenth International Symposium on High-Performance Computer Architecture.

[5]  Pontus Sköldström,et al.  A Use-Case Based Analysis of Network Management Functions in the ONF SDN Model , 2012, 2012 European Workshop on Software Defined Networking.

[6]  Rajkumar Buyya,et al.  High-Performance Cloud Computing: A View of Scientific Applications , 2009, 2009 10th International Symposium on Pervasive Systems, Algorithms, and Networks.

[7]  Jose Renato Santos,et al.  Bridging the Gap between Software and Hardware Techniques for I/O Virtualization , 2008, USENIX Annual Technical Conference.

[8]  John Shalf,et al.  Performance Analysis of High Performance Computing Applications on the Amazon Web Services Cloud , 2010, 2010 IEEE Second International Conference on Cloud Computing Technology and Science.

[9]  Rolf Stadler,et al.  Dynamic resource allocation with management objectives—Implementation for an OpenStack cloud , 2012, 2012 8th international conference on network and service management (cnsm) and 2012 workshop on systems virtualiztion management (svm).

[10]  Paul Rad,et al.  Low-latency software defined network for high performance clouds , 2015, 2015 10th System of Systems Engineering Conference (SoSE).

[11]  Dhabaleswar K. Panda,et al.  Performance Analysis and Evaluation of InfiniBand FDR and 40GigE RoCE on HPC and Cloud Computing Systems , 2012, 2012 IEEE 20th Annual Symposium on High-Performance Interconnects.

[12]  Abhishek Gupta,et al.  Evaluation of HPC Applications on Cloud , 2011, 2011 Sixth Open Cirrus Summit.

[13]  Dhabaleswar K. Panda,et al.  High-Performance Design of HBase with RDMA over InfiniBand , 2012, 2012 IEEE 26th International Parallel and Distributed Processing Symposium.

[14]  Myung-Ki Shin,et al.  Software-defined networking (SDN): A reference architecture and open APIs , 2012, 2012 International Conference on ICT Convergence (ICTC).

[15]  Dhabaleswar K. Panda,et al.  SR-IOV Support for Virtualization on InfiniBand Clusters: Early Experience , 2013, 2013 13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing.

[16]  Geoffrey C. Fox,et al.  Distributed and Cloud Computing: From Parallel Processing to the Internet of Things , 2011 .

[17]  Sos S. Agaian,et al.  A novel image encryption method to reduce decryption execution time in cloud , 2015, 2015 Annual IEEE Systems Conference (SysCon) Proceedings.