{'fraction_non_alphanumeric': 0.022857142857142857, 'fraction_numerical': 0.02, 'mean_word_length': 5.149122807017544, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Real-time Flow Computations using an Image Based Depth Sensor and GPU Acceleration

This work presents a recently developed computational fluid dynamics (CFD) solver based on the Lattice Boltzmann Method (LBM) that is algorithmically optimized for CUDA, allowing for real-time user interaction via stylus input, or a Microsoft Kinect sensor. The linear operations and the local nature of the Lattice Boltzmann equations are well suited to massively parallel architecture and thus ideal for Graphical Processing Units (GPUs). The 2D LBM solver is capable of speeds of up to 820 million lattice updates per second (MLUPS), the equivalent of 2600 time steps per second at a resolution of 640x480 points.