Complete HPC Parallel Sorting Benchmarks

This release contains the complete and stable version of the HPC Parallel Sorting
project, implementing and benchmarking multiple parallel programming paradigms
on a real high-performance computing system.

Included Implementations

• MPI (C) – distributed-memory parallel sorting
• OpenMP (C) – shared-memory parallel sorting
• POSIX Threads (C) – low-level thread-based parallelism
• mpi4py (Python) – distributed parallel sorting with Python bindings

Execution Environment

• Executed and benchmarked on the SPbPU Tornado supercomputer
• Real executions using interactive and multi-node Slurm sessions
• Benchmarks include varying thread counts and MPI ranks (up to 224 processes)

Key Features

• Comparison of shared-memory vs distributed-memory models
• Performance evaluation based on execution time, speedup, and scalability
• Reproducible experiments with provided input data
• Visual performance analysis (plots and execution screenshots)
• Detailed technical report included (Report.pdf)

Notes

This release represents a complete and reproducible academic HPC benchmark suite
and can be used for educational purposes, performance analysis, and portfolio review.