Agent-based Resource Management for Grid Computing Junwei Cao University of Warwick May 2002

Introduction Ten years research on high performance computing at Warwick: Performance evaluation Local grid scheduling Global grid management Collaborations with: NASA Ames Research Centre Los Alamos National Laboratory IBM T J Watson Research Centre

Agents in Context Grid Users PACE Application Tools Global Grid Management - Agents Local Grid Schedulers PACE Performance Evaluation Engine Grid Resources PACE Resource Tools

Challenges Scalability. A grid has the potential to encompass a large number of high performance computing resources. Adaptability. A grid is a dynamic environment where performance of grid resources are changing over time.

A4 Methodology Agent structure Agent hierarchy Service advertisement Communication layer Decision-making layer Local management layer Agent hierarchy Service advertisement Service discovery Agent capability tables A User A

Optimisation Strategies Advertisement Data-push & data-pull Periodic & event-driven Discovery Local services Services in ACTs Lower or upper agents Optimisation Modelling Simulation M A User A A A A

A Case Study sweep3d fft improc closure jacobi memsort cpi S1 S2 S4 S3 (SGIOrigin2000, 16) S2 S4 (SunUltra10, 16) S3 S5 (SunUltra5, 16) S6 S12 (SunSPARCstation2, 16) S11 S8 (SunUltra1, 16) S7 S10 S9 sweep3d fft improc closure jacobi memsort cpi

Experiment 1 FIFO

Experiment 1 FIFO

Experiment 2 FIFO

Discovery Speed & Efficiency No advertisement: Low speed Low efficiency Reasonable advertisement: High speed High efficiency Discovery efficiency (*100) Too much advertisement: Very high speed Very low efficiency

Conclusions A hierarchy of homogenous agents Reconfigurable using different optimisation strategies Step-by-step service advertisement and discovery among agents Quantitative performance evaluation of agent behaviours

Future Work Use of heuristic iterative algorithms for local grid scheduling Integrating agents with grid tools, e.g. Globus, Condor, and NWS More than discovery, enabling automated negotiation and coordination Dynamic performance tuning of agent behaviours