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Migration Cost Aware Task Scheduling

Migration Cost Aware Task Scheduling. 18-743 Milestone Shraddha Joshi, Brian Osbun 10/24/2013. Outline. Problem description Approach Milestone I Methodology Results Observations Future Work. Problem Description. Dynamic schedulers allow task migration during program execution

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Migration Cost Aware Task Scheduling

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  1. Migration Cost Aware Task Scheduling 18-743 Milestone Shraddha Joshi, Brian Osbun 10/24/2013

  2. Outline • Problem description • Approach • Milestone I • Methodology • Results • Observations • Future Work

  3. Problem Description • Dynamic schedulers allow task migration during program execution • Migrating threads to new cores can have hidden costs • Cold cache misses • Overhead of moving architectural state • Congestion on interconnect during transfer • Most task schedulers ignore migration overhead • Problem statement: quantify and consider the task migration cost when evaluating scheduling possibilities

  4. Approach • Architectural transfer is essentially fixed cost • Can be modeled independently • Cache effects have a larger and variable cost • Published theory requires static analysis* • Determination of “useful” blocks in cache • Reaching memory blocks (RMB): all blocks that may be in cache at a point • Live memory blocks (LMB): all blocks that may be referenced before eviction • Usefulness is intersection of RMB and LMB • Dynamic analysis • Need prediction! • For now: everything’s useful! *Source-Hardy et. al. Estimation of Cache Related Migration Delays for Multi-Core Processors with Shared Instruction Caches

  5. Milestone I • To be able to quantify migration cost in terms of a metric • Our predictor: past cache accesses • Our prediction: future cache misses

  6. Methodology • Sniper simulation framework • Clustered architecture • Homogeneous cores • Clustered L1 caches (shared by 4 cores) • Shared L2 cache • Two benchmarks • Radix (SPLASH-2) (compute intensive) • x264 (PARSEC) (memory intensive) • Variables • Time interval before and after migration • Cache size and parameters

  7. Results

  8. Results

  9. Observations • Large cost variance between applications • Compute-intensive v. memory-intensive • Radix: 0.115 accesses per instruction • x264: 0.368 accesses per instruction • Some sensitivity to cache parameters • Smaller cache may evict contents anyway

  10. Future Work • Refine accuracy of cost mechanism • Correlate future cost with past predictors • Incorporate migration cost metric into scheduling algorithm

  11. Q&A

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