We think you have liked this presentation. If you wish to download it, please recommend it to your friends in any social system. Share buttons are a little bit lower. Thank you!
Presentation is loading. Please wait.
Published byPhoenix Gooch
Modified about 1 year ago
TEMPLATE DESIGN © 2008 www.PosterPresentations.com High Performance Molecular Dynamics in Cloud Infrastructure with SR-IOV and GPUDirect Andrew J. Younge *, John Paul Walters +, Geoffrey C. Fox* Introduction BenchmarksResults Conclusion References At present we stand at the inevitable intersection between High Performance Computing (HPC) and Clouds. Various platform tools such as Hadoop and MapReduce, among others have already percolated into data intensive computing within HPC . Alternatively, there are efforts to support traditional HPC-centric scientific computing applications in virtualized Cloud infrastructure. The reasons for supporting parallel computation on Cloud infrastructure is bounded only by the advantages of Cloud computing itself . For users, this includes features such as dynamic scalability, specialized operating environments, simple management interfaces, fault tollarance, and enhanced quality of service, to name a few. The growing importance of supporting advanced scientific computing using cloud infrastructure can be seen by a variety of new efforts, including the NSF-funded XSEDE Comet resource at SDSC . Reluctantly, there exists a past notion that virtualization used in today’s Cloud infrastructure is inherently inefficient. Historically, Cloud infrastructure has also done little to provide the necessary advanced hardware capabilities that have become almost mandatory in Supercomputers today, most notably advanced GPUs and high-speed, low-latency interconnects. The result of these notions has hindered the use of virtualized environments for parallel computation, where performance must be paramount. Recent advances in hypervisor performance  coupled with the newfound availably of HPC hardware in virtual machines analogous to the most powerful supercomputers used today, we see can see the formation of a High Performance Cloud infrastructure. While our previous advanced in this are have focused on single-node advancements, it is now imparative to ensure real-world applications can also operate at scale. Furthermore, the tight and exact integration into an open source Cloud infrastructure framework such as OpenStack also becomes a critical next step.  S. Jha, J. Qiu, A. Luckow, P. K. Mantha, and G. C. Fox, “A tale of two data-intensive paradigms: Applications, abstractions, and architectures,” in Proceedings of the 3rd International Congress on Big Data (BigData 2014), 2014.  M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. Katz, A. Konwinski, G. Lee, D. Patterson, A. Rabkin, I. Stoica, and M. Zaharia, “A view of cloud computing,” Commun. ACM, vol. 53, no. 4, pp. 50–58, Apr. 2010.  M. Norman and R. Moore, “NSF awards 12 million to sdsc to deploy comet supercomputer,” Web page, 2013.  A. J. Younge, R. Henschel, J. T. Brown, G. von Laszewski, J. Qiu, and G. C. Fox, “Analysis of Virtualization Technologies for High Performance Computing Environments,” in Proceedings of the 4th International Conference on Cloud Computing (CLOUD 2011). Washington, DC: IEEE, July 2011.  J. P. Walters, A. J. Younge, D.-I. Kang, K.-T. Yao, M. Kang, S. P. Crago, and G. C. Fox, “GPU-Passthrough Performance: A Comparison of KVM, Xen, VMWare ESXi, and LXC for CUDA and OpenCL Applications,” in Proceedings of the 7th IEEE International Conference on Cloud Computing (CLOUD 2014), IEEE. Anchorage, AK: IEEE, 2014.  J. Jose, M. Li, X. Lu, K. C. Kandalla, M. D. Arnold, and D. K. Panda, “SR-IOV support for virtualization on infiniband clusters: Early experience,” in Cluster Computing and the Grid, IEEE International Symposium on, 2013, pp. 385–392.  M. Musleh, V. Pai, J. P. Walters, A. J. Younge, and S. P. Crago, “Bridging the Virtualization Performance Gap for HPC using SR-IOV for InfiniBand,” in Proceedings of the 7th IEEE International Conference on Cloud Computing (CLOUD 2014), IEEE. Anchorage, AK: IEEE, 2014.  W. M. Brown, “GPU acceleration in LAMMPS  J. Anderson, A. Keys, C. Phillips, T. Dac Nguyen, and S. Glotzer, “HOOMD-Blue, general-purpose many-body dynamics on the GPU,” in APS Meeting Abstracts, vol. 1, 2010, p. 18008. * School of Informatics & Computing, Indiana University 901 E. 10th St., Bloomington, IN 47408 U.S.A. + Information Sciences Institute, University of Southern California 3811 North Fairfax Drive, Suite 200, Arlington, VA 22203 U.S.A. LAMMPS HOOMD-Blue Focus Areas Hypervisor Performance Virtualization can operate with near-native performance. IO Virtualization Leverage VT-d/IOMMU extensions to pass PCI-based hardware directly to a guest VM. GPUs and Accelerators Utilize PCI Passthrough in to provide GPUs to VMs Many hypervisors now able to support GPU Passthrough – we use KVM for best performance. High Speed Interconnects Using SR-IOV, we can create multiple VFs from a single PCI devicee, each assigned directly to a VM. Use Mellanox ConnectX3 VPI InfiniBand. QDR/FDR InfiniBand now possible within Cloud IaaS! OpenStack Integration Integrate virtualization advances to the OpenStack Cloud IaaS. Prototype available, some features available today Historically running advanced scientific applications in a virtualized infrastructure has been limited by both performance and advanced hardware availability Recent advancements allow for the use of both GPUs and InfiniBand fabric to be leveraged directly in VMs LAMMPS and HOOMD represent Molecular Dynamics tools commonly used on the most powerful supercomputers Virtualized performance for both applications at near-native 96.7% and 99.3% efficiency for LAMMPS LJ 2048k and RHODO 512k simulations 98.5% efficiency for HOOMD LJ 256k simulation Support for new GPUDirect RDMA features in virtualized system Large-scale virtualized Cloud Infrastructure can now support many of the same advanced scientific computations that are commonly found running on today’s supercomputers.
Advanced Virtualization Techniques for High Performance Cloud Cyberinfrastructure Andrew J. Younge Ph.D. Candidate Indiana University Advisor: Geoffrey.
Evaluating GPU Passthrough in Xen for High Performance Cloud Computing Andrew J. Younge 1, John Paul Walters 2, Stephen P. Crago 2, and Geoffrey C. Fox.
GPUs on Clouds Andrew J. Younge Indiana University (USC / Information Sciences Institute) UNCLASSIFIED: 08/03/2012.
SALSASALSASALSASALSA Digital Science Center February 12, 2010, Bloomington Geoffrey Fox Judy Qiu
© 2012 MELLANOX TECHNOLOGIES 1 Disruptive Technologies in HPC Interconnect HPC User Forum April 16, 2012.
The Development of Mellanox - NVIDIA GPUDirect over InfiniBand A New Model for GPU to GPU Communications Gilad Shainer.
Cloudsim: simulator for cloud computing infrastructure and modeling Presented By: SHILPA V PIUS 1.
Gilad Shainer, VP of Marketing Dec 2013 Interconnect Your Future.
Grappling Cloud Infrastructure Services with a Generic Image Repository Javier Diaz Andrew J. Younge, Gregor von Laszewski, Fugang.
Eucalyptus on FutureGrid: A case for Eucalyptus 3 Sharif Islam, Javier Diaz, Geoffrey Fox Gregor von Laszewski Indiana University.
Https://portal.futuregrid.org Clouds from FutureGrid’s Perspective April Geoffrey Fox Director, Digital Science Center, Pervasive.
Iterative computation is a kernel function to many data mining and data analysis algorithms. Missing in current MapReduce frameworks is collective communication,
1 1 Hybrid Cloud Solutions (Private with Public Burst) Accelerate and Orchestrate Enterprise Applications.
Performance Analysis of Virtualization for High Performance Computing A Practical Evaluation of Hypervisor Overheads Matthew Cawood University of Cape.
LARGE SCALE DEPLOYMENT OF DAP AND DTS Rob Kooper Jay Alemeda Volodymyr Kindratenko.
Virtual Machine in HPC PAK MARKTHUB (13M54040) 1 VIRTUAL MACHINE IN HPC.
Design Discussion Rain: Dynamically Provisioning Clouds within FutureGrid Geoffrey Fox, Andrew J. Younge, Gregor von Laszewski, Archit Kulshrestha, Fugang.
FutureGrid Connection to Comet Testbed and On Ramp as a Service Geoffrey Fox Indiana University Infra structure.
Building on virtualization capabilities for ExTENCI Carol Song and Preston Smith Rosen Center for Advanced Computing Purdue University ExTENCI Kickoff.
Above the Clouds : A Berkeley View of Cloud Computing Michael Armbrust Armando Fox Rean Griffith Anthony D. Joseph Randy H. Katz Andrew Konwinski Gunho.
Experimenting with FutureGrid CloudCom 2010 Conference Indianapolis December Geoffrey Fox
Extreme scale parallel and distributed systems – High performance computing systems Current No. 1 supercomputer Tianhe-2 at petaflops Pushing toward.
Analysis of Virtualization Technologies for High Performance Computing Environments Andrew J. Younge, Robert Henschel, James T. Brown, Gregor von Laszewski,
Through the development of advanced middleware, Grid computing has evolved to a mature technology in which scientists and researchers can leverage to gain.
Https://portal.futuregrid.org Big Data and Clouds: Challenges and Opportunities NIST January Geoffrey Fox
Memcached Integration with Twister Saliya Ekanayake - Jerome Mitchell - Yiming Sun -
Https://portal.futuregrid.org Scientific Computing Environments ( Distributed Computing in an Exascale era) August Geoffrey Fox
Authors: Thilina Gunarathne, Tak-Lon Wu, Judy Qiu, Geoffrey Fox Publish: HPDC'10, June 20–25, 2010, Chicago, Illinois, USA ACM Speaker: Jia Bao Lin.
1 Cloud Systems Panel at HPDC Boston June Geoffrey Fox Community Grids Laboratory, School of informatics Indiana University
Https://portal.futuregrid.org Directions in eScience Interoperability and Science Clouds June Interoperability in Action – Standards Implementation.
Efficient Resource Management for Cloud Computing Environments 2: Rochester Institute of Technology 102 Lomb Memorial Drive Rochester, New York :
Https://portal.futuregrid.org Science Clouds and FutureGrid’s Perspective June Science Clouds Workshop HPDC 2012 Delft Geoffrey Fox
SALSASALSASALSASALSA Digital Science Center June 25, 2010, IIT Geoffrey Fox Judy Qiu School.
A Practical Evaluation of Hypervisor Overheads Matthew Cawood Supervised by: Dr. Simon Winberg University of Cape Town Performance Analysis of Virtualization.
Data Science at Digital Science October Geoffrey Fox Judy Qiu
IMPROVEMENT OF COMPUTATIONAL ABILITIES IN COMPUTING ENVIRONMENTS WITH VIRTUALIZATION TECHNOLOGIES Abstract We illustrates the ways to improve abilities.
Grids, Clouds and the Community. Cloud Technology and the NGS Steve Thorn Edinburgh University Matteo Turilli, Oxford University Presented by David Fergusson.
Introduction to Data Analysis with R on HPC Texas Advanced Computing Center Feb
IM&T Vacation Program Benjamin Meyer Virtualisation and Hyper-Threading in Scientific Computing.
Https://portal.futuregrid.org Computing Research Testbeds as a Service: Supporting large scale Experiments and Testing SC12 Birds of a Feather November.
Andrew J. Younge Golisano College of Computing and Information Sciences Rochester Institute of Technology 102 Lomb Memorial Drive Rochester, New York
Power-Aware Scheduling of Virtual Machines in DVFS-enabled Clusters Gregor von Laszewski 1, Lizhe Wang 2, Andrew J. Younge 2, Xi He 2 1: Pervasive Technology.
New Direction Proposal: An OpenFabrics Framework for high-performance I/O apps OFA TAC, Key drivers: Sean Hefty, Paul Grun.
Introduction to Cloud Computing Zsolt Németh MTA SZTAKI.
Opensource for Cloud Deployments – Risk – Reward – Reality John Gormally Enterprise Relationship Manager Citrix Networking and Cloud Team.
SALSASALSASALSASALSA Performance Analysis of High Performance Parallel Applications on Virtualized Resources Jaliya Ekanayake and Geoffrey Fox Indiana.
OpenStack for VMware administrators in the context of a fictional use case Bridging the Gap.
3DAPAS/ECMLS panel Dynamic Distributed Data Intensive Analysis Environments for Life Sciences: June San Jose Geoffrey Fox, Shantenu Jha, Dan Katz,
The Datacenter Needs an Operating System Matei Zaharia, Benjamin Hindman, Andy Konwinski, Ali Ghodsi, Anthony Joseph, Randy Katz, Scott Shenker, Ion Stoica.
High Performance Computing on Virtualized Environments Ganesh Thiagarajan Fall 2014 Instructor: Yuzhe(Richard) Tang Syracuse University.
© 2017 SlidePlayer.com Inc. All rights reserved.