OpenGL#
- pycuda.gl.make_context(dev, flags=0)#
Create and return a
pycuda.driver.Contextthat has GL interoperability enabled.Warning
This will fail with a rather unhelpful error message if you don’t already have a GL context created and active.
- class pycuda.gl.graphics_map_flags#
Usage of OpenGL object from CUDA.
- NONE#
Read and write access to mapped OpenGL object from CUDA code.
- READ_ONLY#
Read only access to mapped OpenGL object from CUDA code.
- WRITE_DISCARD#
Write only access to mapped OpenGL object from CUDA code. Reading is prohibited.
- class pycuda.gl.RegisteredBuffer(bufobj, flags=CU_GRAPHICS_MAP_RESOURCE_FLAGS_NONE)#
Object managing mapping of OpenGL buffers to CUDA. Cannot be used to map images.
- gl_handle()#
- unregister()#
- map(stream=None)#
Return a
RegisteredMapping.
- class pycuda.gl.RegisteredImage(bufobj, target, flags=CU_GRAPHICS_MAP_RESOURCE_FLAGS_NONE)#
Object managing mapping of OpenGL textures and render buffers to CUDA.
target must be be one of:
GL_TEXTURE_2D
GL_TEXTURE_RECTANGLE
GL_TEXTURE_CUBE_MAP
GL_TEXTURE_3D
GL_TEXTURE_2D_ARRAY
GL_RENDERBUFFER
(see PyOpenGL docs)
- gl_handle()#
- unregister()#
- map(stream=None)#
Return a
RegisteredMapping.
- class pycuda.gl.RegisteredMapping#
- unmap(stream=None)#
If no stream is specified, the unmap will use the same stream as the original mapping.
- device_ptr_and_size()#
Return a tuple (dev_pointer, size).
- array(index, level)#
Return an array for mapped image object for given array index and MIP level.
Automatic Initialization#
Warning
Importing pycuda.gl.autoinit will fail with a rather unhelpful error
message if you don’t already have a GL context created and active.
- pycuda.gl.autoinit.device#
- pycuda.gl.autoinit.context#
Old-style (pre-CUDA 3.0) API#
- pycuda.gl.autoinit.init()#
Enable GL interoperability for the already-created (so far non-GL) and currently active
pycuda.driver.Context.According to the forum post referenced in the note below, this will succeed on Windows XP and Linux, but it will not work on Windows Vista. There you have to create the GL-enabled context using
make_context().Warning
This function is deprecated since CUDA 3.0 and PyCUDA 2011.1.
Warning
This will fail with a rather unhelpful error message if you don’t already have a GL context created and active.
Note
See this post on the Nvidia forums for a discussion of problems and solutions with the GL interop interface.