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Constraint Programming Techniques for Optimal Instruction Scheduling

Modern processors have multiple pipelined functional units
and can issue more than one instruction per clock cycle. This
puts great pressure on the instruction scheduling phase in
a compiler to expose maximum instruction level parallelism.
Basic blocks and superblocks are commonly used regions of code
in a program for instruction scheduling. Instruction scheduling
coupled with register allocation is also a well studied problem
to produce better machine code. Scheduling basic blocks and
superblocks optimally with or with out register allocation is
NP-complete, and is done sub-optimally in production compilers
using heuristic approaches. In this thesis, I present a
constraint programming approach to the superblock and basic
block instruction scheduling problems for both idealized and
realistic architectures. Basic block scheduling with register
allocation with no spilling allowed is also considered. My
models for both basic block and superblock scheduling are
optimal and fast enough to be incorporated into production
compilers. I experimentally evaluated my optimal schedulers on
the SPEC 2000 integer and floating point benchmarks. On this
benchmark suite, the optimal schedulers were very robust and
scaled to the largest basic blocks and superblocks. Depending
on the architectural model, between 99.991\% to 99.999\% of all
basic blocks and superblocks were solved to optimality. The
schedulers were able to routinely solve the largest blocks,
including blocks with up to 2600 instructions. My results compare
favorably to the best previous optimal approaches, which are based
on integer programming and enumeration.
My approach for basic block scheduling without allowing spilling was good
enough to solve 97.496\% of all basic blocks in the SPEC 2000
benchmark. The approach was able to solve basic blocks as
large as 50 instructions for both idealized and realistic
architectures within reasonable time limits.
Again, my results compare favorably to recent work
on optimal integrated code generation, which is
based on integer programming.
Date03 1900
CreatorsMalik, Abid
Source SetsUniversity of Waterloo Electronic Theses Repository
Detected LanguageEnglish
TypeThesis or Dissertation

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