| commit | f9a17487982ebc231ad0f32f15f261453aef8a88 | [log] [tgz] |
|---|---|---|
| author | Yulong Pei <yulong.pei@intel.com> | Thu Jan 05 02:26:32 2023 +0000 |
| committer | Beno�t Ganne <bganne@cisco.com> | Fri Jan 13 09:57:00 2023 +0000 |
| tree | edbfdc326ad1b0fc25f2efa083e94010c025c2a8 | |
| parent | 809eb669c7a353cd06da58ccdf8578053b1233ca [diff] |
af_xdp: update af_xdp driver plugin to depend on libxdp AF_XDP support is deprecated in libbpf since v0.7.0 [1], the libxdp library now provides the functionality which once was in libbpf, this commit updates af_xdp plugin to depend on libxdp, libbpf still remains a dependency even if libxdp is present, as it need use libbpf APIs for program loading. libxdp is distributed within xdp-tool [2], xdp-tools package also include libbpf in it as dependency, so here installed libxdp v1.2.9 and libbpf v0.8.0, both from xdp-tool-1.2.9 package. More information about libxdp compatibility can be found in the libxdp README [3]. In libbpf v0.8.0, The bpf_prog_load function was deprecated and changed to bpf_object__open_file and bpf_object__next_program and bpf_object__load, The bpf_get_link_xdp_id and bpf_set_link_xdp_fd functions were deprecated and changed to bpf_xdp_attach and bpf_xdp_detach, The bpf_object__unload function was deprecated and changed to bpf_object__close. [1] https://github.com/libbpf/libbpf/commit/277846bc6c15 [2] https://github.com/xdp-project/xdp-tools/releases/tag/v1.2.9 [3] https://github.com/xdp-project/xdp-tools/blob/master/lib/libxdp/README.org Type: improvement Change-Id: Ifbf6e3aa38bc6e0b77561f26311fd11c15ddb47e Signed-off-by: Yulong Pei <yulong.pei@intel.com>
The VPP platform is an extensible framework that provides out-of-the-box production quality switch/router functionality. It is the open source version of Cisco's Vector Packet Processing (VPP) technology: a high performance, packet-processing stack that can run on commodity CPUs.
The benefits of this implementation of VPP are its high performance, proven technology, its modularity and flexibility, and rich feature set.
For more information on VPP and its features please visit the FD.io website and What is VPP? pages.
Details of the changes leading up to this version of VPP can be found under doc/releasenotes.
| Directory name | Description |
|---|---|
| build-data | Build metadata |
| build-root | Build output directory |
| docs | Sphinx Documentation |
| dpdk | DPDK patches and build infrastructure |
| extras/libmemif | Client library for memif |
| src/examples | VPP example code |
| src/plugins | VPP bundled plugins directory |
| src/svm | Shared virtual memory allocation library |
| src/tests | Standalone tests (not part of test harness) |
| src/vat | VPP API test program |
| src/vlib | VPP application library |
| src/vlibapi | VPP API library |
| src/vlibmemory | VPP Memory management |
| src/vnet | VPP networking |
| src/vpp | VPP application |
| src/vpp-api | VPP application API bindings |
| src/vppinfra | VPP core library |
| src/vpp/api | Not-yet-relocated API bindings |
| test | Unit tests and Python test harness |
In general anyone interested in building, developing or running VPP should consult the VPP wiki for more complete documentation.
In particular, readers are recommended to take a look at [Pulling, Building, Running, Hacking, Pushing](https://wiki.fd.io/view/VPP/Pulling,_Building,_Run ning,_Hacking_and_Pushing_VPP_Code) which provides extensive step-by-step coverage of the topic.
For the impatient, some salient information is distilled below.
To install system dependencies, build VPP and then install it, simply run the build script. This should be performed a non-privileged user with sudo access from the project base directory:
./extras/vagrant/build.sh
If you want a more fine-grained approach because you intend to do some development work, the Makefile in the root directory of the source tree provides several convenience shortcuts as make targets that may be of interest. To see the available targets run:
make
The directory extras/vagrant contains a VagrantFile and supporting scripts to bootstrap a working VPP inside a Vagrant-managed Virtual Machine. This VM can then be used to test concepts with VPP or as a development platform to extend VPP. Some obvious caveats apply when using a VM for VPP since its performance will never match that of bare metal; if your work is timing or performance sensitive, consider using bare metal in addition or instead of the VM.
For this to work you will need a working installation of Vagrant. Instructions for this can be found [on the Setting up Vagrant wiki page] (https://wiki.fd.io/view/DEV/Setting_Up_Vagrant).
Several modules provide documentation, see @subpage user_doc for more end-user-oriented information. Also see @subpage dev_doc for developer notes.
Visit the VPP wiki for details on more advanced building strategies and other development notes.