Transactional Event Profiling in a Best Effort

HTMMatthew Gaudet

Supervisor: José Nelson Amaral (University of Alberta)

Collaborators: Amy Wang (IBM Toronto), Peng Wu (IBM TJ Watson)

The Story.

Transactions Aborts Serializations

1042 200 10

1000 Aborts 1000 Aborts

1 abort / second 1000 aborts / second

We need a pair of:

X-Ray Specs

Event Profiling

AnalyzersRuntime

Hardware

Program

Log FileInstrumented

AnalyzersLimited only by the power of your

Peeking into execution:

50000 cycles = 0.00003125 seconds

Seeing Rates

As they change

Which transactions are active?

Real TX Length Distributions

Details matter

LR Mode

SR Mode

Probe effects

1 2 4 8 16 32 640%

5%

10%

15%

20%

25%

30%

35%

40%

genomevacation_high

1 2 4 8 16 32 640%

5%

10%

15%

20%

25%

30%

35%

40%

genome

Using this

When? Too little?

Bad performance

Too Much? Bad

performance

Want to improve performance on BG/Q

(Judicious) Serialization

Solution: Runtime Adaptation

Understanding What’s going on?

Solution:

Future Work

• The ability to zoom and explore log files, like Visualizing Transactions

• Support for longer, larger programs: In memory compression, partial log-dumps.

Conclusion

1. Event Logging provides a useful view of transactional execution