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Accelerating Ansys Fluent: The Impact of GPU Solving on Simulation Preformance

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©2024 Rand Simulation 6 Study Results: Mixing Tank Model (~4 Million Elements) Continued... The first experiment compares segregated and coupled solving method performance on the Ansys mixing tank model, the smaller of the two benchmark simulations. In the previous charts, each GPU (y-axis) are grouped based on how many HPC packs are required for that configuration and lists its equivalent CPU cores (x-axis). At the end of each bar, the associated hardware costs are displayed. When using HPC Packs for Ansys Fluent Simulations, the benefit of using GPUs instead of CPUs for solving becomes readily apparent. For CPU cases, 2 HPC Packs allow parallel processing on 36 CPU cores, 3 HPC Packs allow 132 CPU cores, and 4 HPC Packs allow 516 cores. When utilizing GPUs, the equivalent number of HPC Packs allow vastly more computing power. For instance, 128 CPU cores (the baseline case) require 3 HPC Packs with an estimated hardware cost of $52,000. For approximately half the hardware cost and same number of HPC Packs, an NVIDIA RTX 6000 Ada Generation oers performance that is equivalent to approximately 250 to 350 CPU cores. When selecting to utilize segregated or coupled solving methods, the coupled solving method delivered higher performance in terms of equivalent CPU cores for the Mixing Tank Study. The question now becomes, how do GPUs perform simulating a model that is not only much larger but also more complex? The Impact of GPU Solving on Simulation Performance

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