The command "meson build" causes a deprecation warning with meson 0.64.0.
WARNING: Running the setup command as `meson [options]` instead of
`meson setup [options]` is ambiguous and deprecated.
Therefore fix the examples in the documentation.
Cc: stable@dpdk.org
Signed-off-by: Stephen Hemminger <stephen@networkplumber.org>
Acked-by: Bruce Richardson <bruce.richardson@intel.com>
Acked-by: Zhangfei Gao <zhangfei.gao@linaro.org>
Signed-off-by: David Marchand <david.marchand@redhat.com>
Acked-by: Stanislaw Kardach <kda@semihalf.com>
NVIDIA acquired Mellanox Technologies in 2020.
The DPDK documentation and code might still include instances
of or references to Mellanox trademarks (like BlueField and ConnectX)
that are now NVIDIA trademarks.
The PCI IDs and copyrights are unchanged.
Signed-off-by: Thomas Monjalon <thomas@monjalon.net>
Acked-by: Gal Cohen <galco@nvidia.com>
To enable the gpudev rte_gpu_mem_cpu_map feature to expose
GPU memory to the CPU, the GPU CUDA driver library needs
the GDRCopy library and driver.
If DPDK is built without GDRCopy, the GPU CUDA driver returns
error if the is invoked rte_gpu_mem_cpu_map.
All the others GPU CUDA driver functionalities are not affected by
the absence of GDRCopy, thus this is an optional functionality
that can be enabled in the GPU CUDA driver.
CUDA driver documentation has been updated accordingly.
Signed-off-by: Elena Agostini <eagostini@nvidia.com>
The features list were missed when introducing the driver.
Fixes: 1306a73b19 ("gpu/cuda: introduce CUDA driver")
Cc: stable@dpdk.org
Signed-off-by: Elena Agostini <eagostini@nvidia.com>
This is the CUDA implementation of the gpudev library.
Functionalities implemented through CUDA Driver API are:
- Device probe and remove
- Manage device memory allocations
- Register/unregister external CPU memory in the device memory area
Signed-off-by: Elena Agostini <eagostini@nvidia.com>
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>
