Andrei Goldchleger, Fabio Kon, Alfredo Goldman and Marcelo Finger University of São.

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Presentation transcript:

Andrei Goldchleger, Fabio Kon, Alfredo Goldman and Marcelo Finger University of São Paulo, Brazil InteGrade: Object-Oriented Grid Middleware Leveraging Idle Computing Power of Desktop Machines

2 InteGrade: Description Middleware to build a grid of commodity machines Desktop users (Resource Providers) export their resources into the grid Grid applications use only idle resources Advantages over traditional dedicated clusters of commodity hardware

3 Based on Distributed Object Oriented Technology (CORBA) Preserves Resource Provider’s QoS at all costs Supports a wide Range of Parallel Applications Usage Pattern Collection and Analysis InteGrade: Key Features

4 User Level Scheduler (DSRT) Lightweight ORB Configurable Resource Sharing (Optional) Feature: Preserves Resource Provider’s QoS

5 Enhances scheduling by offering an idea of resource usage Usage Data regarding short intervals (e.g. 5 min.) is collected Data is grouped in larger intervals called Periods Clustering Algorithms Applied to data will derive Behavioral Categories (e.g. night, lunch- break, week-days, etc) Each machine will have a schedule representing its resources availability throughout the week Feature: Usage Pattern Collection and Analysis

6 Often unsupported by other grid initiatives, especially ones that make opportunistic use of shared resources –Normally parallel applications must have little or even no communication between the application nodes InteGrade’s architecture addresses those needs Network information about lines interconnecting nodes must be available Feature: Support for a Wide Range of Parallel Applications

7 Usage Pattern Collection and Analysis provides hints, minimizing checkpointing situations Checkpointing for sequential applications – Must be machine and OS independent Progress of parallel applications is more difficult to ensure Possible solution: Use BSP as parallel application model Feature: Ensures Application Progress

8 Architecture: Intra- Cluster LRM - Local Resource Manager GRM - Global Resource Manager

9 Architecture: Intra- Cluster LUPA - Local Usage Pattern Analyser GUPA - Global Usage Pattern Analyser

10 Architecture: Intra- Cluster NCC - Node Control Center ASCT - Application Submission and Control Tool

11 Related Work Globus (Argonne National Labs / U. of Chicago / USC) –Does not focus on QoS-preserving utilization of desktop machines –InteGrade uses CORBA and OO design Legion (U. of Virginia) –Proprietary distributed object model –InteGrade has deeper focus on idle resource management and desktop machines

12 Condor (U. of Wisconsin-Madison) – Limitations regarding support for parallel applications (U. of California Berkeley) –Hard-coded application –No communication between application nodes BOINC (U. of California Berkeley) – Limited support for parallel applications Related Work (continued)

13 Implementation Status Already Implemented: –Intra-Cluster Information Update Protocol –Intra-Cluster Execution Protocol (non- parallel applications only) Software used: –GRM: JacORB –LRM: C++ using Orbil

14 Implementation Status: ClusterView

15 Project Information Website: Source code available (anonymous CVS checkout & web front end) Increasing number of students working on the project Initial working version expected for the end of 2003