7 april SP3.1: High-Performance Distributed Computing The KOALA grid scheduler and the Ibis Java-centric grid middleware Dick Epema Catalin Dumitrescu, Alex Iosup, Hashim Mohamed, Ozan Sonmez Henri Bal, Thilo Kielmann, Jason Maassen, Rob van Nieuwpoort, et al.

7 april TUDelft: KOALA KOALA is a multicluster/grid scheduler Main goals of KOALA: Load sharing of jobs across the sites in a grid:  Automatic resource selection Co-allocation of jobs across the sites in a grid:  In order to use more resources  As dictated by the structure of applications (e.g., simulation/visualization) KOALA has been released on the DAS in september 2005

7 april KOALA: Scheduling global queue LS local queues with local schedulers local jobs global job KOALA clusters LS load sharing co-allocation

7 april VU: Ibis Ibis: Java-centric grid middleware for distributed supercomputing Satin: divide-and-conquer parallelism in grids GAT: Grid Application Toolkit Implemented several Java applications from SP 1.3 (Medical/Vumc) SP 1.6 (Telescience/AMOLF) SP 2.1 (iPSE/ UvA) SP 2.2 (AID/UvA)

7 april Ibis: Grid’5000 experiments Grid’5000: French computer science Grid with 2000 nodes at 9 sites Used Grid’5000 for Running Satin applications Nqueens challenge (2 nd Grid Plugtest) Ibis/Satin/GAT application running on 960 nodes at 6 sites, ~85% efficiency Large-scale peer-to-peer experiments using Zorilla (Gnutella-like latency-based flooding of ads for joining a compution)

7 april KOALA feature 1: the Runners There are many ugly application types out there No way they can all be supported by a single scheduler Solution: runners (=interface modules) Currently supported: Any type of single-component job MPI/DUROC jobs Ibis jobs HOC applications runner

7 april KOALA feature 2: the policies Originally supported co-allocation policies: Worst-Fit: balance job components across sites Close-to-Files: take into account the locations of input files to minimize transfer times Different application types require different ways of component placement So: Modular structure with pluggable policies Take into account internal communication structure of applications

7 april KOALA feature 3: support for HOCs Higher-Order Components: Pre-packaged software components with generic patterns of parallel behavior Patterns: master-worker, pipelines, wavefront Benefits: Facilitates parallel programming in grids Enables user-transparent scheduling in grids Most important additional middleware: Translation layer that builds a performance model from the HOC patterns and the user-supplied application parameters Supported by KOALA (with Univ. of Münster) Initial results: up to 50% reduction in runtimes

7 april TUDelft: GrenchMark GrenchMark is a flexible grid workload generator, submitter, and results analyzer Main goals of GrenchMark: Generic workload definition for many types of workloads and application characteristics Grid workload generation Submitting and replaying workloads in different grid settings GrenchMark released in november 2005 GrenchMark used to test KOALA

7 april KOALA future (1) Support for more applications types, e.g., Workflows Parameter sweep applications Communication-aware and application-aware scheduling policies: Take into account the communication pattern of applications when co-allocating Also schedule bandwidth (in DAS3) Better interface KOALA-local schedulers KOALA is too nice

7 april KOALA future (2) Peer-to-peer structure instead of hierarchical grid scheduler Support heterogeneity DAS3 DAS2 + DAS3 PoC DAS3 + Grid’5000

7 april DAS-3DAS-3 CPU’s R R R R R NOC KOALA and Ibis future

7 april Conclusions SP3.1 is well on track SP3.1 has delivered reliable software tools for everybody to use: KOALA/Grenchmark Ibis/Satin SP3.1 has a bright future Still many research challenges (Access to) great new heterogeneous testbeds

7 april More information Web sites:  general description  KOALA tutorial  papers grenchmark.st.ewi.tudelft.nl: grenchmark.st.ewi.tudelft.nl  general description  download  papers  Ibis distribution  documentation  papers