Coscheduling in Clusters: Is it a Viable Alternative

1
Coscheduling in Clusters Is it a Viable
Alternative?

• Gyu Sang Choi, Jin-Ha Kim, Deniz Ersoz, Andy B.
  Yoo, Chita R. Das
• Presented by Richard Huang

2
Outline

• Evaluation of scheduling alternatives
• Proposed HYBRID Coscheduling
• Evaluation
• Conclusions
• Discussion

3
Evaluation of Scheduling Alternatives

• Local Scheduling
• Processes of parallel job independently scheduled
• Batch Scheduling
• Most popular (Maui, PBS,etc.)
• Avoid memory swapping, but low utilization and
  high completion time
• Gang Scheduling
• All processes of job (gang) scheduled together
  for simultaneous execution
• Faster completion time, but global
  synchronization costs

4
Communication-Driven Coscheduling

• Dynamic Coscheduling (DCS)
• Uses incoming message to schedule processes for
  which messages are destined
• Spin Block (SB)
• Process waiting for message spins for fixed
  amount of time before blocking itself
• Periodic Boost (PB)
• Periodically boosts priority of process with
  un-consumed messages
• Co-ordinated Coscheduling (CC)
• Optimizes spinning time to improve performance at
  both sender and receiver

5
HYBRID Coscheduling

• Idea
• Combines merits of both gang scheduling and
  communication-driven coscheduling
• Coschedule ALL processes like gang scheduler
• Boost process priority during communication phase
• Issues
• How to differentiate between computation and
  communication phases?
• How to ensure fairness during boosting?

6
HYBRID Coscheduling

• Boost priority whenever parallel process enter
  collective communication phase
• Immediate blocking used at sender and receiver

7
Traditional and Generic Coscheduling Framework
8
Evaluation

• 16 node Linux cluster connected through 16-port
  Myrinet switch
• 100 mixed applications from NAS
• Two different job allocation
• PACKING contiguous nodes assigned to a job to
  reduce system fragmentation and increase system
  utilization
• NO PACKING parallel processes of job randomly
  allocated to available nodes in system

9
Performance Comparison
10
Observations

• Average performance gain for PACKING about 20
  compared to NO PACKING
• Under high load, big differences due to waiting
  times
• Under light load, difference in execution time
  more pronounced
• Batch scheduler has lowest execution time,
  followed by HYBRID
• HYBRID has lowest completion time among all
  scheduling schemes

11
Explanations

• HYBRID avoids unnecessary spinning
• process immediately blocked if communication
  operation is not complete
• HYBRID reduces communication delay
• process wake up immediately upon receipt of
  message (since its priority boosted)
• HYBRID avoids interrupt overheads
• Frequent interrupts from NIC to CPU to boost
  processs priority in CC, DCS, and PB
• HYBRID boosted only at beginning of an MPI
  collective communication
• HYBRID avoids global synchronization overhead
  like gang scheduling
• HYBRID follows implicit coscheduling

12
Other Results

• Completing jobs faster can lead to energy savings
  by using dynamic voltage scaling or shutting down
  machines

• Communication-driven coscheduling should deploy
  memory aware allocator to avoid expensive disk
  activities

13
Conclusions

• Can get significant performance improvement by
  using coscheduling mechanisms like HYBRID, SB, or
  CC
• Block-based scheduling techniques had better
  results because other processes in ready state
  can proceed
• HYBRID scheme is best performer and can be easily
  implemented on any platform with only
  modification in the message passing layer
• New techniques deployed on cluster should avoid
  expensive memory swapping
• Improved efficiency in scheduling algorithm can
  translate to better performance-energy ratio

14
Discussion

• Can it be true that blocking is always better
  than spinning?
• How likely is it to move away from batch
  scheduling in clusters and super computers?
• Do people try to save energy by improving
  scheduling algorithm?