System Software OptIPuter System Software Andrew A. Chien SAIC Chair Professor, Computer Science and Engineering, UCSD Director, Center for Networked Systems September 2003

System Software OptIPuter System Software Team Challenge –~20 Lead Researchers, Many More in Entire Team –Diverse Researcher Backgrounds and Focus –Broad Research Agenda, Abstract Shared Perspective Process –Innumerable Phone Calls and 1-on-1 Meetings, Fall 2002-Spring 2003 –Team Meeting with UCSD and UCI Teams (October 4, 2002) –Straw Man OptIPuter System Software Architecture (January 2003) –Goals, Context, Organization, Relationship of Efforts –OptIPuter All Hands Meeting, February 6-7, 2003 –First Presentation to Entire Team –Feedback, Revision, Improvement, Deeper Understanding, Shared Perspective –Optical Signalling and Network Management Meeting (May 22, 2003) –Mambretti Organized –OptIPuter Software Architecture Version 1.0 (July 2003) –Structure Stabilized, interfaces Becoming Concrete

System Software ’s Transform Distributed Systems Key Technology Changes –Massive Bandwidth – x Increases Wide-Area Systems –“End To End” -Connections –Private Networks, Guaranteed Bandwidth –Endpoints are Parallel Clusters –Large-Scale Network-Attached –Storage –Instruments –Displays –Other Peripherals –Grids and Flexible Wide-Area Sharing Opportunities –Communication –Tight Wide-area Resource Coupling –Simpler Distributed Applications –Proactive Computing and Communication Challenge is Abstractions, Technologies, and Protocols (SOFTWARE!) to Deliver these Capabilities to Applications

System Software Towards Middleware for -Networked Systems Fabric Resource Access and Control: Computers, Storage, Networks Connectivity Globus_IO/XIO & GSI Resource GRAM, GridFTP, GRIS, Co- allocation Collective DUROC, GARA, Replica Catalogs, Metadata Servers, Brokers, Workflow Application Leverage Investment and Capabilities (e.g. Globus 2.2 and 3.0) –Carl Kesselman OptIPuter Participant –Ian Foster, OptIPuter Frontier Advisory Board Explore What Must Change –New Software/Protocols for Managing Lambdas –Simplify, Deliver Higher Performance and New Capabilities Globus Architecture

System Software OptIPuter Software Architecture for Distributed Virtual Computers v1.1 Layer 4: XCP Node Operating Systems -configuration, Net Management Grid and Web Middleware – (Globus/OGSA/WebServices/J2EE) Physical Resources DVC #1 OptIPuter Applications DVC #2DVC #3 Layer 5: SABUL, RBUDP, Fast, GTP Real-Time Objects Security Models Data Services: DWTP Higher Level Grid Services Visualization DVC/ Middleware High-Speed Transport Optical Signaling/Mgmt

System Software OptIPuter Links Three Major Sets of Technology Activities Distributed Virtual Computers –Provide a Simple Abstractions –Aggregate Component Technology Capabilities –Surface Novel Capabilities High speed Transport Protocols [Bannister’s Talk] –Long Thread of High Bandwidth-Delay Product Network Protocols –Span The Range “Reach” For Dedicated Optical Connections –Complete Integration with IP Network Management –Hybrid – to Local Packet-Switched Networks –Separate – End-to-end Optical Network Signaling and Management [Mambretti’s Talk] –Single Domain and Inter-Domain –Hybrid Circuit and Packet-Switched Networks –Planning and Execution

System Software Distributed Virtual Computers

System Software Exploiting ’s for an Application Network View: Ad Hoc connections –Applications Request -Connections –Network Recognizes High BW flows and Configures System View: Enclave of Resources and Connections –a Distributed Virtual Computer (a SYSTEM) –How to Specify, Implement, and Exploit?

System Software DVC Examples Virtual Cluster (Hide Complexity of Grid; Resource Flexibility) –Shared Single Domain (Spans Multiple) –Private Connections; Simple Network Naming –Simple Resource Discovery and Access –Uniform Performance Characteristics –Direct Access to Everything (Storage, Displays, etc.) Real-Time Virtual Cluster for Distributed Collaborative Visualization –Grid Resources + Real-Time (TMO) Collaborative Visualization Cluster –Grid Resources + Photonic Multicast or LambdaRAM (Leigh) SIO/NCMIR UCI or UIC SDSC UCSD CSE

System Software Realizing Distributed Virtual Computers Research Challenges –Application-driven Definition of Abstractions –Useful Collections which Match Application Paradigms and Needs –Incorporates New Collective Models –DVC Description –Namespaces, Communication, Performance, Real-Time, … –Standard Specifications; Most Applications Parameterize –Integration Of Component Technologies Executing the DVC on a Grid –Planner That Identifies Resources –Selects from Virtual Grid Resources –Negotiates with Resource Managers and Brokers –Executor and Monitor for DVC –Acquires and Configures –Monitors for Failures and Performance –Adapts and Reconfigures

System Software OptIPuter Component Technologies

System Software Current Storage Views Network-attached Storage (NAS) –Filesystem protocols; Integrated Access-Control and Security –Low performance; Little Aggregation and Parallelism Grid View: High-Level Storage Federation –GridFTP (Distributed File Sharing) –GSI-based Access/Authentication –Put/Get, Third-Party Transfers, Whole File and Segments Single-System view: Lower-level storage federation –Secure Single System View –SAN – Block Level Disk and Controller Protocols –High Performance, Efficient sharing Research Areas –Network-Attached Secure Disk –Direct Access File Systems

System Software We Need a Distributed Storage Solution for e-Science Distributed Data Generators BIRN: Distributed Data, Intensive Analysis –100GB Data Elements; Petabyte Data Sets –Comparative and Collective Analysis across Data Elements –Visualization of Multi-Scale Data Objects

System Software Storage Research Directions From Performance to Performability –Manage and Exploit Multi-Latency Performance –Parallel Performance, Stability, and Isolation –Integration of Device, Network, Site Reliability Concerns OptIPuter Storage Directions –Application-Driven Design –Needs, Performance, Device/Site/Network Flexibility, Coding and Selection –Integrate Dynamic ’s and SAN Networks –Peering, Protocol Interfacing, Performance –Performance Robust Storage –Erasure/Other Redundancy; Large-Scale Parallelism; Statistical Approaches to Performance Isolation –Secure Shared Storage: Threshold Cryptography Approach

System Software OptIPuter Security Considerations OptIPuter as a Computing Platform –Information Assurance and Security Needed for Applications –Current Plan: use Globus Security Infrastructure OptIPuter as a Research Platform –Current Efforts –Distributed Security Services (Goodrich & Tamassia) –Incremental IP Trace-Back via Packet Marking for DOS Defense (Goodrich) –Enhanced Forensic Analysis By Design (Karin & Peisert) –Planned Efforts –Minimum Round Trip Latency Control (Goodrich) –Hardening Against Attacks by Multi-Path Routing (Goodrich, Karin) –End-to-End Application and Session Security Through Dedicated Lambdas (Karin) Source: Karin, UCSD and Goodrich, UCI

System Software Multi-Lambda Security Opportunities Security Frequently Defined Through Three Measures: –Integrity, Confidentiality, And Reliability (“Uptime”) Can These Measures be Enhanced by Employing Multiple Lambdas? Can Confidentiality be Improved by Dividing the Transmission Over Multiple Lambdas? –Fundamentally or Using “Cheap” Encryption? Can Integrity be Ensured or Reliability Improved by Exploiting Redundancy? –Source Coding and Performance –Adaptive Techniques Source: Goodrich, Karin

System Software Vision – Real-Time Tightly Coupled Wide-Area Distributed Computing Real- Time Object network Goals High-precision Timings of Critical Actions Tight Bounds on Response Times Ease of Programming –High-Level Prog –Top-Down Design Ease of Timing Analysis Dynamically formed Distributed Virtual Computer Source: Kim, UCI

System Software Real-Time: from LAN to WAN Time-Triggered Message-Triggered Object (TMO) Middleware Subsystem Model that can be Easily Implemented on Both Windows and Linux Platforms Developed a Global Time-Based Coordination for use in Fair and Efficient Distributed On-Line Game Systems and LAN Feasibility Demonstration –a Step towards Distributed OptIPuter Environment Demonstration –Paper will be Presented at IDPT 2003 Conference, December 2003 var TT Method 2 Service Method 1 TT Method 1 AAC        Compo- nents of a C++ object No thread, No priority High-level Programming Style Deadlines Service Method 2 Source: Kim, UCI

System Software TMO and OptIPuter Software TMO will be Integrated into the Overall OptIPuter Software Architecture Begin Design TMO Programming Framework for the OptIPuter Prototype Implementation TMO Support on Linux Platforms, Including OptIPuter Visualization Cluster (UIC – Leigh, UCI -- Jenks) Kernel TMOSM FT Support Middleware Lambda mux / demux Kernel TMOSM FT Support Middleware Lambda mux / demux data " Let us start a chorus at 2pm " " e-Science " An API Wrapping the Services of the RT Middleware Enables High-Level RT Programming Without a new Compiler Source: Kim, UCI

System Software Prophesy: Application Performance Modeling Performance Modeling of Applications on OptIPuter Cross Platform Comparison (vs. Traditional Grid & Parallel) Yr1: Completed Data Analysis Module Yr2: Work with Applications and High Speed Transport Protocols Target applications include: –SIO Geophysical Data Visualization –NCMIR/BIRN Neuroscience Applications Source: Taylor, TAMU Web-based GUI Profiling & Instrumentation Actual Execution Performance Database Template Database Systems Database Model Builder Symbolic Predictor DATA COLLECTION DATABASES DATA ANALYSIS

System Software Summary OptIPuter System Software Team Organization –Development of a Concrete, Shared Perspective –Organization into Tightly-Coupled Teams OptIPuter Software Architecture 1.0 (July 2003) –Provides Focus on Key Problems, Clusters Related Activities –Framework for Integrating Diverse Capabilities, Identifying Gaps, Integrating and Delivering Solutions Research Activity Clusters –Distributed Virtual Computers –Including Real-Time, Security, Storage, Performance Modeling –High Speed Transport Protocols –Optical Signaling and Network Management