The Device abstract represents any hardware device with memory and compuation units. All Tensor operations are scheduled by the resident device for execution. Tensor memory is also managed by the device's memory manager. Therefore, optimization of memory and execution are implemented in the Device class.
Currently, SINGA has three Device implmentations,
The following code provides examples of creating devices:
from singa import device cuda = device.create_cuda_gpu_on(0) # use GPU card of ID 0 host = device.get_default_device() # get the default host device (a CppCPU) ary1 = device.create_cuda_gpus(2) # create 2 devices, starting from ID 0 ary2 = device.create_cuda_gpus([0,2]) # create 2 devices on ID 0 and 2
work in progress