24. Packet Framework

24.4.3.1. Hash Table Overview

Hash tables are important because the key lookup operation is optimized for speed: instead of having to linearly search the lookup key through all the keys in the table, the search is limited to only the keys stored in a single table bucket.

Associative Arrays

An associative array is a function that can be specified as a set of (key, value) pairs, with each key from the possible set of input keys present at most once. For a given associative array, the possible operations are:

1. add (key, value): When no value is currently associated with key, then the (key, value ) association is created. When key is already associated value value0, then the association (key, value0) is removed and association (key, value) is created;
2. delete key: When no value is currently associated with key, this operation has no effect. When key is already associated value, then association (key, value) is removed;
3. lookup key: When no value is currently associated with key, then this operation returns void value (lookup miss). When key is associated with value, then this operation returns value. The (key, value) association is not changed.

The matching criterion used to compare the input key against the keys in the associative array is exact match, as the key size (number of bytes) and the key value (array of bytes) have to match exactly for the two keys under comparison.

Hash Function

A hash function deterministically maps data of variable length (key) to data of fixed size (hash value or key signature). Typically, the size of the key is bigger than the size of the key signature. The hash function basically compresses a long key into a short signature. Several keys can share the same signature (collisions).

High quality hash functions have uniform distribution. For large number of keys, when dividing the space of signature values into a fixed number of equal intervals (buckets), it is desirable to have the key signatures evenly distributed across these intervals (uniform distribution), as opposed to most of the signatures going into only a few of the intervals and the rest of the intervals being largely unused (non-uniform distribution).

Hash Table

A hash table is an associative array that uses a hash function for its operation. The reason for using a hash function is to optimize the performance of the lookup operation by minimizing the number of table keys that have to be compared against the input key.

Instead of storing the (key, value) pairs in a single list, the hash table maintains multiple lists (buckets). For any given key, there is a single bucket where that key might exist, and this bucket is uniquely identified based on the key signature. Once the key signature is computed and the hash table bucket identified, the key is either located in this bucket or it is not present in the hash table at all, so the key search can be narrowed down from the full set of keys currently in the table to just the set of keys currently in the identified table bucket.

The performance of the hash table lookup operation is greatly improved, provided that the table keys are evenly distributed among the hash table buckets, which can be achieved by using a hash function with uniform distribution. The rule to map a key to its bucket can simply be to use the key signature (modulo the number of table buckets) as the table bucket ID:

bucket_id = f_hash(key) % n_buckets;

By selecting the number of buckets to be a power of two, the modulo operator can be replaced by a bitwise AND logical operation:

bucket_id = f_hash(key) & (n_buckets - 1);

considering n_bits as the number of bits set in bucket_mask = n_buckets - 1, this means that all the keys that end up in the same hash table bucket have the lower n_bits of their signature identical. In order to reduce the number of keys in the same bucket (collisions), the number of hash table buckets needs to be increased.

In packet processing context, the sequence of operations involved in hash table operations is described in Fig. 24.2:

Fig. 24.2 Sequence of Steps for Hash Table Operations in a Packet Processing Context

24.4.3.2. Hash Table Use Cases

Flow Classification

Description: The flow classification is executed at least once for each input packet. This operation maps each incoming packet against one of the known traffic flows in the flow database that typically contains millions of flows.

Hash table name: Flow classification table

Number of keys: Millions

Key format: n-tuple of packet fields that uniquely identify a traffic flow/connection. Example: DiffServ 5-tuple of (Source IP address, Destination IP address, L4 protocol, L4 protocol source port, L4 protocol destination port). For IPv4 protocol and L4 protocols like TCP, UDP or SCTP, the size of the DiffServ 5-tuple is 13 bytes, while for IPv6 it is 37 bytes.

Key value (key data): actions and action meta-data describing what processing to be applied for the packets of the current flow. The size of the data associated with each traffic flow can vary from 8 bytes to kilobytes.

Address Resolution Protocol (ARP)

Description: Once a route has been identified for an IP packet (so the output interface and the IP address of the next hop station are known), the MAC address of the next hop station is needed in order to send this packet onto the next leg of the journey towards its destination (as identified by its destination IP address). The MAC address of the next hop station becomes the destination MAC address of the outgoing Ethernet frame.

Hash table name: ARP table

Number of keys: Thousands

Key format: The pair of (Output interface, Next Hop IP address), which is typically 5 bytes for IPv4 and 17 bytes for IPv6.

Key value (key data): MAC address of the next hop station (6 bytes).

24.4.3.3. Hash Table Types

Table 24.5 lists the hash table configuration parameters shared by all different hash table types.

24.4.3.4. Bucket Search Logic for Configurable Key Size Hash Tables

The performance of the bucket search logic is one of the main factors influencing the performance of the key lookup operation. The data structures and algorithm are designed to make the best use of Intel CPU architecture resources like: cache memory space, cache memory bandwidth, external memory bandwidth, multiple execution units working in parallel, out of order instruction execution, special CPU instructions, etc.

The bucket search logic handles multiple input packets in parallel. It is built as a pipeline of several stages (3 or 4), with each pipeline stage handling two different packets from the burst of input packets. On each pipeline iteration, the packets are pushed to the next pipeline stage: for the 4-stage pipeline, two packets (that just completed stage 3) exit the pipeline, two packets (that just completed stage 2) are now executing stage 3, two packets (that just completed stage 1) are now executing stage 2, two packets (that just completed stage 0) are now executing stage 1 and two packets (next two packets to read from the burst of input packets) are entering the pipeline to execute stage 0. The pipeline iterations continue until all packets from the burst of input packets execute the last stage of the pipeline.

The bucket search logic is broken into pipeline stages at the boundary of the next memory access. Each pipeline stage uses data structures that are stored (with high probability) into the L1 or L2 cache memory of the current CPU core and breaks just before the next memory access required by the algorithm. The current pipeline stage finalizes by prefetching the data structures required by the next pipeline stage, so given enough time for the prefetch to complete, when the next pipeline stage eventually gets executed for the same packets, it will read the data structures it needs from L1 or L2 cache memory and thus avoid the significant penalty incurred by L2 or L3 cache memory miss.

By prefetching the data structures required by the next pipeline stage in advance (before they are used) and switching to executing another pipeline stage for different packets, the number of L2 or L3 cache memory misses is greatly reduced, hence one of the main reasons for improved performance. This is because the cost of L2/L3 cache memory miss on memory read accesses is high, as usually due to data dependency between instructions, the CPU execution units have to stall until the read operation is completed from L3 cache memory or external DRAM memory. By using prefetch instructions, the latency of memory read accesses is hidden, provided that it is preformed early enough before the respective data structure is actually used.

By splitting the processing into several stages that are executed on different packets (the packets from the input burst are interlaced), enough work is created to allow the prefetch instructions to complete successfully (before the prefetched data structures are actually accessed) and also the data dependency between instructions is loosened. For example, for the 4-stage pipeline, stage 0 is executed on packets 0 and 1 and then, before same packets 0 and 1 are used (i.e. before stage 1 is executed on packets 0 and 1), different packets are used: packets 2 and 3 (executing stage 1), packets 4 and 5 (executing stage 2) and packets 6 and 7 (executing stage 3). By executing useful work while the data structures are brought into the L1 or L2 cache memory, the latency of the read memory accesses is hidden. By increasing the gap between two consecutive accesses to the same data structure, the data dependency between instructions is loosened; this allows making the best use of the super-scalar and out-of-order execution CPU architecture, as the number of CPU core execution units that are active (rather than idle or stalled due to data dependency constraints between instructions) is maximized.

The bucket search logic is also implemented without using any branch instructions. This avoids the important cost associated with flushing the CPU core execution pipeline on every instance of branch misprediction.

24.4.3.4.1. Configurable Key Size Hash Table

Fig. 24.3, Table 24.8 and Table 24.9 detail the main data structures used to implement configurable key size hash tables (either LRU or extendable bucket, either with pre-computed signature or “do-sig”).

Fig. 24.3 Data Structures for Configurable Key Size Hash Tables

Table 24.8 Main Large Data Structures (Arrays) used for Configurable Key Size Hash Tables

#	Array name	Number of entries	Entry size (bytes)	Description
1	Bucket array	n_buckets (configurable)	32	Buckets of the hash table.
2	Bucket extensions array	n_buckets_ext (configurable)	32	This array is only created for extendable bucket tables.
3	Key array	n_keys	key_size (configurable)	Keys added to the hash table.
4	Data array	n_keys	entry_size (configurable)	Key values (key data) associated with the hash table keys.

Table 24.9 Field Description for Bucket Array Entry (Configurable Key Size Hash Tables)

#	Field name	Field size (bytes)	Description
1	Next Ptr/LRU	8	For LRU tables, this fields represents the LRU list for the current bucket stored as array of 4 entries of 2 bytes each. Entry 0 stores the index (0 .. 3) of the MRU key, while entry 3 stores the index of the LRU key. For extendable bucket tables, this field represents the next pointer (i.e. the pointer to the next group of 4 keys linked to the current bucket). The next pointer is not NULL if the bucket is currently extended or NULL otherwise. To help the branchless implementation, bit 0 (least significant bit) of this field is set to 1 if the next pointer is not NULL and to 0 otherwise.
2	Sig[0 .. 3]	4 x 2	If key X (X = 0 .. 3) is valid, then sig X bits 15 .. 1 store the most significant 15 bits of key X signature and sig X bit 0 is set to 1. If key X is not valid, then sig X is set to zero.
3	Key Pos [0 .. 3]	4 x 4	If key X is valid (X = 0 .. 3), then Key Pos X represents the index into the key array where key X is stored, as well as the index into the data array where the value associated with key X is stored. If key X is not valid, then the value of Key Pos X is undefined.

Fig. 24.4 and Table 24.10 detail the bucket search pipeline stages (either LRU or extendable bucket, either with pre-computed signature or “do-sig”). For each pipeline stage, the described operations are applied to each of the two packets handled by that stage.

Fig. 24.4 Bucket Search Pipeline for Key Lookup Operation (Configurable Key Size Hash Tables)

Table 24.10 Description of the Bucket Search Pipeline Stages (Configurable Key Size Hash Tables)

#	Stage name	Description
0	Prefetch packet meta-data	Select next two packets from the burst of input packets. Prefetch packet meta-data containing the key and key signature.
1	Prefetch table bucket	Read the key signature from the packet meta-data (for extendable bucket hash tables) or read the key from the packet meta-data and compute key signature (for LRU tables). Identify the bucket ID using the key signature. Set bit 0 of the signature to 1 (to match only signatures of valid keys from the table). Prefetch the bucket.
2	Prefetch table key	Read the key signatures from the bucket. Compare the signature of the input key against the 4 key signatures from the packet. As result, the following is obtained: match = equal to TRUE if there was at least one signature match and to FALSE in the case of no signature match; match_many = equal to TRUE is there were more than one signature matches (can be up to 4 signature matches in the worst case scenario) and to FALSE otherwise; match_pos = the index of the first key that produced signature match (only valid if match is true). For extendable bucket hash tables only, set match_many to TRUE if next pointer is valid. Prefetch the bucket key indicated by match_pos (even if match_pos does not point to valid key valid).
3	Prefetch table data	Read the bucket key indicated by match_pos. Compare the bucket key against the input key. As result, the following is obtained: match_key = equal to TRUE if the two keys match and to FALSE otherwise. Report input key as lookup hit only when both match and match_key are equal to TRUE and as lookup miss otherwise. For LRU tables only, use branchless logic to update the bucket LRU list (the current key becomes the new MRU) only on lookup hit. Prefetch the key value (key data) associated with the current key (to avoid branches, this is done on both lookup hit and miss).

Additional notes:

1. The pipelined version of the bucket search algorithm is executed only if there are at least 7 packets in the burst of input packets. If there are less than 7 packets in the burst of input packets, a non-optimized implementation of the bucket search algorithm is executed.
2. Once the pipelined version of the bucket search algorithm has been executed for all the packets in the burst of input packets, the non-optimized implementation of the bucket search algorithm is also executed for any packets that did not produce a lookup hit, but have the match_many flag set. As result of executing the non-optimized version, some of these packets may produce a lookup hit or lookup miss. This does not impact the performance of the key lookup operation, as the probability of matching more than one signature in the same group of 4 keys or of having the bucket in extended state (for extendable bucket hash tables only) is relatively small.

Key Signature Comparison Logic

The key signature comparison logic is described in Table 24.11.

Table 24.11 Lookup Tables for Match, Match_Many and Match_Pos

#	mask	match (1 bit)	match_many (1 bit)	match_pos (2 bits)
0	0000	0	0	00
1	0001	1	0	00
2	0010	1	0	01
3	0011	1	1	00
4	0100	1	0	10
5	0101	1	1	00
6	0110	1	1	01
7	0111	1	1	00
8	1000	1	0	11
9	1001	1	1	00
10	1010	1	1	01
11	1011	1	1	00
12	1100	1	1	10
13	1101	1	1	00
14	1110	1	1	01
15	1111	1	1	00

The input mask hash bit X (X = 0 .. 3) set to 1 if input signature is equal to bucket signature X and set to 0 otherwise. The outputs match, match_many and match_pos are 1 bit, 1 bit and 2 bits in size respectively and their meaning has been explained above.

As displayed in Table 24.12, the lookup tables for match and match_many can be collapsed into a single 32-bit value and the lookup table for match_pos can be collapsed into a 64-bit value. Given the input mask, the values for match, match_many and match_pos can be obtained by indexing their respective bit array to extract 1 bit, 1 bit and 2 bits respectively with branchless logic.

Table 24.12 Collapsed Lookup Tables for Match, Match_Many and Match_Pos

	Bit array	Hexadecimal value
match	1111_1111_1111_1110	0xFFFELLU
match_many	1111_1110_1110_1000	0xFEE8LLU
match_pos	0001_0010_0001_0011__0001_0010_0001_0000	0x12131210LLU

The pseudo-code for match, match_many and match_pos is:

match = (0xFFFELLU >> mask) & 1;

match_many = (0xFEE8LLU >> mask) & 1;

match_pos = (0x12131210LLU >> (mask << 1)) & 3;

24.4.3.4.2. Single Key Size Hash Tables

Fig. 24.5, Fig. 24.6, Table 24.13 and Table 24.14 detail the main data structures used to implement 8-byte and 16-byte key hash tables (either LRU or extendable bucket, either with pre-computed signature or “do-sig”).

Fig. 24.5 Data Structures for 8-byte Key Hash Tables

Fig. 24.6 Data Structures for 16-byte Key Hash Tables

Table 24.13 Main Large Data Structures (Arrays) used for 8-byte and 16-byte Key Size Hash Tables

#	Array name	Number of entries	Entry size (bytes)	Description
1	Bucket array	n_buckets (configurable)	8-byte key size: 64 + 4 x entry_size 16-byte key size: 128 + 4 x entry_size	Buckets of the hash table.
2	Bucket extensions array	n_buckets_ext (configurable)	8-byte key size: 64 + 4 x entry_size 16-byte key size: 128 + 4 x entry_size	This array is only created for extendable bucket tables.

Table 24.14 Field Description for Bucket Array Entry (8-byte and 16-byte Key Hash Tables)

#	Field name	Field size (bytes)	Description
1	Valid	8	Bit X (X = 0 .. 3) is set to 1 if key X is valid or to 0 otherwise. Bit 4 is only used for extendable bucket tables to help with the implementation of the branchless logic. In this case, bit 4 is set to 1 if next pointer is valid (not NULL) or to 0 otherwise.
2	Next Ptr/LRU	8	For LRU tables, this fields represents the LRU list for the current bucket stored as array of 4 entries of 2 bytes each. Entry 0 stores the index (0 .. 3) of the MRU key, while entry 3 stores the index of the LRU key. For extendable bucket tables, this field represents the next pointer (i.e. the pointer to the next group of 4 keys linked to the current bucket). The next pointer is not NULL if the bucket is currently extended or NULL otherwise.
3	Key [0 .. 3]	4 x key_size	Full keys.
4	Data [0 .. 3]	4 x entry_size	Full key values (key data) associated with keys 0 .. 3.

and detail the bucket search pipeline used to implement 8-byte and 16-byte key hash tables (either LRU or extendable bucket, either with pre-computed signature or “do-sig”). For each pipeline stage, the described operations are applied to each of the two packets handled by that stage.

Fig. 24.7 Bucket Search Pipeline for Key Lookup Operation (Single Key Size Hash Tables)

Table 24.15 Description of the Bucket Search Pipeline Stages (8-byte and 16-byte Key Hash Tables)

#	Stage name	Description
0	Prefetch packet meta-data	Select next two packets from the burst of input packets. Prefetch packet meta-data containing the key and key signature.
1	Prefetch table bucket	Read the key signature from the packet meta-data (for extendable bucket hash tables) or read the key from the packet meta-data and compute key signature (for LRU tables). Identify the bucket ID using the key signature. Prefetch the bucket.
2	Prefetch table data	Read the bucket. Compare all 4 bucket keys against the input key. Report input key as lookup hit only when a match is identified (more than one key match is not possible) For LRU tables only, use branchless logic to update the bucket LRU list (the current key becomes the new MRU) only on lookup hit. Prefetch the key value (key data) associated with the matched key (to avoid branches, this is done on both lookup hit and miss).

Additional notes:

1. The pipelined version of the bucket search algorithm is executed only if there are at least 5 packets in the burst of input packets. If there are less than 5 packets in the burst of input packets, a non-optimized implementation of the bucket search algorithm is executed.
2. For extendable bucket hash tables only, once the pipelined version of the bucket search algorithm has been executed for all the packets in the burst of input packets, the non-optimized implementation of the bucket search algorithm is also executed for any packets that did not produce a lookup hit, but have the bucket in extended state. As result of executing the non-optimized version, some of these packets may produce a lookup hit or lookup miss. This does not impact the performance of the key lookup operation, as the probability of having the bucket in extended state is relatively small.

24.5.2.1. Port Action Handler

An action handler can be assigned to each input/output port to define actions to be executed on each input packet that is received by the port. Defining the action handler for a specific input/output port is optional (i.e. the action handler can be disabled).

For input ports, the action handler is executed after RX function. For output ports, the action handler is executed before the TX function.

The action handler can decide to drop packets.

24.5.3.1. Table Action Handler

An action handler to be executed on each input packet can be assigned to each table. Defining the action handler for a specific table is optional (i.e. the action handler can be disabled).

The action handler is executed after the table lookup operation is performed and the table entry associated with each input packet is identified. The action handler can only handle the user-defined actions, while the reserved actions (e.g. the next hop actions) are handled by the Packet Framework. The action handler can decide to drop the input packet.

24.5.3.2. Reserved Actions

The reserved actions are handled directly by the Packet Framework without the user being able to change their meaning through the table action handler configuration. A special category of the reserved actions is represented by the next hop actions, which regulate the packet flow between input ports, tables and output ports through the pipeline. Table 24.16 lists the next hop actions.

24.5.3.3. User Actions

For each table, the meaning of user actions is defined through the configuration of the table action handler. Different tables can be configured with different action handlers, therefore the meaning of the user actions and their associated meta-data is private to each table. Within the same table, all the table entries (including the table default entry) share the same definition for the user actions and their associated meta-data, with each table entry having its own set of enabled user actions and its own copy of the action meta-data. Table 24.17 contains a non-exhaustive list of user action examples.