Bhubaneswar, Odisha, India
Summary
Developed a flexible, high-performance Python module for SPH-smoothed visualizations from large-scale particle datasets, enhancing capabilities for 2D projections and 3D rotation animations in cosmological simulations.
Highlights
Engineered a robust Python module, SPHERE, for visualizing Smoothed Particle Hydrodynamics (SPH) data, significantly improving the analysis of large-scale cosmological simulations.
Implemented high-performance CPU rendering utilizing Numba parallelization, achieving efficient processing for complex datasets.
Integrated multiple SPH kernels (cubic spline, quintic, Wendland C4) and memory-efficient chunked processing to optimize performance and handle massive datasets effectively.
Automated movie generation capabilities, providing dynamic and insightful visualizations that contributed to clearer understanding of simulation outcomes.