APReF's implementation in Python 3
-
Updated
Jul 16, 2023 - Python
APReF's implementation in Python 3
Cetus Source to Source compiler improvements underway at University of Delaware
PARQ is an automatic parallelization engine based on Skolem Function Synthesis and Quantified Invariant Generation. It is aimed at parallelization of array modifying programs written as Constrained Horn Clause (CHC) formulas.
the base for a web-based parallel programming environment build over a microservice approach
APReF: An Automatic Parallelizer of Recursive Functions for Haskell
Benchmarks of loop fission algorithm.
Autonomously driving equation discovery, from the micro to the macro, from laptops to supercomputers.
Refactorings for optimizing Java 8 stream client code for greater parallelism and efficiency.
TC Optimizing Compiler
DiscoPoP - Discovery of Potential Parallelism
[IJCAI2023] An automated parallel training system that combines the advantages from both data and model parallelism. If you have any interests, please visit/star/fork https://github.com/Youhe-Jiang/OptimalShardedDataParallel
Par4All is an automatic parallelizing and optimizing compiler (workbench) for C and Fortran sequential programs
Automated Parallelization System and Infrastructure for Multiple Ecosystems
Pluto: An automatic polyhedral parallelizer and locality optimizer
Add a description, image, and links to the automatic-parallelization topic page so that developers can more easily learn about it.
To associate your repository with the automatic-parallelization topic, visit your repo's landing page and select "manage topics."