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GPU Info

FAQ

  1. Do I need a GPU?

Technically no, you can perform limited software rendering on linux using lavapipe (see drivers link below). However fastplotlib is intentionally built for realtime rendering using the latest GPU technologies, so we strongly recommend that you use a GPU.

  1. My kernel keeps crashing when I create visualizations.

This can happen under the following circumstances:

  • You have ran out of GPU VRAM.
  • Driver issues (see next section).

If you aren't able to solve it please post an issue on GitHub. :)

Drivers

See the README: https://github.com/fastplotlib/fastplotlib?tab=readme-ov-file#graphics-drivers

If you notice weird graphic artifacts, things not rendering, or other glitches try updating to the latest stable drivers.

View available GPU

You can view all GPUs that are available to WGPU like this:

from wgpu.backends.wgpu_native import enumerate_adapters
from pprint import pprint

for adapter in enumerate_adapters():
    pprint(adapter.request_adapter_info())

For example, on a Thinkpad AMD laptop with a dedicated nvidia GPU this returns:

{'adapter_type': 'IntegratedGPU',
 'architecture': '',
 'backend_type': 'Vulkan',
 'description': 'Mesa 22.3.6',
 'device': 'AMD Radeon Graphics (RADV REMBRANDT)',
 'vendor': 'radv'}
{'adapter_type': 'DiscreteGPU',
 'architecture': '',
 'backend_type': 'Vulkan',
 'description': '535.129.03',
 'device': 'NVIDIA T1200 Laptop GPU',
 'vendor': 'NVIDIA'}
{'adapter_type': 'CPU',
 'architecture': '',
 'backend_type': 'Vulkan',
 'description': 'Mesa 22.3.6 (LLVM 15.0.6)',
 'device': 'llvmpipe (LLVM 15.0.6, 256 bits)',
 'vendor': 'llvmpipe'}
{'adapter_type': 'Unknown',
 'architecture': '',
 'backend_type': 'OpenGL',
 'description': '',
 'device': 'AMD Radeon Graphics (rembrandt, LLVM 15.0.6, DRM 3.52, '
           '6.4.0-0.deb12.2-amd64)',
 'vendor': ''}

GPU currently in use

If you want to know the GPU that a current plot is using you can check the adapter that the renderer is using:

# for example if we make a plot
plot = fpl.Plot()
plot.add_image(np.random.rand(100, 100))
plot.show()

# GPU that is currently in use by the renderer
plot.renderer.device.adapter.request_adapter_info()