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Flexible Matching: Explore and reveal accelerator-supported workloads in Deep Learning Models

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flexmatch

Flexible Matching via Equality Saturation

Workflow (Deprecated)

  1. Having patterns defined in Relay
  2. Run EqSat on each pattern and get the corresponding EGraph
  3. Pattern match on a given model using EGraphMatcher
  4. Annotate matched region with BYOC-style function annotations for the codegen

Utilities

Note: Please run cargo build in the flexmatch directory before using the utilities there.

  • flexmatch: Rust interfaces that call glenside and apis in (my fork of) egg
  • tests/run_eqsat
    • Takes a relay source file, an output file name and config(s) (under configs/)
    • Run equality saturation on the given model with respect to rewrite rules in configs
    • Example: python3 run_eqsat.py models/resmlp.relay resmlp im2col-rewrites linear-rewrites
  • tests/compile_model
    • Takes the relay source file, the output model and eclass analysis data json from EqSat
    • Compiles the rewritten model back to a relay executable model and saves to a file
    • Optional argument: --debug; instead of inserting accelerator calls, if this argument is passed, the equivalent relay function will be generated
    • Example: python3 compile_model.py models/resmlp.relay resmlp-rewritten.relay resmlp-rewritten.json resmlp-data.json linear-rewrites im2col-rewrites --debug

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Flexible Matching: Explore and reveal accelerator-supported workloads in Deep Learning Models

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