Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality visualization of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems to bridge the gap between performance-oriented and quality-focused state-of-the-art solutions. To this end, we aim to exploit the flexibility and performance of cutting-edge GPU architecture features to formulate novel hybrid rendering approaches, taking advantage of both object and image order techniques. The envisioned solutions will be applicable to unstructured point clouds for instant visualization of billions of points, and leverage minimally-invasive compression, culling, and level-of-detail techniques to balance performance and quality on-demand. To ensure interactivity and veracity, we further tackle the GPU-accelerated editing of point clouds, as well as common point cloud display issues through corrective real-time methods. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its seminal goal is an efficient data knowledge transfer from sensor to user, with a wide range of ICT use cases to virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.