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This lecture covers the importance of parallel computation in Computational Fluid Dynamics (CFD), focusing on distributing calculations among multiple processors to reduce computation time and increase memory availability. It explains the implementation of parallel computation in Fluent, emphasizing the need for transparent and portable code. The lecture also delves into mesh partitioning techniques, algorithms, and Fluent's capabilities in this regard. Additionally, it discusses parallel performance metrics like bandwidth and latency, highlighting their impact on scalability. Visualization techniques such as ray tracing, photorealism, and stereoscopy are explored, along with their applications in scientific data interpretation. The lecture concludes with a summary of the benefits of visualization in scientific research and communication.
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