4 रिपॉजिटरी
Utilities for printing and analyzing the state of code after specific optimization passes.
Distinct from Compiled Code Analysis: Specifically targets the inspection of code between compiler passes for debugging optimization bugs, not final binary auditing.
Explore 4 awesome GitHub repositories matching development tools & productivity · Intermediate Representation Inspection. Refine with filters or upvote what's useful.
This project is a JavaScript optimizer, minifier, module bundler, transpiler, and static analysis tool. It provides a compilation pipeline designed to shrink file sizes and improve runtime performance. The system utilizes a multi-pass compilation process to perform dead code elimination, global name mangling, and static type inference. It identifies unreachable functions and unused variables to reduce the final output size and detects potential runtime errors without executing the code. The tool manages assets through dependency resolution, code chunking, and bundle management. It ensures co
Provides the ability to print the state of the code after each optimization phase to identify bugs.
TileLang is a Python-embedded domain-specific language compiler that JIT-compiles and autotunes GPU kernels. It uses a tile-based DSL, automatic software pipelining, and parallel autotuning to generate optimized GPU kernels at runtime. It supports tensor core operations with Pythonic syntax, automatic memory management, and thread mapping. The compiler searches over tile sizes, thread counts, and scheduling policies, compiling and benchmarking candidates in parallel to find the fastest kernel. It also caches compiled binaries and tuning results to disk for reuse across sessions. TileLang inc
Extracts the intermediate representation of compiled GPU kernels for debugging and analysis.
IREE is an MLIR-based compiler toolchain and runtime designed to translate machine learning models from various frameworks into optimized binaries for execution across diverse hardware targets. It provides a unified pipeline to ingest models from PyTorch, TensorFlow, JAX, and ONNX, lowering them into a common intermediate representation for deployment on CPUs, GPUs, and bare-metal embedded systems. The project distinguishes itself through a bytecode virtual machine and a hardware abstraction layer that decouple high-level model logic from specific hardware instruction sets. It supports sophis
Snapshots and analyzes the intermediate representation between compiler passes to detect regressions.
Phasar is a static analysis framework designed for the inspection of software logic through the processing of compiler intermediate representations. It provides a modular pipeline for building program representations, including call graphs, control flow graphs, and type hierarchies, which serve as the foundation for deep structural analysis of software behavior. The framework specializes in interprocedural data flow analysis and pointer alias resolution, enabling the tracking of information movement across function boundaries and the identification of indirect memory access patterns. By lever
Processes compiler intermediate representations to perform deep structural inspection of software logic.