January 2002FAST 2002 WIP Presentation1 The Armada framework for parallel I/O on computational grids Ron Oldfield and David Kotz Department of Computer.

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Presentation transcript:

January 2002FAST 2002 WIP Presentation1 The Armada framework for parallel I/O on computational grids Ron Oldfield and David Kotz Department of Computer Science Dartmouth College

January 2002FAST 2002 WIP Presentation2 Introduction Must use large remote datasets Often computationally intensive Datasets often need pre- and/or post-processing Examples –Climate modeling (EOS-DAS) –Astronomy (Digital Sky Surveys) –Comp. Biology (Computed MicroTomography) –Computational physics Flexibility –Application control of the interface –Application control of system policies (caching, data-dist., …) Performance –Parallel data transfers. –Remote execution of user code (e.g., filtering, transforms, compression, encryption) Computational Grids: geographically distributed networks of heterogeneous computer systems and devices. Data-intensive grid applications I/O system requirements

January 2002FAST 2002 WIP Presentation3 Armada Flexible design, based on stackable file systems. Applications access data through a graph of “ships” called an “armada”. Requests travel toward data servers. Data is pushed toward clients for reads, pulled toward servers for writes. The armada abstracts details of the I/O system –Caching, filtering, data distribution from data provider added by application file dist clients on site A filter data segments on site B file dist replica data segments from site C API data flow An I/O framework for data-intensive grid applications

January 2002FAST 2002 WIP Presentation4 Improving Performance file dist clients on site A filter data segments on site B file dist replica data segments from site C API dist clients on site A file filter data segments on site B dist data segments from site C API file filter file filter file filter file filter replica combine replica

January 2002FAST 2002 WIP Presentation5 In progress… Automate graph restructuring. –Formalize rules and algorithms Develop placement algorithms. –Requires detailed information on ship requirements and available resources. Performance monitoring and analysis. Contact Information Ron Oldfield David Kotz