Hi James, James Keaveney <james.keave...@durham.ac.uk> writes: > I'm having an issue with PyCUDA that at first glance seem like they > might be similar to those of Thomas Unterthiner (messages from Jun 20 > 2014, "Weird bug when slicing arrays on Kepler cards"). I'm also using a > Kepler card (GTX 670) and getting the same clean-up/dead context errors. > However, unlike Thomas, I'm not using cublas. The simplest example I can > show is below, which is a cuda kernel taken directly from here: > http://devblogs.nvidia.com/parallelforall/cuda-pro-tip-write-flexible-kernels-grid-stride-loops/ > > [snip] > pycuda._driver.LogicError: cuMemcpyDtoH failed: invalid/unknown error code > PyCUDA WARNING: a clean-up operation failed (dead context maybe?) > cuModuleUnload failed: invalid/unknown error code > PyCUDA WARNING: a clean-up operation failed (dead context maybe?) > cuMemFree failed: invalid/unknown error code > PyCUDA WARNING: a clean-up operation failed (dead context maybe?) > cuMemFree failed: invalid/unknown error code > PyCUDA WARNING: a clean-up operation failed (dead context maybe?) > cuMemFree failed: invalid/unknown error code > PyCUDA WARNING: a clean-up operation failed (dead context maybe?) > cuMemFree failed: invalid/unknown error code
This means your context went away while PyCUDA was still talking to it. This will happen most often if you perform some invalid operation (such as access out-of-bounds memory in a kernel). In this case, the cuMemcpyDtoH operation could be at fault. HTH, Andreas
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