PhotoScan makes heavy use of both the central processors (CPUs) in a computer and the video cards (GPUs) to run many of the calculations involved in turning still images into a 3D model or map. Intel’s new Xeon Scalable processors offer configurations with dozens of CPU cores, as well as the ability to support multiple GPUs – so let’s see how they perform in PhotoScan.
Want to see how your system stacks up to the latest hardware? Download our free, public Pix4D benchmark tool which will walk you through a couple of basic projects and display the calculation times. We’ve also included a video walkthrough, showing how to use this tool, and some comparison results from recent workstations built here at Puget Systems.
PhotoScan makes heavy use of the central processor (CPU) in a computer to run many of the calculations involved in turning still images into a 3D model or map. Different steps in that process utilize the CPU in various ways, though, so we are looking at how several Intel and AMD processors compare in this application.
PhotoScan makes use of both the CPU and GPUs (video cards) in a computer, during different steps of the photogrammetry workflow. One of the configuration options within this program also allows the CPU to be utilized during steps that are primarily performed on the GPU – and it is enabled by default. However, we have found in our testing that this option usually hampers performance more than it helps!
PhotoScan makes use of the video cards in a computer to assist with the computation of certain steps. As such, both the model of video card used and the number of GPUs present in a system can have an impact on the amount of time those steps take. In this article, we take a look at how multiple GeForce GTX 1080 Ti cards scale in performance across a few different CPU platforms.
PhotoScan makes use of the video cards in a computer to assist with the computation of certain steps. As such, the model of video card used can have an impact on the amount of time those steps take. In this article, we take a look at the GeForce 1000-series – based on NVIDIA’s Pascal GPU architecture – to see how they compare to each other.
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