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Center for Experimental Research in Computer Systems Spring 2007 IAB Meeting Karsten Schwan, Calton Pu, Douglas Blough, Sudhakar Yalamanchili IUCRCERCS.

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Presentation on theme: "Center for Experimental Research in Computer Systems Spring 2007 IAB Meeting Karsten Schwan, Calton Pu, Douglas Blough, Sudhakar Yalamanchili IUCRCERCS."— Presentation transcript:

1 Center for Experimental Research in Computer Systems Spring 2007 IAB Meeting Karsten Schwan, Calton Pu, Douglas Blough, Sudhakar Yalamanchili IUCRCERCS NSF Industry University Co-operative Research Center

2 Mission Scientific.Grid Enterprise Embedded Lead the innovation of new information and computing technologies, to construct the interactive information systems of the future, and to create the intellectual capital that can advance these technologies and fuel future advances. Information anytime, anywhere  Timeliness! Quality! Security! Robustness! Remote access to Information System

3 Strategic Thrusts - Highlights –Scientific/Technical Computing -- Dynamic Data Management and GT: IHPCL Laboratory (e.g., new cluster machines, including substantial Intel donations for education and for multicore computing initiative) DOE:ORNL, Sandia: High Performance I/O initiative; involvement with startups Cisco (MPI and IB QoS); Dell; HP/Intel (Gelato, Itanium donations); IBM (VMM power management, Cell SUR grant), RNet communication processor design News: Multicore Focus (HP, IBM, Intel); Ongoing I/O Initiative, Virtualization in HPC (ONRL, Sandia, UNM)

4 Strategic Thrusts - Highlights –Enterprise Computing -- Autonomic/Adaptive and Service-Oriented Systems: IBM, Intel, TCS (autonomic and critical enterprise systems, dynamic content distribution/event-based systems, SOA, virtualization – hypervisor scaleout, I/O virtualization, trusted passages, metering, power management, failure diagnosis and fault containment) HP (deployment and management, system monitoring, risk-based control, stream data mining) Worldspan (runtime behavior detection and QoI, virtualization) LogicBlox (Dynamic code generation for efficient data access) Delta, Raytheon (policy/performancerobustness, runtime behavior modeling) Cisco, Intel (network data services, heterogeneous multicore, IB network virtualization) News/Outreach: IBM SUR (joint with Ohio State), OSU industry partners, OSU IAB meeting, exploring new links: Benchmark, Earthlink, McKesson, NSF CRI Airport LAN Airport LAN Airport LAN Airport LAN Cluster Computing Real-Time Information Processing Cluster Computing Real-Time Information Processing Optimization Baggage Status Baggage Displays Crew and Equipment Status FAA Flight Data Passenger paging and response Gate Readers Wide-area Transport Real-time Decision Tools Scalable Robust Services Storage Databases capture, display, transport, filter, transform Real-Time Information Transport Visualization Real-time Situation Assessment High Performance Computing Operational Flight Displays

5 Strategic Thrusts - Highlights –Embedded Systems/Architecture Boeing (testing, software correctness) Intel (in-vehicle computing and lightweight methods for system virtualization, system-level power management, computer architecture) Motorola (middleware for pervasive and mobile applications) Federal: pervasive applications (transportation, robotics), upcoming Cyberphysical Systems program IBM, Intel (network processors and heterogeneous multicore) Sony (gaming applications) News: Korea program in Embedded Systems, Samsung educational program, Robotics Center liason, Sensor (OSU) and MobiEMU testbeds image quality, end-to-end delay, jitter, loss rate throughput, response times

6 CERCS Personnel Faculty –Mustaque Ahamad, Mostafa Ammar, Doug Blough, Constantinos Dovrolis, Greg Eisenhauer, Richard Fujimoto, Ada Gavrilovska, Alexander Gray, Mary Jean Harrold, Hsien-Hsin Lee, Wenke Lee, Ling Liu, Gabriel Loh, Pete Manolios, Alex Orso, Henry Owen, Santosh Pande, Milos Prvulovic, Calton Pu, Kishore Ramachandran, Jay Ramanathan (Ohio State), Rajiv Ramnath (Ohio State), George Riley, David Schimmel, Karsten Schwan, Olin Shivers, Matthew Wolf, Hongyan Zha, Sudhakar Yalamanchili, Ellen Zegura Research Staff –Steve Ferenci, David Hilley –Supported by DARPA, DOE, NSF, (CoC), (ECE) Associated Faculty/Researchers –David Bader, Tucker Balch (Robotics), Patrick Bridges (UNM), Robert Butera, Steve DeWeerth, Irfan Essa, Phil Hutto, Byron Jeff (Clayton State), Scott Klasky (ORNL), Kang Li, Sung Kyu Lim, Arthur Maccabe (UNM), Vincent Mooney, Jeff Nichols (ORNL), Krishna Palem, Kalyan Perumalla (ORNL), Jeff Vetter (ORNL), Patrick Widener (UNM)

7 Industrial Relations IUCR CERCS Center –Contributors (GT): Boeing, Cisco, Delta, DOE, HP, IBM, Intel, LogicBlox, TCS, Worldspan –Industry Workshops and Industrial Advisory Board Joint initiatives - e.g., TIE grant with UFL, expansion to Ohio State (joint curriculum/facility efforts), planned expansion to UNM Internship Program –Amazon, ATT, CISCO, Delta, (DoCoMo), DOE, Google, HP, IBM, Intel, Microsoft, Motorola, NetApp, Radisys, TCS, VMWare, Worldspan Evolving relationships: –ATT, DoCoMo, Microsoft, Motorola, NetApp, Netronome, Raytheon, RNet, VMWare, Xilinx

8 Overview - Current Industry Engagements One slide per ongoing project Federal projects (e.g., joint work with DOE ORNL) elided, so, few HPC efforts described Same order: HPC, Enterprise, Embedded

9 HPC: Cisco - Infiniband-based Research Gavrilovska, Schwan, Wolf Mechanisms for delivering end-to-end QoS levels in challenging settings: –Multi-core nature of future HPC nodes –I/O limitations in high-performance infrastructures –End-to-end virtualized environments Two main efforts under current investigations: –Data virtualization: ‘Datatap’ mechanism on top of low-level IB verb interface to (1) extract data from IB infrastructure, (2) middleware mechanisms to support dynamic extensions for service-oriented applications, (3) dynamic, resource-aware routing and data distribution to meet application QoS requirements. –Platform virtualization: (1) integrate x86-based virtualization solutions into Infiniband settings, (2) develop mechanisms for end-to-end QoS for VM-to- VM interactions by improved and dynamic resource management and scheduling mechanisms. Additional Effort :RNET – high end NIC for science applications

10 Enterprise: Elba Project – HP Labs Calton Pu Apply code generation techniques to automate large system deployment, measurement, evaluation, and management Collaborative work (1 faculty-Pu, 1 industry-Sahai, 6 PhD stud., 4 MS stud., 1 undergrad.) 8 published papers in 2 years, several more in the pipeline Automated System Mgmt (1) Design (2) Code Generation (4) Evaluation & Analysis (5) Reconfiguration (3) Deployment Current work: (step 4 above) Evaluation of 3-tier benchmark (RUBiS) using generated scripts (millions of lines of deployment, measurement, and analysis scripts)

11 Enterprise: Robust Delivery of Quality Data - Worldspan Karsten Schwan, Mohamed Mansour, Jay Lofstead Problem: Complex GDS with potentially unanticipated behaviors Example: Variable search times due to caching effects Solution: Runtime behavior detection, model construction, and mitigation Specific approach: Mitigation via request reordering

12 Enterprise: Runtime Behavior Diagnosis – Delta Air Lines Sandip Agarwala, Mohamed Mansour, Karsten Schwan Investigation of multiple enterprise architectures –Revenue Pipeline, delta.com, DNS Path detection in complex systems Autonomic workflows Monitoring and management in SOA systems (proposed work)

13 Enterprise: Collaboration with IBM Research Ling Liu Distributed Systems and Software –Dynamic Content Dissemination: Architectures and Optimizations –Collaborators: Arun Iyengar, Fred Douglis, Isabelle Rouvellou Event Streams and Security –Sensor Stream Processing and Optimization (e.g., load shedding, load balancing, motion adaptive indexing) –Event Stream Mining –Collaborators: Philip Yu, Bugra Gedik, Rong Chang Service Oriented Computing –Secure publish-subscribe systems, Secure Event Dissemination –Collaborators: Arun Iyengar, Liang Jie Zhang 13

14 Enterprise/HPC: High Productivity Computing Stream computing programming model –Kernels expressed in a declarative programming language –Custom hardware for accelerating data intensive kernels –Explicit interaction model: non-coherent shared memory Focus on applications such as retail forecasting and data analytics Local Memory Cache ACC DMA FIFO Local Memory Cache Local Memory Cache ACC DMA FIFO ACC DMA FIFO Network (e.g., Hypertransport) CPU Run-time Kernel InputsOutputsInputsOutputs Application Memory Sudha Yalamanchili with LogicBlox Inc.

15 Enterprise/HPC: Databus: Runtime Rule Generation - LogicBlox Greg Eisenhauer Fine grain retail data analysis (what- if calculations) Rule-based declarative language Compile down to interpreted “FactBus”, Rule objects and variable objects. Apply rules top to bottom, fallback on failure. Use DCG for “Just-In Time” compilation Initial results, speedups of 3. Additional improvements anticipated. Write Test Iterator Lookup BinOp FactBus Variables Rules DCG subset apply DB String int bool double

16 Enterprise/HPC: Scalable Hypervisors - Intel Karsten Schwan

17 Enterprise: Power Management in Virtualized Systems Platform HW VMM Dom0 OS Application VM 3 OS Application VM 2 VPM Channel VPM Mechanisms PM Policy Platform HW VMM Dom0 OS Application VM 1 VPM Channel VPM Mechanisms PM Policy Heterogeneity-aware Allocation Policy Leverage heterogeneity in: Performance capabilities Power efficiency of resources Power management support Leverage heterogeneity in: Performance capabilities Power efficiency of resources Power management support Coordinate virtualized system management: Enable VM management independence Decouple virtual and physical resources for management Introduce “soft” scaling for flexible management Coordinate virtualized system management: Enable VM management independence Decouple virtual and physical resources for management Introduce “soft” scaling for flexible management Ripal Nathuji Karsten Schwan IBM + Intel

18 Enterprise: Trusted Passages on Virtualized Platforms – Intel/NSF Hypervisor Service VM Guest VM1 Guest VM2 BE NIC Trust Controller App. FE Hypervisor Service VM Guest VM1 Guest VM2 BE NIC Trust Controller App. FE networ k Host1Host2 Overlay node1Overlay node2 networ k Trusted passage Mustaq Ahamad Greg Eisenhauer Wenke Lee Karsten Schwan Run trusted services across untrusted platforms: Trust models and trust controller mechanisms for evolving node trust Virtual Machines Monitoring and Introspection to support trust controllers Data Interception and Redirection as Remedial Measures

19 Research Question How can we perform fault analysis at the system-model level and make this information accessible to developers? Fault Propagation for Safety (Boeing) Problem Critical avionics systems now use integrated modular avionics making fault analysis for the entire system difficult Embedded/Enterprise: Aristotle Research Group (Mary Jean Harrold) Testing Evolving Software (TCS) (with Alex Orso) Problem Changes require rapid modification and testing for quick release causing released software to have many defects Research Question How can we test well (to gain confidence in changes before release of changed software) MaTRIX Computes conditions test cases must satisfy to test changes well FauPA Propagates injected faults forward to determine impact; Traces faulty components backward to find root cause

20 Embedded: Correct Software Assemblies - Boeing


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