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Algorithms for Advanced Packet Classification with TCAMs

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  1. Algorithms for Advanced Packet Classification with TCAMs Karthik Lakshminarayanan UC Berkeley Joint work with Anand Rangarajan and Srinivasan Venkatachary (Cypress Semiconductors Inc.)

  2. Packet Processing Environment Rule: acl-id src-addr src-port dst-addr dst-port proto (e.g. acl1231128.32.0.0/80-102332.12.1.1/161024tcp) Rule Action Hdr Payload permit/deny, update counter … … Search Key ACL Database • Packet matches a set of rules based on the header • Examples: routers, intrusion detection systems

  3. Ternary Content Addressable Memory 00100x1x001110x0x Search key 01110xxx001100xxx 011101xx001100x10 width = W bits 1111101x1101000xx width = W bits • Memory device with fixed width arrays • Each bit is 0, 1 or x (don’t care) • Search is performed against all entries in parallel and the first result is returned TCAM row1 row2 Output is row2 … rown

  4. TCAM: Benefits and Disadvantages • Benefits: • Deterministic Search Throughput—O(1) search • Disadvantages: • Cost • Power consumption • Current TCAM usage: • 6 million TCAM devices deployed • Used in multi-gigabit systems that have O(10,000) rules • TCAMs can support a table of size 128K ternary entries and 133 million searches per second for 144-bit keys

  5. Problems • Range Representation Problem • Multimatch Classification Problem Algorithms in software easier to implement

  6. Problems • Range Representation Problem • Multimatch Classification Problem

  7. Range Representation Problem • Representing prefixes in ternary is trivial • IP address prefixes present in rules • Representing arbitrary ranges is not easy though • port fields might contain ranges • e.g. some security applications may allow ports 1024-65535 only

  8. Earlier Approaches – I Prefix expansion of ranges: • express ranges as a union of prefixes • have a separate TCAM entry for each prefix • expansion: the number of entries a rules expands to • Example: the range [3,12] over a 4-bit field would expand to: • 0011 (3), 01xx (4-7), 10xx (8-11) and 1100 (12) • Worst-case expansion for a W-bit field is 2W-2 • example: [1,14] would expand to 0001, 001x, 01xx, 10xx, 110x, 1110 • 16-bit port field expands to 30 entries

  9. Earlier Approaches – II Database-dependent encoding: • observation: TCAM array has some unused bits • use these additional bits to encode commonly occurring ranges in the database • TCAMs with IP ACLs have ~ 36 extra bits • 144-bit wide TCAMs • 104-bits + 4-bits for IP ACL rules

  10. Earlier Approaches – II Database-dependent encoding: • observation: TCAM array has some unused bits • use these additional bits to encode commonly occurring ranges in the database • Example: Address Port … 12.123.0.0/16 20-24 … 32.12.13.0/24 1024- … 128.0.0.0/8 20-24 … Set extra bit to 1 Set extra bit to x Set extra bit to 1 If search key falls in 20-24, set extra bit to 1, else set it to 0

  11. Earlier Approaches – II Database-dependent encoding: • observation: TCAM array has some unused bits • use these additional bits to encode commonly occurring ranges in the database • Improved version:Region-based Range Encoding • Disadvantages: • database dependent  incremental update is hard

  12. Database-Independent Range Pre-Encoding • Key insight: use additional bits in a database independent way • wider representation of ranges • reduce expansion in the worst-case

  13. Database-Independent Range Pre-Encoding • Fence encoding (W bits): • total of 2W-1 bits • encoding of i has i ones preceded by 2W-i-1 zeros • e.g. W=3, f(0) = 0000000, f(2) = 0000011 • With 2W-1 bits, fence encoding achieves an expansion of 1 Theorem: For achieving a worst-case row expansion of 1 for a W-bit range, 2W-1 bits are necessary

  14. Database-Independent Range Pre-Encoding • Procedure: • split W-bit field into multiple chunks • encode each chunk using fence encoding • “combine” the chunks to form ternary entries k0 bits k1 bits k2 bits W bits Combining chunks: analogous to multi-bit tries

  15. Unibit view of DIRPE (Prefix expansion) • W=3 divided into 3 one-bit chunks • R=[1,6]—prefixes = {001,01x,10x,110} • Each level can contribute to at most 2 prefixes (but the top level) xxx 0xx 1xx 00x 01x 10x 11x 000 001 010 011 100 101 110 111

  16. Multi-bit view of DIRPE • Legend: • 8-bit field (W=8) • k0=2, k1=3, k2=3 • R=[11,54] • =[013, 066] • split chunk = 1 Worst case expansion = 2W/k – 1 Number of extra bits needed = (2k-1)W/k - W

  17. Comparison of Expansion Worst-case expansion Real-life expansion DIRPE + DB-dependent  Net expansion was 1.12

  18. Region-based Encoding (with r regions) DIRPE (with k-bit chunks) Prefix Expansion DIRPE + Region-based Metric (2k-1) log2r F( W(2k-1) 2n-1 k F( Extra bits 0 F(log2r + ) - W) 2n-1 k ) r + r Worst-case capacity degradation 2log2r 2W )F )F - 1 ( ( (2W-2)F (2log2r)F k k Cost of an incremental update W )F ) O(( O(N) O(WF) O(N) k Pre-computed table of size: Both pieces of logic from previous two columns W.2k Overhead on the packet processor ) O( 2n-1 ) F.2W) O((log2r+ k None r logic gates ( or ) O(nF) comparators of width W bits

  19. DIRPE: Summary • Database independent • Scales well for large databases • Good incremental update properties • Additional bits needed • Small logic needed for modifying search key

  20. Problems • Range Expansion Problem • Multimatch Classification Problem

  21. Multimatch Classification Problem • TCAM search primitive: return first matching entry for a key • Multimatch requirement: return k matches (or all matches) for a key • security applications where all signatures that match this packet need to be found • accounting applications where counters have to be updated for all matching entries

  22. Earlier Approaches match Entry Invalidation scheme: • maintain state of multimatch using an additional bit in TCAM called “valid” bit TCAM array x 00100x1x001110x0x Search key x 01110xxx001100xxx 0 011101xx001100x10 1 … valid bit 1111101x1101000xx x valid bit

  23. Earlier Approaches Entry Invalidation scheme: • maintain state of multimatch using an additional bit in TCAM called “valid” bit • Disadvantage: • ill-suited for multi-threaded environments • need one bit for each thread

  24. Earlier Approaches Geometric intersection scheme: • construct geometric intersection (cross-products) of the fields and place in TCAM • pre-processing step is expensive • search is fast • Disadvantage: • does not scale well in capacity • for router dataset: expansion of 25—100

  25. Multimatch Using Discriminators (MUD) • Observation: after index j is matched, the ACL has to be searched for all indices >j • Basic idea: • store a discriminator field with each row that encodes the index of the row • to search rows with index >j, the search key is expanded to prefixes that correspond to >j • multiple searches are then issued

  26. MUD: Example match TCAM array rule0 0000 001x 01xx 1xxx Search key rule1 0001 xxxx 011101xx00 rule2 0010 … discriminator discriminator field

  27. Geometric Intersection-based Entry Invalidation MUD Metric Multi-threading support Yes Yes No Worst-case TCAM entries for N rules N O(NF) N O(N) O(NF) Update cost O(N) 1 + d + (d-1)(k-2) Cycles for k multi-matches 7k k with DIRPE: 1 + d(k-1) r without DIRPE: d Extra bits 0 0 with DIRPE: log2(d/r) + (d-r) + (2r-1) Small state machine logic; can be implemented using a few hundred gates or a few microcode instructions Small state machine logic; can be implemented using a few hundred gates or a few microcode instructions Overhead on the packet processor None

  28. MUD: Summary • No per-search state—multi-threaded • Incremental updates fast • Scales well to large databases • Additional bits needed • Extra search cycles • Can still support Gbps speeds

  29. Conclusion • Range expansion problem: proposed DIRPE, a database independent encoding • scales to large number of ranges • good incremental update properties • Multimatch classification problem: MUD • suitable for multithreaded environments • scales to large databases • No change to hardware  easy to deploy