High-level Adaptive Program optimization with ADapt

1. Michael J. Voss and Rudolf Eigenmann PPoPP, ‘01 (Presented by Kanad Sinha) High-level Adaptive Program optimization with ADapt

2. Agenda • Motivation • General choices for adaptive optimization • ADAPT • The Architecture • The Language • An example • Results

3. Motivation 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.

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

5. 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

6. 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 …

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

8. 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

9. ADAPT – The Architecture

10. 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

11. 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

12. ADAPT – The Architecture

13. 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

14. ADAPT – The Architecture Optimization process outside critical path/decoupled from execution

15. 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.

16. ADAPT – An example

17. ADAPT – An example • Initialize some variables • Constraints • Interface to tool to be used • This block defines the heuristic

18. ADAPT – An example

19. ADAPT - Results • Test Machines: 6 core Sun ULTRA Enterprise 4000, single-core Pentium II Linux workstation

20. 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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