Thomas Unterthiner

DeviceMemoryPool causes crash at shutdown

7

Consider the following piece of code: ``` import numpy as np import pycuda.autoinit import pycuda.gpuarray as gpu from pycuda.tools import DeviceMemoryPool cuda_memory_pool = DeviceMemoryPool() X = np.array([1, 2, 3.0]) X...

Division between int-gpuarray and int scalar does not work

1

Consider: ``` import pycuda.autoinit from pycuda import gpuarray x = gpuarray.to_gpu(np.arange(4)) x / 4 ``` This will give the following exception: ``` error Traceback (most recent call last) in ()...

`empty_like` ignores memory-order

1

Consider: ``` x = np.random.normal(size=(3, 5)).astype(np.float64, order="F") x_gpu = gpuarray.to_gpu(x) y_gpu = gpuarray.empty_like(x_gpu) x_gpu.flags.c_contiguous == y_gpu.flags.c_contiguous # gives "False" ``` I'm not very familiar with the `ArrayFlags` mechanism. It seems...

Monitors always write to stdout

16

Currently, all monitors write to stdout. If brainstorm is used from an IPython notebook, and some monitor as an `update` interval, this will inevitably lead to a completely frozen browser...

All buffers have to be of the same dtype

3

Currently, all buffers (parameters, internals, gradients, ...) are assumed to have the dtype (typically either float or double). This is a bit restrictive: For example, in a max-pooling operation, one...

Streams

14

Sooner or later, we should think about introducing CUDA streams for our GPU implementation. Side-Effect: Looking at the profiling outputs, across various example the most expensive call we make is...