michael j voss and rudolf eigenmann ppopp 01 presented by kanad sinha
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High-level Adaptive Program optimization with ADapt

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Michael J. Voss and Rudolf Eigenmann PPoPP, ‘01 (Presented by Kanad Sinha). High-level Adaptive Program optimization with ADapt. Agenda. Motivation General choices for adaptive optimization ADAPT The Architecture The Language An example Results. Motivation.

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Presentation Transcript
  • Motivation
  • General choices for adaptive optimization
    • The Architecture
    • The Language
    • An example
  • Results

There’s only so much optimization that can be performed at compile-time.

  • Have to generate code for generic system models – make compile-time assumptions that may be sensitive to input, unknown till runtime.
  • Convergence of technologies – difficult to generate common binary to exploit individual system characteristics.

Possible solution?

“Use of adaptive and dynamic optimization paradigms, where optimization is performed at runtime when complete system and input knowledge is available.”

ways to go about it
Ways to go about it…
  • Choose from statically generated code-variants

+ Easy

-May not result in max possible optimization

- Can result in code explosion

  • Parameterization

+ Single copy of source

- May still not result in max possible optimization

  • Dynamic compilation

+ Complete input and system knowledge – max optimization possible

- Considerable runtime overhead

adapt features
ADAPT : Features
  • Automated De-Coupled Adaptive Program Optimization
  • Generic framework, which leverages existing tools
  • Uses a domain-specific language, AL, by which adaptive techniques can be specified

adapt features contd
ADAPT : Features (contd.)
  • Supports dynamic compilation and parameterization
  • Enables optimizations through “runtime sampling”
  • Facilitates an iterative modification and search approach
adapt prelude
ADAPT :Prelude

3 functions of a dynamic/adaptive optimization system

  • Evaluate effectiveness of particular optimization for current input & system information
  • Apply optimization if profitable
  • Re-evaluate applied optimizations and tune according current runtime conditions
adapt the architecture1
ADAPT – The Architecture

Runtime system consists of:

  • Modified version of application
  • Remote optimizer
    • has source code
    • description of target machine
    • stand-alone tools & compilers
  • Local optimizer
    • agent of remote-optimizer on system
    • detects hot-spots
    • tracks multiple interval contexts (here, loop bounds)
    • runs in separate thread

Optimization and execution truly asynchronous

adapt the architecture2
ADAPT – The Architecture
  • LO invokes RO, when hotspot detected
  • RO tunes the interval using available tools, according to user-specified heuristics
  • RPC returns
  • If new code available, dynamically link to application as the new best/experimental version, depending on RO’s message
adapt the architecture4
ADAPT – The Architecture
  • Candidate code sections have 2 control flow paths
    • through best known version
    • through experimental version

Each of these can be replaced dynamically

  • Flag indicates which version to execute
  • Monitor experimental versions of each context
    • collected data used as feedback
    • if better, swap with best known version
adapt the architecture5
ADAPT – The Architecture

Optimization process outside critical path/decoupled from execution

adapt the language
ADAPT – The Language
  • ADAPT Language (AL) *
  • Features:
    • Uses an LL1 grammar => simple parser
    • Domain specific language with C-style format
    • Defines reserved words that at runtime contain useful input data and system information

* “A full description of ADAPT language is beyond the scope of this paper”, and by extension, this presentation.

adapt an example1
ADAPT – An example
  • Initialize some variables
  • Constraints
  • Interface to tool to be used
  • This block defines the heuristic
adapt results
ADAPT - Results
  • Test Machines: 6 core Sun ULTRA Enterprise 4000, single-core Pentium II Linux workstation
today s take aways
Today’s Take-aways
  • There’s advantage in doing runtime optimization
  • Can be applied to general-purpose programs as well
  • For full-blown runtime optimization, need to move optimization process outside the critical path

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