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Faster maximum clique
Mentored by: Next Silicon
Optimized algorithms for maximum clique detection in large graphs
C++
Graph Algorithms
Combinatorial Optimization
Parallel Computing
Data Structures
Description
High-performance algorithms for finding maximum cliques in graph structures. Implements advanced pruning techniques, branch-and-bound optimization, and parallel processing to handle large-scale graphs efficiently. Includes both exact and approximation algorithms with performance comparisons and scalability analysis.
Team Members
Cohort: Embedded Systems Bootcamp 2025 (Embedded)
Responsibilities:
Implemented the LazyMC algorithm within a modular C++17 codebase, including performance-driven data-structure optimizations.
based on the academic paper "Less Is More" (https://pureadmin.qub.ac.uk/ws/portalfiles/portal/630842925/paper.pdf?&~nfopt(fileDistorted=9431535770239338&uploadEmbeddedImages=1))
Built a comprehensive testing suite using GoogleTest and benchmarking workflows using Google Benchmark.
Optimized runtime via Intel VTune profiling (CPU hotspots, memory behavior) and multithreading with OpenMP.
Integrated CI pipelines using GitHub Actions for automated builds, tests, and benchmark runs.
...and more contributions not listed here
R
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Responsibilities:
Implemented the LazyMC algorithm for maximum-clique detection in a modular C++ system with performance optimizations
based on the academic paper "Less Is More" https://pureadmin.qub.ac.uk/ws/portalfiles/portal/630842925/paper.pdf?&~nfopt(fileDistorted=9431535770239338&uploadEmbeddedImages=1)
Experience working with CMake.
Developed GoogleTest suite and Google Benchmark performance framework.
Optimized with Intel VTune and multithreading via OpenMP.
...and more contributions not listed here