This is usually where we can gain most because many scenes are overwhelmingly unoptimized. In many cases, we start in the second category. We can free up more memory and we can reduce the amount of memory used by Blender during rendering. However, we are still limited by the total amount of available memory and so Blender may still crash, so what can we do? What can we do when Blender run out of memory during rendering?įrom a birds-eye view there are two things we can do. So, deciding between CPU and GPU based on the available VRAM and the size of a scene has become less of an issue. These days, if we use a GPU to render, Blender can use both the GPUs VRAM and the system RAM when the VRAM becomes full. Related content: Common render problems in Blender If this is the case for you, you can read my article on common render problems to get some guidance on what driver to use for your graphics card. There are other reasons why Blender may crash during rendering, such as a bug in Blender or a graphics driver that isn't co-operating. No matter what compute device we choose to use, we still need to fit the data needed for rendering in the available RAM. Either with Cuda or Optix if we have an Nvidia card, or with OpenCL with AMD cards. In most cases, if we have a dedicated graphics card, we can use it to render our scenes in Blender. This can be system RAM, or it can be your VRAM that is handled by your graphics card (GPU). The most common cause for Blender to not be able to complete a render is that it runs out of available RAM. So, what does this have to do with rendering in Blender? Why does Blender crash during rendering? Instead, it is a dedicated part of the hard drive called a swap partition. On Windows this space on the hard drive is called the swap file while on MacOS and Linux, this isn't a file. Related content: Will Blender run on a 32-bit computer? At some point the operating system can even start to move data from RAM to the hard drive for later if applications are open for longer periods in the background but isn't vital enough to store in the faster RAM. In the meantime, other applications that are minimized or has not been active for a long time gets less and less priority. Both in the foreground and in the background.įor instance, the operating system knows what application is currently being used actively and so it prioritizes memory for it along with other resources such as CPU and disk access depending on what it needs. It allocates memory for applications upon request and free memory when it is no longer needed based on what the user is currently doing and what different processes are running. In a computer, the operating system is responsible for managing memory.
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