ParTools allows the interactive analysis of a C program execution profile and data dependencies to facilitate the discovery and selection of suitable parallelization candidates in a manual parallelization process. The flow does not assume any specific parallelization technique, thus it can be broadly applied.
The original (serial) C source is automatically annotated to trace the execution profile and data dependencies at run-time. The annotated program is then executed using a significant (but small) data set selected by the developer. The data collected is cross-referenced with the original source and can be interactively analyzed graphically to determine the best parallelization candidates and techniques.
Features
- Automatic C source annotation for run-time tracing.
- Automatic run-time data collection.
- Interactive graphical analysis of execution profile and data dependencies.
- Cross-reference with the original C source.
- Can be used to support analysis for any parallelization technique.
Project Samples
Follow ParTools
You Might Also Like
Gen AI apps are built with MongoDB Atlas
MongoDB Atlas is the developer-friendly database used to build, scale, and run gen AI and LLM-powered apps—without needing a separate vector database. Atlas offers built-in vector search, global availability across 115+ regions, and flexible document modeling. Start building AI apps faster, all in one place.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of ParTools!