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Buddy Compiler Open Projects

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Prathamesh Tagore edited this page Mar 1, 2022 · 8 revisions

Buddy Compiler Open Projects

Currently, we provide 4 open projects in the following two directions.

Domain-specific Compiler

  • Description

We want to introduce the following 3 domain-specific MLIR dialects in the buddy compiler: Digital Image Processing (DIP), Audio Signal Processing (ASP), and Point Cloud (PC). Participants can choose 1~2 operations in a specific dialect to contribute. All projects in this direction will have a similar workflow.

(1) Data Structure Definition: Participants should add domain-specific data structure to interoperate with MLIR memory reference C/C++ data structure. For example, the MemRef constructor can work with OpenCV's Mat data structure (see here for more details).

(2) Operation Implementation: Participants should define their chosen operations in the specific dialect and implement their respective lowering passes using MLIR.

(3) Evaluation: Participants should register their created operation's use case in buddy benchmark and evaluate end-to-end cases against SOTA works in their respective domain. For example, we compare the Buddy Corr2D and OpenCV Filter2D in our benchmark framework (see here for more details).

Project 1: Adding Morphological Transformations in DIP Dialect.

There are 7 morphological operations which can be implemented for this project: Erosion, Dilation, Opening, Closing, Morphological Gradient, Top Hat, and Black Hat.

  • Expected outcomes: 1～2 morphological transformation operations and lowering passes.
  • Skills required: Excellent C/C++ skills, basic understanding of MLIR, Image Processing domain knowledge
  • Possible mentors: Hongbin Zhang, Prathamesh Tagore
  • Duration: 175 hours for each operation
  • Difficulty rating: Hard

Project 2: Adding Noise Suppression Operation in ASP Dialect.

Participants should add noise suppression operation and related end-to-end support for noise suppression cases.

  • Expected outcomes: noise suppression operations and lowering passes.
  • Skills required: Excellent C/C++ skills, basic understanding of MLIR, Audio Processing domain knowledge
  • Possible mentors: Hongbin Zhang
  • Duration: 175 hours for each operation
  • Difficulty rating: Hard

Project 3: Adding Convolution Operation in PC Dialect.

Participants should add point cloud specific convolution operation and related end-to-end support.

  • Expected outcomes: point cloud specific convolution operation and lowering pass.

  • Skills required: Excellent C/C++ skills, basic understanding of MLIR, basic domain knowledge

  • Possible mentors: Hongbin Zhang

  • Duration: 175 hours for each operation

  • Difficulty rating: Hard

Performance Optimization using Vectorization

Project 4: Vectorizing Convolution or GEMM Operations.

  • Description: Optimize existing convolution and GEMM operations using vectorization. You can refer to the algorithm here.
  • Expected outcomes: A vectorized convolution or a vectorized GEMM operation.
  • Skills required: Good C++ coding skills, basic understanding of MLIR and vectorization.
  • Possible mentors: Liutong Han, Hongbin Zhang
  • Duration: 175 hours for each operator (convolution/GEMM), 350 hours for both
  • Difficulty rating: Hard
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