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Modern open source C++ FIX framework featuring complete schema customisation, high performance and fast development.
Pipeline training and inference Anomalib models UI in Anomaly Detection
The NAS Parallel Benchmarks for evaluating C++ parallel programming frameworks on shared-memory architectures
NAS Parallel Benchmark Kernels in C/C++. The parallel versions are in FastFlow, TBB, and OpenMP.
Framework for building parallel cellular automata in C++. In it you can also find a work-stealing threadpool and a reusable barrier that you can use in other projects.
Ant Colony Optimization for Traveling Salesman Problem written in plain C++, C++ with FastFlow and CUDA
Final project and assignments of Parallel and Distributed Systems: Paradigms and Models course
Homework of the Parallel and Distributed Systems: Paradigms and Models course of the Computer Science and Networking Master's Degree @ University of Pisa
(SPM) Distributed Systems: Paradigm and Models
Project for the course Parallel & Distributed Systems: Paradigms & Models @ Unipi
A C++ Poisson Equation solver performing Gauss-Seidel (vanilla) & Red-Black, Jacobi methods
Parallelization of a genetic algorithm to solve the Travelling Salesman Problem (TSP). A sequential version is developed, followed by an analysis to identify components suitable for parallelization. Two parallel implementations are created using standard threads and FastFlow.
A parallel Huffman encoding/decoding implementation in C++ providing a solution using fastflow and native threads
Final project for the Parallel and Distributed System course at UNIPI: Sequential and parallel implementations of the Odd-Even Sort using pthreads and FastFlow
Parallel implementation of the odd-even sort algorithm using pthreads and FastFlow
Parallel implementation of KNN algorithm using C++ and FastFlow library
Parallel implementation of KNN algorithm, using C++ standard library and FastFlow.
"Parallel and Distributed Systems" Course Material
Given a set of points in a 2D space, we require to compute in parallel for each one of the points in the set of points the set of k closest points. Point i is the point whose coordinates are listed in line i in the file. The input of the program is a set of floating-point coordinates (one per line, comma separated) and the output is a set of lines each hosting a point id and a list of point ids representing its KNN set ordered with respect to distance.
Parallel Huffman Coding (SPM Project 2022-2023)