HPEC’02 Workshop September 24-26, 2002, MIT Lincoln Labs Applying Model-Integrated Computing & DRE Middleware to High- Performance Embedded Computing Applications.

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Presentation transcript:

HPEC’02 Workshop September 24-26, 2002, MIT Lincoln Labs Applying Model-Integrated Computing & DRE Middleware to High- Performance Embedded Computing Applications Douglas C. Schmidt Aniruddha Gokhale Chris Gill

HPEC’02 CoSMIC 2 Context HPEC systems are widely used for signal & image processing applications with stringent QoS distributed real-time & embedded (DRE) requirements Motivation Problem Due to weight, power, real-time, & footprint constraints, HPEC software has not traditionally been able to leverage advances in COTS middleware Promising Solution Use standards-based DRE middleware supporting multidimensional QoS properties (RT-CORBA, DP-CORBA, load balancing)

HPEC’02 CoSMIC 3 DRE Middleware in HPEC Applications High-performance, real-time, fault- tolerant, & secure systems Power-aware ad hoc, mobile & embedded systems Autonomous distributed embedded systems

HPEC’02 CoSMIC 4 DRE Middleware: RT CORBA Overview CORBA is a middleware standard Real-time CORBA adds QoS to classic CORBA to control: 3. Memory Resources Request buffering These capabilities address some (but by no means all) important HPEC application development & QoS- enforcement challenges 2. Communication Resources Protocol policies Explicit binding Protocol Properties Explicit Binding Client Propagation & Server Declared Priority Models Portable Priorities Thread Pools Static Scheduling Service Standard Synchonizers 1. Processor Resources Thread pools Priority models Portable priorities Standard synchronizers Static scheduling service Request Buffering

HPEC’02 CoSMIC 5 DRE Middleware: Data Parallel CORBA Data Parallel CORBA bridges the gap between traditional CORBA applications & high- performance embedded parallel processing applications as follows: Client on parallel ORB Parallel ObjectComputing Grid Part 1 Part 2 Part 3 Airborne HPEC Distributed shipboard clusters CONUS supercomputers … Data reorganization strategies Enable CORBA applications over clusters of computers No change required in software technologies, methodologies, or tools Enable massively parallel applications to integrate easily with distributed systems Allow parallel applications to benefit from distributed object methodologies, technologies, & tools Add parallelism & data distribution to the transparencies offered by CORBA Enable a new class of applications e.g., financial, industrial, medical, aerospace, multimedia, and military domains

HPEC’02 CoSMIC 6 Problems with Standard DRE Middleware Lack of coordination in standards committees addressing multiple QoS properties Several independent standards each addressing a single dimension of QoS e.g., Real-time CORBA, Fault tolerant CORBA, Load Balancing, Data Parallel CORBA, etc. Promising Solution Integrate Model-Integrated Computing & the OMG Model Driven Architecture with Multi-QoS DRE middleware Too many “standards” Proliferation of middleware technologies – CORBA, Java EJB/RMI, COM+/.NET No one-size-fits all Accidental complexities assembling, integrating & deploying software systems

HPEC’02 CoSMIC 7 Proliferation of middleware UML modeling tools used to model DRE application behavior Model-first/generate-next strategy for finer grained control in components Simultaneous support for multiple QoS dimensions Model overall application QoS & partitioning Compose application servers Model & synthesize components Validate & deploy Accidental Complexities Synthesize container QoS configurations & metadata Integrating MIC with DRE Middleware

HPEC’02 CoSMIC 8 Applies domain-specific modeling languages to computing systems Provides rich modeling environment including model analysis & model-based program synthesis Modeling of integrated end-to-end view of applications with interdependencies Modeling languages & environments themselves can be modeled as meta-models Examples Generic Modeling Environment ( Ptolemy ( Based on DARPA MoBIES program Analyze – different but interdependent characteristics of DRE system behavior Synthesize – platform-specific code customized for DRE application Model-Integrated Computing (MIC) Overview

HPEC’02 CoSMIC 9 OMG standardization of MIC paradigm Defines platform- independent models (PIMs) and platform-specific Models (PSMs) Uses Unified Modeling Language (UML) for modeling Real-time profile Dynamic scheduling profile Meta Object Facility (MoF) serves as meta-model repository XML Metadata Interchange (XMI) for meta-model exchange Efforts are underway to integrate DARPA MoBIES/MIC with OMG MDA Contact John Bay Model Driven Architecture (MDA) Overview

HPEC’02 CoSMIC 10 Component Integrated ACE ORB (CIAO) Support development via composition Providing CCM framework QoS-aware Decouple QoS policies specification from component implementations Specify QoS policies in component assembly descriptors Configurable Leveraging hardware capabilities Composing QoS supporting mechanisms for CCM application servers deuce.doc.wustl.edu/CIAO CCM incarnation of TAO Real-time ORB

HPEC’02 CoSMIC 11 Integrating DP-CORBA & Load Balancing Meta Resource Broker DP-CORBA incarnation of TAO Broker for resources Maintains abstractions of concrete resources & their usage Uses DP-CORBA to partition data Uses TAO load balancing service to make optimal use of resources QuO (quo.bbn.com) provides flexible QoS management MRB uses QuO for QoS monitoring and adaptation

HPEC’02 CoSMIC 12 Component Synthesis with MIC (CoSMIC) Synthesizes code & configuration metadata for the CIAO CORBA Component middleware Reusing components via compositions vs. generating new component implementations Composition of applications components & CIAO plug-ins CIAO helps instantiating application processes MDA tool suite UML modeling using GME Analysis & synthesis tools Enhancement to GME tool Uses MDA standards-based approach DARPA PCES program seeks solutions to integrate MIC with DRE Middleware Contact Douglas Schmidt

HPEC’02 CoSMIC 13 Summary of Ongoing Work RT/CCM (CIAO) being implemented at Washington University & Vanderbilt University DP-CORBA being implemented jointly between Vanderbilt University & UC Irvine CoSMIC tool suite, MRB being developed at Vanderbilt University All results will be available as open- source software deuce.doc.wustl.edu/CIAO

HPEC’02 CoSMIC 14 Benefits of Integrating MIC & DRE Middleware Large portions of application code can be composed from prevalidated, reusable middleware components. Helps in the rapid assembling and deployment of applications in the face of changing business or government rules and procedures. Makes middleware more robust by automating the configuration of QoS-critical aspects, such as concurrency, distributions, security, and dependability MIC helps bridge the interoperability problems between different middleware for which no standard solutions exist.

HPEC’02 CoSMIC 15 DRE Middleware Relationship with HPEC GRID Grid Challenges Tight coupling with grid infrastructure middleware (GIM) Accidental complexities of assembling & deploying grid applications Difficulties in resource & QoS assurance Grid Characteristics Simultaneous multiple QoS properties Multiple resources from multiple providers Middleware Examples: Globus, ICENI, Legion Applying Standard Real-Time & Data Parallel CORBA Enhances HPEC Extends Current Grid Capabilities Leverages Model Integrated Computing Applying Standard Real-Time & Data Parallel CORBA Enhances HPEC Extends Current Grid Capabilities Leverages Model Integrated Computing

HPEC’02 CoSMIC 16 Concluding Remarks DRE application development challenges resolved by combining MIC/MDA & QoS- enabled component middleware The CoSMIC & CIAO projects are applying MIC/MDA to support DRE CORBA-based HPEC applications