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Sin Ming Loo 1 , Simon Y. Foo 2

MAPLD 2004. A Methodology for System-on-a-Programmable-Chip Resources Utilization. Sin Ming Loo 1 , Simon Y. Foo 2. 1 { smloo@boisestate.edu } Electrical and Computer Engineering Department Boise State University Boise, Idaho 83725. 2 { foo@eng.fsu.edu }

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Sin Ming Loo 1 , Simon Y. Foo 2

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  1. MAPLD 2004 A Methodology for System-on-a-Programmable-Chip Resources Utilization Sin Ming Loo1, Simon Y. Foo2 1{smloo@boisestate.edu} Electrical and Computer Engineering Department Boise State University Boise, Idaho 83725 2{foo@eng.fsu.edu} Electrical and Computer Engineering Department Florida State University Tallahassee, Florida 32310

  2. Agenda • Reconfigurable Hardware • Reconfigurable System Design Model • Search Techniques • Problems Encountered and Lessons Learned • On-going Research • Summary F194/MAPLD 2004

  3. Configurable Logic Blocks(CLB) Input/Output Blocks (IOB) Embedded Block Memory (BRAM) Reconfigurable Hardware (RH) • Configured by the user after fabrication • Provides flexibility formally found only in software based systems • Eliminates the need to create custom hardware • Allows specialization and customization to meet the needs of the application F194/MAPLD 2004

  4. Task Specific Core (TSC) • Allows the application to be implemented in a more “optimal” fashion from a performance point of view • Best performance would occur if the application is constructed entirely with TSC • TSC implementation is most often highly concurrent • But, concurrency is not free! • TSC implementations usually consume enormous amounts of reconfigurable resources • RH is limited by size • Size limitation is unlikely to be solved by improvements in device technology • Due to expanding complexity of application problems F194/MAPLD 2004

  5. Space Time Trade-off • How to determine an effective balance between performance and resource utilization? • which portions must have concurrency? • which portions can be implemented sequentially? • How much concurrency can be employed without exceeding the available RH resources? F194/MAPLD 2004

  6. Methodology • Employs multiple Von Neumann style processing cores + high performance task specific modules • Allows task executes sequentially on Von Neumann type processing cores • Employs parallel processing style static scheduling • Insight gained through this problem can be extrapolated and extended to less deterministic problems F194/MAPLD 2004

  7. Task System Hardware Library Constraints Scheduler Task Schedule High-Level Hardware System Description Reconfigurable System Design Model (RSDM) • Apply scheduling theory to a pre-fabricated RH environment • The heart of this design model is a scheduler • Input to scheduler: • Hardware Library, Task System, Resource Constraints, Design Constraints • Scheduler produces: • Task Execution Schedule, High-Level Hardware System Description F194/MAPLD 2004

  8. Task System Hardware Library Constraints Scheduler Task Schedule High-Level Hardware System Description High-Level Hardware System Description • Specifies • the number and type of functional units used • number and type of communication core elements used • the necessary system topology F194/MAPLD 2004

  9. Computational Complexity • Hard problem! • To find the optimum solution, it requires (#PC + #TSC)noperations • For example, • A system with 100 tasks • Hardware Library has 3 PCs • Each task has two TSC implementations • Scheduling operation requires 0.5 nsec • 3 + 2)100 = 7.886x1069operations • For0.5 nsec/operation, it will require1.2507x1053yearsto find the optimum solution F194/MAPLD 2004

  10. Search Techniques • Search Algorithms • Random • Simulated Annealing • Genetic Algorithms (Found to be the most effective technique in finding a ‘good’ solution) • Others (depth-first, breadth-first, branch-and-bound, etc.) • Using synthetic task systems F194/MAPLD 2004

  11. Problems Encountered & Lessons Learned • Representative task systems for reconfigurable hardware scheduling (co-synthesis) research? • First-cut approach, synthetic task systems • Within reconfigurable hardware, especially Field-Programmable Gate Arrays, what percentage of resources should be utilized during scheduling • No applications specific information are used during scheduling F194/MAPLD 2004

  12. Application Specific Inputs • Designer knows the design/application the best • Needs to be able to take in designer’s view of tasks’ execution location • Mobility factor • Allow user to specify the execution location of a task, in IP processor or as TSC • All other tasks are scheduled around the ‘fixed tasks’ F194/MAPLD 2004

  13. On-going … • Collecting resources and performance (timing) data from real-world applications • Benchmark selected: MiBench, an embedded system benchmark • Synthetic task systems are being used to compare the scheduling algorithms F194/MAPLD 2004

  14. Summary • Presented a Reconfigurable System Design Model (RSDM) • Collected data is available at http://coen.boisestate.edu/smloo/rsdm F194/MAPLD 2004

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