Numba compatible RVSDG (Regionalized Value State Dependence Graph) utilities.
This repository contains Numba compatible utilities for working with RVSDGs (Regionalized Value State Dependency Graphs). RVSDGs are a type of Intermediary Representation (IR) suitable for regularizing Python bytecode within Numba.
The code in this repository is an implementation of the CFG restructuring algorithms in Bahmann 2015, specifically those from section 4.1 and 4.2: namely "loop restructuring" and "branch restructuring". These are interesting for Numba because they serve to clearly identify regions within the Python bytecode.
- Python 3.11
- graphviz
- pyyaml
You can create a conda env using the following:
conda env create -n numba-rvsdg python=3.11 python-graphviz
conda activate numba-rvsdg
pip install pyyaml
At the time of writing pyyaml
was not available for Python 3.11 via
defaults
so it had to be installed with pip
.
The following files are included in this repository:
numba_rvsdg
├── __init__.py
├── core
│ ├── datastructures
│ │ ├── basic_block.py # BasicBlock implementation
│ │ ├── scfg.py # SCFG implementation, maps names to blocks
│ │ ├── byte_flow.py # ByteFlow implementation, SCFG + bytecode
│ │ ├── flow_info.py # Converts program to ByteFlow
│ ├── transformations.py # Algorithms
│ └── utils.py # Miscellaneous utilities
├── networkx_vendored
│ └── scc.py # Strongly Connected Componets (loop detection)
├── rendering
│ └── rendering.py # Graphivz based rendering of SCFGs
├── tests
│ ├── simulator.py # Simulator utility for running SCFGs
│ ├── test_byteflow.py # Testung ByteFlow and others
│ ├── test_fig3.py # Testing fig. 3 from Bahman2015
│ ├── test_fig4.py # Testing fig. 4 from Bahman2015
│ ├── test_simulate.py # Simulator based testing
│ └── test_transforms.py # Testing graph transformations
└── utils
The following will process the given example function and display the four different stages. "initial" is the unprocessed bytecode as produced by cpython. "closed" is simply the closed variant of the initial CFG. "loop restructuring" is the loop-restructured version and "branch-restructured" is the final form which includes closing, loop-restructuring and branch-restructuring.
# Example: for loop with branch and early exit
from numba_rvsdg.rendering.rendering import render_func
def foo(n):
c = 0
for i in range(n):
c += 1
if i == 100:
break
return c
render_func(foo)
Reismann2020
-- https://arxiv.org/pdf/1912.05036.pdf -- Describes the concept of RVSDGsBahmann2015
-- https://dl.acm.org/doi/pdf/10.1145/2693261 -- Describes the transformation algorithms implemented
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