commit | 7cd35f5d688d9e3bddf66602655274dae944b086 | [log] [tgz] |
---|---|---|
author | Zachary Leaf <zachary.leaf@arm.com> | Fri Jun 25 08:11:15 2021 -0500 |
committer | Fan Zhang <roy.fan.zhang@intel.com> | Thu Apr 14 12:46:51 2022 +0000 |
tree | a379d214f3036cecf5d13fe94f65dd4ba85c73f5 | |
parent | e1fd3903efe38880a45687299a414b1516994955 [diff] |
ipsec: perf improvement of ipsec4_input_node using flow cache Adding flow cache support to improve inbound IPv4/IPSec Security Policy Database (SPD) lookup performance. By enabling the flow cache in startup conf, this replaces a linear O(N) SPD search, with an O(1) hash table search. This patch is the ipsec4_input_node counterpart to https://gerrit.fd.io/r/c/vpp/+/31694, and shares much of the same code, theory and mechanism of action. Details about the flow cache: Mechanism: 1. First packet of a flow will undergo linear search in SPD table. Once a policy match is found, a new entry will be added into the flow cache. From 2nd packet onwards, the policy lookup will happen in flow cache. 2. The flow cache is implemented using a hash table without collision handling. This will avoid the logic to age out or recycle the old flows in flow cache. Whenever a collision occurs, the old entry will be overwritten by the new entry. Worst case is when all the 256 packets in a batch result in collision, falling back to linear search. Average and best case will be O(1). 3. The size of flow cache is fixed and decided based on the number of flows to be supported. The default is set to 1 million flows, but is configurable by a startup.conf option. 4. Whenever a SPD rule is added/deleted by the control plane, all current flow cache entries will be invalidated. As the SPD API is not mp-safe, the data plane will wait for the control plane operation to complete. Cache invalidation is via an epoch counter that is incremented on policy add/del and stored with each entry in the flow cache. If the epoch counter in the flow cache does not match the current count, the entry is considered stale, and we fall back to linear search. The following configurable options are available through startup conf under the ipsec{} entry: 1. ipv4-inbound-spd-flow-cache on/off - enable SPD flow cache (default off) 2. ipv4-inbound-spd-hash-buckets %d - set number of hash buckets (default 4,194,304: ~1 million flows with 25% load factor) Performance with 1 core, 1 ESP Tunnel, null-decrypt then bypass, 94B (null encrypted packet) for different SPD policy matching indices: SPD Policy index : 2 10 100 1000 Throughput : Mbps/Mbps Mbps/Mbps Mbps/Mbps Mbps/Mbps (Baseline/Optimized) ARM TX2 : 300/290 230/290 70/290 8.5/290 Type: improvement Signed-off-by: Zachary Leaf <zachary.leaf@arm.com> Signed-off-by: mgovind <govindarajan.Mohandoss@arm.com> Tested-by: Jieqiang Wang <jieqiang.wang@arm.com> Change-Id: I8be2ad4715accbb335c38cd933904119db75827b
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.