2000-2001 NPACI Alpha Project Review: Cellular Microphysiology on the Data Grid

1. 2000-2001 NPACI Alpha Project Review: Cellular Microphysiology on the Data Grid Fran Berman, UCSD Tom Bartol, Salk Institute

2. “MCell” Alpha project • Project leaders: Terry Sejnowski, Salk Institute, Fran Berman, UCSD • Senior Participants: • Tom Bartol, Salk • Joel Stiles, CMU (leveraged) • Edwin Salpeter, Cornell (leveraged) • Jack Dongarra, Rich Wolski, U. of Tenn. • Mark Ellisman, UCSD NCMIR • Henri Casanova, UCSD CSE (leveraged)

3. MCell Alpha Goals • General goal:Implementation and deployment of MCell, a general Monte Carlo simulator of cellular microphysiology using NPACI high performance and distributed resources • Specific goals: • Develop a Grid-enabled version of MCell available to all MCell and NPACI users • Develop an MPI/Open MP version suitable for MPP platforms such as Blue Horizon • Perform large-scale runs necessary for new disciplinary results • Extend the prototype and tech transfer APST user-level middleware for deploying MCell and similar parameter sweep applications to NPACI partners

4. MCell Alpha Project • Previous Accomplishments • Prototype of Grid-enabled MCell code (via APST Grid middleware) developed • SW integrates NetSolve, AppLeS, NWS • Initial MCell runs performed on Blue Horizon • Agenda for this presentation: • Tom: What is MCell and what are its computational requirements? • Fran: How do we develop SW for performance-efficient distributed MCell runs? • FY 00-01 plans and feedback

5. Tom’s Presentation

6. Grid-enabled MCell • Previous work • Have developed prototype of APST (AppLeS Parameter Sweep Template) which can be used to deploy MCell in wide-area Grid environments • Includes mechanism for targeting available services at remote resources (NetSolve, Globus, GASS, IBP, NWS) • Have developed a Grid MCell performance model • Have developed performance-efficient Grid-oriented scheduling heuristics for MCell • NPACI Alpha Project Goals • Develop a Grid-enabled version of MCell with enhanced scheduling algorithms, I/O, and data storage model available targeted to MCell users and NPACI resources. • Extend the prototype and tech transfer APST user-level middleware for deploying MCell and similar parameter sweep applications to NPACI partners • Develop an MPI/Open MP version of MCell suitable for MPP platforms such as Blue Horizon • Perform large-scale runs necessary for new disciplinary results

7. Grid-enabled MCell • Have performed initial wide-area MCell runs using APST prototype • APST • APST = AppLeS Parameter Sweep Template • MCell used as driving application • Developed as user-level Grid middleware for scheduling and deploying MCell and other parameter sweep applications • Joint work with Henri Casanova • Research supported by NASA and NSF

8. Scheduling Issues for MCell • Large shared files may complicate the scheduling process • Post-processing must minimize file transfer time • Adaptive scheduling necessary to account for • dynamic environment

9. Computation Computation Scheduling Approach used for MCell • Contingency Scheduling: Allocation developed by dynamically generating a Gantt chart for scheduling unassigned tasks between scheduling events • Basic skeleton • Compute the next scheduling event • Create a Gantt Chart G • For each computation and file transfer currently underway, compute an estimate of its completion time and fill in the corresponding slots in G • Select a subset T of the tasks that have not started execution • Until each host has been assigned enough work, heuristically assign tasks to hosts, filling in slots in G • Implement schedule Network links Hosts(Cluster 1) Hosts(Cluster 2) Resources 1 2 1 2 1 2 Scheduling event Time Scheduling event G

10. scheduler API Workqueue Gantt chart heuristic algorithms Workqueue++ XSufferage MinMin Sufferage MaxMin actuate report actuate retrieve transport API execution API metadata API GASS IBP GRAM NetSolve NWS NFS Condor, Ninf, Legion,.. transfer execute query Legion IBP Globus Ninf Condor NWS NetSolve APST/MCell user-level middleware Command-line client APST/MCell Client interacts Controller triggers Scheduler APST/MCell Daemon Actuator Metadata Bookkeeper store Grid Resourcesand Middleware

11. MCell Computational Challenges • Support for large-scale distributed MCell runs • Support for large-scale parallel MCell runs • Execution of large-scale runs • Tech Transfer of APST for NPACI parameter sweep application developers User-level middleware facilitates use of Grid for wider class of users MCell algorithm and SW development allows for new disciplinary results

12. FY 00-01 Plans • Develop Grid-enabled MCell • Optimize scheduling strategy • Increase sensitivity of model to environmental constraints (data storage, I/O, post-processing, resource location) • Target SW to NPACI resources • Robustify and tech transfer more general APST user-level middleware to NPACI metasystem • Develop MPP-enabled MPI/OpenMP version of MCell • Adapt algorithm for performance in MPP environment • Develop MPP-enabled APST to efficiently deploy MCell tasks to parallel environments • Implement/deploy SW for large-scale Blue Horizon runs • Perform larger-scale runs necessary for new disciplinary results

13. Feedback • It would be easier to perform this work for NPACI if … • Allocation of NS thrust area computer time was more generous • Blue Horizon had larger scratch space • A rendering farm were available • Globus platform was more stable • NWS, NetSolve, and other services were more consistently available at NPACI partner sites