1. Workshop on HPC in India Grid Middleware for High Performance Computing Sathish Vadhiyar Grid Applications Research Lab (GARL) Supercomputer Education and Research Centre (SERC) Indian Institute of Science (IISc) Bangalore - 560012 ATIP 1 st Workshop on HPC in India @ SC-09

2. Sathish VadhiyarATIP 1 st Workshop on HPC in India @ SC-092 Grid Applications Research Lab  Grid and Parallel Computing with primary focus on  developing grid applications,  building strategies for checkpointing, migration, rescheduling, and fault-tolerance for parallel applications on grid systems, and  performance modeling of parallel applications on grids

3. Sathish VadhiyarATIP 1 st Workshop on HPC in India @ SC-093 Motivation  Developing solutions for deployment and use of large-scale scientific applications on grids  Will result in exploration of large- sized problems and long-running applications

4. Sathish VadhiyarATIP 1 st Workshop on HPC in India @ SC-094 Grid Applications Climate Modeling  Enable efficient executions of long-running climate modeling simulations on grid systems with the objective of solving climate science problems  Community Climate System Model (CCSM) – a multi- component global general circulation model  Analyzed the benefits of executing different components with checkpointing and rescheduling in different batch systems of a grid with a novel execution model CCSM

5. Sathish VadhiyarATIP 1 st Workshop on HPC in India @ SC-095 Grid Applications Climate Modeling – General Idea IJHPCA, FGCS  Job submission to a batch system incurs queue waiting time  Waiting time depends on processor requirements  How about decomposing a job into small subjobs with small processor requirements and submitting the subjobs to multiple batch systems of a grid?  Efficiency depends on effective system utilization using checkpointing, migration and rescheduling  Leads to 55% average increase in throughput Novel Execution Model

6. Sathish VadhiyarATIP 1 st Workshop on HPC in India @ SC-096  Predictions of future sequences in an evolutionary tree important for drug discovery, pharmaceutical research and disease control  Different ways of an ancestor sequence to transform to a progeny sequence  Formulated as a search-space exploration problem and used computational grids for explorations of the huge space of possible mutations  Used popular mutations to predict future evolutionary paths.  Performed predictions for hiv sequences and other protein sequences  40% better than random methods Grid Applications DNA Sequence Evolutions JPDC, escience 2009 Master-Worker Architecture for Analyzing Mutations 40% Better Predictions

7. Sathish VadhiyarATIP 1 st Workshop on HPC in India @ SC-097 Rescheduling  It is necessary to adapt application execution to grid resource and application dynamics  SRS – a checkpointing library for malleable applications  Can allow processor reconfiguration between migrations  Supports different data distributions, storage infrastructure, active migration and fault tolerance

8. Sathish VadhiyarATIP 1 st Workshop on HPC in India @ SC-098 1 2 3 4 5 6 7 8 9 10 11 12 13.. N Cluster-1 23 1 2 3 4 5 6 7 8 9 10 11 12 13.. N 1 2 3 4 5 6 7 8 9 10 11 12 13.. N Interval 1 (t 1 ) Interval 2 (t 2 ) Interval 3 (t 3 ) Interval i (t i )  To find {I 1, I 2, …,I Lopt } such that is minimized where L opt – number of intervals; t i – predicted execution time of each interval; rcost – rescheduling cost  Developed 3 novel algorithms for deriving a rescheduling plan  Incremental algorithm, division heuristic and genetic algorithm  Given a parallel application consisting of multiple phases and given a set of resources, the problem is to derive a rescheduling plan  Where to execute the different phases and when to migrate/reschedule Application Phases Division heuristic Resheduling Strategies

9. Sathish VadhiyarATIP 1 st Workshop on HPC in India @ SC-099 Rescheduling Strategies  Performed experiments with five large- scale multi-phase parallel applications  Molecular dynamics, n-body simulations, astrophysical gas dynamics, crack propagation, electromagnetics. Rescheduling MethodTime (hours) Incremental6.8 Division6.58 Genetic5.97 Single Schedule68.77 Huge Benefits due to Rescheduling

10. Sathish VadhiyarATIP 1 st Workshop on HPC in India @ SC-0910 Performance Modeling JPDC,CPE  It is imperative to automatically derive “knowledge” (performance characteristics) of applications  Can be used for effective mapping of applications to resources  Built techniques for automatically deriving performance model functions for predicting execution costs of parallel applications on grids  First effort to deal with load changes during application executions  Less than 30% modeling errors – best reported for non-dedicated systems  Have also developed novel scheduling algorithms that use the model functions  Generates 80% better schedules than existing approaches Box Elimination (BE) [red bars] 50-80% more efficient! Performance Model Accuracy for Parallel QR Scheduling Method Scheduling Results

11. Sathish VadhiyarATIP 1 st Workshop on HPC in India @ SC-0911 Grid Middleware  Created a grid middleware for parallel multi-phase applications with rescheduling capabilities  Have successfully run multi-phase applications on grid consisting of multiple batch and interactive clusters in two geographically distributed sites  Also created a grid middleware for multi-component applications for coordinating the executions of the components on the different systems Grid Middleware for Multi-Phase Applications Grid Middleware for Multi-Component Applications

12. Sathish VadhiyarATIP 1 st Workshop on HPC in India @ SC-0912 Other Research  Checkpointing Interval Selection  For efficient execution in the presence of failures  A Markov Model consisting of 3 kinds of states for performance prediction  Extensive simulations with 9-year real supercomputer failure traces on 8 parallel systems, 3 rescheduling policies, and 3 parallel applications  Our model’s checkpointing intervals lead to high amount of useful work by the applications in the presence of failures  Compiler-aided checkpointing instrumentation  A source-to-source precompiler for automatic insertion of checkpointing calls  Performs live-variable analysis for determining data and wrappers for finding data sizes  Can handle parallel applications with block-distribution (molecular dynamics)

13. Sathish VadhiyarATIP 1 st Workshop on HPC in India @ SC-0913 Summary  Primary endeavor to aid scientific advancement in different domain areas using grid systems  Grid research in two different application areas that resulted in significant application benefits using grids  Contributed novel scheduling and rescheduling algorithms, performance modeling strategies and robust grid middleware for use by scientific community

14. Sathish VadhiyarATIP 1 st Workshop on HPC in India @ SC-0914 Areas of Collaborations  Scalability of large-scale and peta applications  Fault tolerance in high performance systems  Setting up Indo-US grids  Grid middleware collaborations