59. Graph Library and Inbuilt Nodes

Graph architecture abstracts the data processing functions as a node and links them together to create a complex graph to enable reusable/modular data processing functions.

The graph library provides API to enable graph framework operations such as create, lookup, dump and destroy on graph and node operations such as clone, edge update, and edge shrink, etc. The API also allows to create the stats cluster to monitor per graph and per node stats.

59.1. Features

Features of the Graph library are:

• Nodes as plugins.

• Support for out of tree nodes.

• Inbuilt nodes for packet processing.

• Multi-process support.

• Low overhead graph walk and node enqueue.

• Low overhead statistics collection infrastructure.

• Support to export the graph as a Graphviz dot file. See rte_graph_export().

• Allow having another graph walk implementation in the future by segregating the fast path(rte_graph_worker.h) and slow path code.

59.2. Advantages of Graph architecture

• Memory latency is the enemy for high-speed packet processing, moving the similar packet processing code to a node will reduce the I cache and D caches misses.

• Exploits the probability that most packets will follow the same nodes in the graph.

• Allow SIMD instructions for packet processing of the node.-

• The modular scheme allows having reusable nodes for the consumers.

• The modular scheme allows us to abstract the vendor HW specific optimizations as a node.

59.3. Performance tuning parameters

• Test with various burst size values (256, 128, 64, 32) using RTE_GRAPH_BURST_SIZE config option. The testing shows, on x86 and arm64 servers, The sweet spot is 256 burst size. While on arm64 embedded SoCs, it is either 64 or 128.

• Disable node statistics (using RTE_LIBRTE_GRAPH_STATS config option) if not needed.

59.4. Programming model

59.4.1. Anatomy of Node:

Fig. 59.1 Anatomy of a node

The node is the basic building block of the graph framework.

A node consists of:

59.4.1.1. process():

The callback function will be invoked by worker thread using rte_graph_walk() function when there is data to be processed by the node. A graph node process the function using process() and enqueue to next downstream node using rte_node_enqueue*() function.

59.4.1.2. Context memory:

It is memory allocated by the library to store the node-specific context information. This memory will be used by process(), init(), fini() callbacks.

59.4.1.3. init():

The callback function will be invoked by rte_graph_create() on when a node gets attached to a graph.

59.4.1.4. fini():

The callback function will be invoked by rte_graph_destroy() on when a node gets detached to a graph.

59.4.1.5. Node name:

It is the name of the node. When a node registers to graph library, the library gives the ID as rte_node_t type. Both ID or Name shall be used lookup the node. rte_node_from_name(), rte_node_id_to_name() are the node lookup functions.

59.4.1.6. nb_edges:

The number of downstream nodes connected to this node. The next_nodes[] stores the downstream nodes objects. rte_node_edge_update() and rte_node_edge_shrink() functions shall be used to update the next_node[] objects. Consumers of the node APIs are free to update the next_node[] objects till rte_graph_create() invoked.

59.4.1.7. next_node[]:

The dynamic array to store the downstream nodes connected to this node. Downstream node should not be current node itself or a source node.

59.4.1.8. Source node:

Source nodes are static nodes created using RTE_NODE_REGISTER by passing flags as RTE_NODE_SOURCE_F. While performing the graph walk, the process() function of all the source nodes will be called first. So that these nodes can be used as input nodes for a graph.

59.4.2. Node creation and registration

• Node implementer creates the node by implementing ops and attributes of struct rte_node_register.

• The library registers the node by invoking RTE_NODE_REGISTER on library load using the constructor scheme. The constructor scheme used here to support multi-process.

59.4.3. Link the Nodes to create the graph topology

Fig. 59.2 Topology after linking the nodes

Once nodes are available to the program, Application or node public API functions can links them together to create a complex packet processing graph.

There are multiple different types of strategies to link the nodes.

59.4.3.1. Method (a):

Provide the next_nodes[] at the node registration time. See struct rte_node_register::nb_edges. This is a use case to address the static node scheme where one knows upfront the next_nodes[] of the node.

59.4.3.2. Method (b):

Use rte_node_edge_get(), rte_node_edge_update(), rte_node_edge_shrink() to update the next_nodes[] links for the node runtime but before graph create.

59.4.3.3. Method (c):

Use rte_node_clone() to clone a already existing node, created using RTE_NODE_REGISTER. When rte_node_clone() invoked, The library, would clone all the attributes of the node and creates a new one. The name for cloned node shall be "parent_node_name-user_provided_name".

This method enables the use case of Rx and Tx nodes where multiple of those nodes need to be cloned based on the number of CPU available in the system. The cloned nodes will be identical, except the "context memory". Context memory will have information of port, queue pair in case of Rx and Tx ethdev nodes.

59.4.4. Create the graph object

Now that the nodes are linked, Its time to create a graph by including the required nodes. The application can provide a set of node patterns to form a graph object. The fnmatch() API used underneath for the pattern matching to include the required nodes. After the graph create any changes to nodes or graph is not allowed.

The rte_graph_create() API shall be used to create the graph.

Example of a graph object creation:

{"ethdev_rx-0-0", ip4*, ethdev_tx-*"}

In the above example, A graph object will be created with ethdev Rx node of port 0 and queue 0, all ipv4* nodes in the system, and ethdev tx node of all ports.

59.4.5. Multicore graph processing

In the current graph library implementation, specifically, rte_graph_walk() and rte_node_enqueue* fast path API functions are designed to work on single-core to have better performance. The fast path API works on graph object, So the multi-core graph processing strategy would be to create graph object PER WORKER.

59.4.6. In fast path

Typical fast-path code looks like below, where the application gets the fast-path graph object using rte_graph_lookup() on the worker thread and run the rte_graph_walk() in a tight loop.

struct rte_graph *graph = rte_graph_lookup("worker0");

while (!done) {
    rte_graph_walk(graph);
}

59.4.7. Context update when graph walk in action

The fast-path object for the node is struct rte_node.

It may be possible that in slow-path or after the graph walk-in action, the user needs to update the context of the node hence access to struct rte_node * memory.

rte_graph_foreach_node(), rte_graph_node_get(), rte_graph_node_get_by_name() APIs can be used to get the struct rte_node*. rte_graph_foreach_node() iterator function works on struct rte_graph * fast-path graph object while others works on graph ID or name.

59.4.8. Get the node statistics using graph cluster

The user may need to know the aggregate stats of the node across multiple graph objects. Especially the situation where each graph object bound to a worker thread.

Introduced a graph cluster object for statistics. rte_graph_cluster_stats_create() API shall be used for creating a graph cluster with multiple graph objects and rte_graph_cluster_stats_get() to get the aggregate node statistics.

An example statistics output from rte_graph_cluster_stats_get()

+---------+-----------+-------------+---------------+-----------+---------------+-----------+
|Node     |calls      |objs         |realloc_count  |objs/call  |objs/sec(10E6) |cycles/call|
+---------------------+-------------+---------------+-----------+---------------+-----------+
|node0    |12977424   |3322220544   |5              |256.000    |3047.151872    |20.0000    |
|node1    |12977653   |3322279168   |0              |256.000    |3047.210496    |17.0000    |
|node2    |12977696   |3322290176   |0              |256.000    |3047.221504    |17.0000    |
|node3    |12977734   |3322299904   |0              |256.000    |3047.231232    |17.0000    |
|node4    |12977784   |3322312704   |1              |256.000    |3047.243776    |17.0000    |
|node5    |12977825   |3322323200   |0              |256.000    |3047.254528    |17.0000    |
+---------+-----------+-------------+---------------+-----------+---------------+-----------+

59.4.9. Node writing guidelines

The process() function of a node is the fast-path function and that needs to be written carefully to achieve max performance.

Broadly speaking, there are two different types of nodes.

59.4.10. Static nodes

The first kind of nodes are those that have a fixed next_nodes[] for the complete burst (like ethdev_rx, ethdev_tx) and it is simple to write. process() function can move the obj burst to the next node either using rte_node_next_stream_move() or using rte_node_next_stream_get() and rte_node_next_stream_put().

59.4.11. Intermediate nodes

The second kind of such node is intermediate nodes that decide what is the next_node[] to send to on a per-packet basis. In these nodes,

• Firstly, there has to be the best possible packet processing logic.

• Secondly, each packet needs to be queued to its next node.

This can be done using rte_node_enqueue_[x1|x2|x4]() APIs if they are to single next or rte_node_enqueue_next() that takes array of nexts.

In scenario where multiple intermediate nodes are present but most of the time each node using the same next node for all its packets, the cost of moving every pointer from current node’s stream to next node’s stream could be avoided. This is called home run and rte_node_next_stream_move() could be used to just move stream from the current node to the next node with least number of cycles. Since this can be avoided only in the case where all the packets are destined to the same next node, node implementation should be also having worst-case handling where every packet could be going to different next node.

59.4.11.1. Example of intermediate node implementation with home run:

1. Start with speculation that next_node = node->ctx. This could be the next_node application used in the previous function call of this node.

2. Get the next_node stream array with required space using rte_node_next_stream_get(next_node, space).

3. while n_left_from > 0 (i.e packets left to be sent) prefetch next pkt_set and process current pkt_set to find their next node

4. if all the next nodes of the current pkt_set match speculated next node, just count them as successfully speculated(last_spec) till now and continue the loop without actually moving them to the next node. else if there is a mismatch, copy all the pkt_set pointers that were last_spec and move the current pkt_set to their respective next’s nodes using rte_enqueue_next_x1(). Also, one of the next_node can be updated as speculated next_node if it is more probable. Finally, reset last_spec to zero.

5. if n_left_from != 0 then goto 3) to process remaining packets.

6. if last_spec == nb_objs, All the objects passed were successfully speculated to single next node. So, the current stream can be moved to next node using rte_node_next_stream_move(node, next_node). This is the home run where memcpy of buffer pointers to next node is avoided.

7. Update the node->ctx with more probable next node.

59.5. Graph object memory layout

Fig. 59.3 Memory layout

Understanding the memory layout helps to debug the graph library and improve the performance if needed.

Graph object consists of a header, circular buffer to store the pending stream when walking over the graph, and variable-length memory to store the rte_node objects.

The graph_nodes_mem_create() creates and populate this memory. The functions such as rte_graph_walk() and rte_node_enqueue_* use this memory to enable fastpath services.

59.6. Inbuilt Nodes

DPDK provides a set of nodes for data processing. The following section details the documentation for the same.

59.6.1. ethdev_rx

This node does rte_eth_rx_burst() into stream buffer passed to it (src node stream) and does rte_node_next_stream_move() only when there are packets received. Each rte_node works only on one Rx port and queue that it gets from node->ctx. For each (port X, rx_queue Y), a rte_node is cloned from ethdev_rx_base_node as ethdev_rx-X-Y in rte_node_eth_config() along with updating node->ctx. Each graph needs to be associated with a unique rte_node for a (port, rx_queue).

59.6.2. ethdev_tx

This node does rte_eth_tx_burst() for a burst of objs received by it. It sends the burst to a fixed Tx Port and Queue information from node->ctx. For each (port X), this rte_node is cloned from ethdev_tx_node_base as “ethdev_tx-X” in rte_node_eth_config() along with updating node->context.

Since each graph doesn’t need more than one Txq, per port, a Txq is assigned based on graph id to each rte_node instance. Each graph needs to be associated with a rte_node for each (port).

59.6.3. pkt_drop

This node frees all the objects passed to it considering them as rte_mbufs that need to be freed.

59.6.4. ip4_lookup

This node is an intermediate node that does LPM lookup for the received ipv4 packets and the result determines each packets next node.

On successful LPM lookup, the result contains the next_node id and next-hop id with which the packet needs to be further processed.

On LPM lookup failure, objects are redirected to pkt_drop node. rte_node_ip4_route_add() is control path API to add ipv4 routes. To achieve home run, node use rte_node_stream_move() as mentioned in above sections.

59.6.5. ip4_rewrite

This node gets packets from ip4_lookup node with next-hop id for each packet is embedded in node_mbuf_priv1(mbuf)->nh. This id is used to determine the L2 header to be written to the packet before sending the packet out to a particular ethdev_tx node. rte_node_ip4_rewrite_add() is control path API to add next-hop info.

59.6.6. null

This node ignores the set of objects passed to it and reports that all are processed.