Benchmarking GPUs on SVBRDF Extractor Model

• URL: http://arxiv.org/abs/2310.19816v1
• Date: Thu, 19 Oct 2023 17:09:06 GMT
• Title: Benchmarking GPUs on SVBRDF Extractor Model
• Authors: Narayan Kandel, Melanie Lambert
• Abstract summary: In this work, we try to differentiate the performance of different GPUs on neural network models that operate on bigger input images (256x256) In this work, we tried to differentiate the performance of different GPUs on neural network models that operate on bigger input images (256x256)
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: With the maturity of deep learning, its use is emerging in every field. Also, as different types of GPUs are becoming more available in the markets, it creates a difficult decision for users. How can users select GPUs to achieve optimal performance for a specific task? Analysis of GPU architecture is well studied, but existing works that benchmark GPUs do not study tasks for networks with significantly larger input. In this work, we tried to differentiate the performance of different GPUs on neural network models that operate on bigger input images (256x256).

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