What Programming LanguageCompiler Researchers should Know about Computer Architecture

1
What Programming Language/Compiler Researchers
should Know about Computer Architecture

• Lizy Kurian John
• Department of Electrical and Computer Engineering
• The University of Texas at Austin

2
Somebody once said

• Computers are dumb actors and compilers/programme
  rs are the master playwrights.

3
Computer Architecture Basics

• ISAs
• RISC vs CISC
• Assembly language coding
• Datapath (ALU) and controller
• Pipelining
• Caches
• Out of order execution
• Hennessy and Patterson architecture books

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Basics

• ILP
• DLP
• TLP
• Massive parallelism
• SIMD/MIMD
• VLIW
• Performance and Power metrics

Hennessy and Patterson architecture books ASPLOS,
ISCA, Micro, HPCA
5
The Bottomline

• Programming Language choice affects performance
  and power
• eg Java
• Compilers affect Performance and Power

6
A Java Hardware Interpreter

• Radhakrishnan, Ph. D 2000 (ISCA2000, ICS2001)
• This technique used by Nazomi Communications,
  Parthus (Chicory Systems)

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HardInt Performance

• Hard-Int performs consistently better than the
  interpreter
• In JIT mode, significant performance boost in 4
  of 5 applications.

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Compiler and Power
A
A
A
E
Cycle 1
Cycle 1
B
C
B
B
C
E
C
Cycle 2
Cycle 2
D
E
D
D
Cycle 3
Cycle 3
F
F
F
Cycle 4
Cycle 4
DDG
Peak Power 2 Energy 6
Peak Power 3 Energy 6
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Valluri et al 2001 HPCA workshop

• Quantitative Study
• Influence of state-of-the-art optimizations on
  energy and power of the processor examined
• Optimizations studied
• Standard O1 to O4 of DEC Alphas cc compiler
• Four individual optimizations simple
  basic-block instruction scheduling, loop
  unrolling, function inlining, and aggressive
  global scheduling

10
Standard Optimizations on Power
11
Somebody once said

• Computers are dumb actors and compilers/programme
  rs are the master playwrights.

12
A large part of modern out of order processors

• is hardware that could have been eliminated if a
  good compiler existed.

13
Let me get more arrogant

• A large part of modern out of order processors
  was designed because
• computer architects thought compiler writers
  could not do a good job.

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Value Prediction

• Is a slap on your face
• Shen and Lipasti

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Value Locality

• Likelihood that an instructions computed result
  or a similar predictable result will occur soon
• Observation a limited set of unique values
  constitute majority of values produced and
  consumed during execution

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Load Value Locality
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Causes of value locality

• Data redundancy many 0s, sparse matrices, white
  space in files, empty cells in spread sheets
• Program constants
• Computed branches base address for jump tables
  is a run-time constant
• Virtual function calls involve code to load a
  function pointer can be constant

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Causes of value locality

• Memory alias resolution compiler conservatively
  generates code may contain stores that alias
  with loads
• Register spill code stores and subsequent loads
• Convergent algorithms convergence in parts of
  algorithms before global convergence
• Polling algorithms

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2 Extremist Views

• Anything that can be done in hardware should be
  done in hardware.
• Anything that can be done in software should be
  done in software.

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What do we need?

• The Dumb actor
• Or the
• The defiant actor who pays very little
  attention to the script

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Challenging all compiler writers

• The last 15 years was the defiant actors era
• What about the next 15? TLP, Multithreading,
  Parallelizing compilers Its time for a lot
  more dumb acting from the architects side.
• And its time for some good scriptwriting from
  the compiler writers side.

22
BACKUP
23
Compiler Optimzations

• cc - Native C compiler on Dec Alpha 21064 running
  OSF1 operating system
• gcc Used to study the effect of individual
  optimizations

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Std Optimizations Levels on cc

• -O0 No optimizations performed
• -O1 Local optimizations such as CSE, copy
  propagation, IVE etc
• -O2 Inline expansion of static procedures and
  global optimizations such as loop unrolling,
  instruction scheduling
• -O3 Inline expansion of global procedures
• -O4 s/w pipelining, loop vectorization etc

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Std Optimizations Levels on gcc

• -O0 No optimizations performed
• -O1 Local optimizations such as CSE, copy
  propagation, dead-code elimination etc
• -O2 aggressive instruction scheduling
• -O3 Inlining of procedures
• Almost same optimizations in each level of cc and
  gcc
• In cc and gcc, optimizations that increase ILP
  are in levels -O2, -O3, and -O4
• cc used where ever possible, gcc used used where
  specific hooks are required

NOTE
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Individual Optimizations

• Four gcc optimizations, all optimizations applied
  on top -O1
• -fschedule-insns local register allocation
  followed by basic-block list scheduling
• -fschedule-insns2 Postpass scheduling done
• -finline-functions Integrated all simple
  functions into their callers
• -funroll-loops Perform the optimization of loop
  unrolling

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Some observations

• Energy consumption reduces when of instructions
  is reduced, i.e., when the total work done is
  less, energy is less
• Power dissipation is directly proportional to IPC
  

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Observations (contd.)

• Function inlining was found to be good for both
  power and energy
• Unrolling was found to be good for energy
  consumption but bad for power dissipation

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MMX/SIMD

• Automatic usage of SIMD ISA still difficult 10
  years after introduction of MMX.

30
Standard Optimizations on Power (Contd)