In heterogeneous computing system, processing is not only in the CPU.
Some tasks can be delegated to devices working in parallel.
Such workload distribution can be achieved by sharing some memory.
As a first step, the features are focused on memory management.
A function allows to allocate memory inside the device,
or in the main (CPU) memory while making it visible for the device.
This memory may be used to save packets or for synchronization data.
The next step should focus on GPU processing task control.
Signed-off-by: Elena Agostini <eagostini@nvidia.com>
Signed-off-by: Thomas Monjalon <thomas@monjalon.net>
In heterogeneous computing system, processing is not only in the CPU.
Some tasks can be delegated to devices working in parallel.
The new library gpudev is for dealing with GPGPU computing devices
from a DPDK application running on the CPU.
The infrastructure is prepared to welcome drivers in drivers/gpu/.
Signed-off-by: Elena Agostini <eagostini@nvidia.com>
Signed-off-by: Thomas Monjalon <thomas@monjalon.net>
