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Statistical Selection of Compiler OptionsPowerPoint Presentation

Statistical Selection of Compiler Options

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Statistical Selection of Compiler Options

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Statistical Selectionof Compiler Options

R.P.J. Pinkers

P.M.W. Knijnenburg

M. Haneda

H.A.G. Wijshoff

- Modern compilers contain dozens of options.
- Options can positively or negatively interfere.
- Optimal setting of those options depends on application as well as target architecture.
- Standard –Ox settings produce sub-optimal results.
- We propose almost automatic iterative procedure to select options for a given application and architecture based on statistical analysis

- If there are N options or factors, the full optimization space contains 2N combinations.
- This space is called afull factorial design.
- A fractional factorial design is a subset of the full factorial design.
- An Orthogonal Array (OA) or Taguchi design is a well-known approach to fractional factorial designs.
- An OA allows us to determine the effect of a factor in the presence of other factors using a reduced space.

- OA is N x k matrix of zeroes and ones.
- The columns are interpreted as options.
- Each row defines a compiler setting.
- An OA has the property that two arbitrary columns contain the patterns
equally often.

- Each option Oi is turned on and off equally often.
- If Oi is turned on, then each other option Oj is turned on and off equally often.

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- An OA allows us to calculate the main effect of options.
- The main effect of an option Oi wrt an OA A is defined as
where s denotes a row in A and T(s) denotes the execution time of the program when compiles with setting s.

- Execution times are given in cycles or seconds.
- Effects of options for different benchmarks cannot be compared easily.
- We define relative effect of an option Oi as

- An option can improve or degrade performance.
- The main effect is always positive and does not distinguish between improvement or degradation.
- We define the improvement of an option Oi wrt an OA A as

Repeat:

- Compile application with each row from A as compiler setting and execute optimized application.
- Compute effect of each option.
- If effect is larger than threshold of 10%
- if option has positive improvement, switch option on
- else switch option off.

- Construct new OA A by dropping columns corresponding to selected options.
until all options are set

- SimpleScalar simulator with GCC 2.6.3.
- Contains 19 options divided in 14 factors
- 6 SPEC95 benchmarks.

- We have proposed a method based on statistical analysis of the effect of options using Orthogonal Arrays.
- Method uses (almost) no knowledge of compiler.
- Can be implemented as a simple driver on top of any compiler.
- Significant improvement can be obtained by automatically tuning compiler options over standard optimization settings.