ECE 526 - PowerPoint PPT Presentation

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ECE 526

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ECE 526 Network Processing Systems Design System Implementation Principles II Varghese Chapter 3 * – PowerPoint PPT presentation

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Title: ECE 526


1
ECE 526 Network Processing Systems Design
  • System Implementation Principles II
  • Varghese Chapter 3

2
Outline
  • Review Principle 1-7
  • Implementation principles
  • Reflect what we learned
  • Example TCAM updating
  • Cautionary Questions

3
Reviews
  • P1 Avoid Obvious Waste
  • Example copy packet pointer instead of packet
  • P2 Shift Computation in Time
  • precompute (table lookup),
  • evaluate lazily (network forensics)
  • Share Expenses (batch processing)
  • P3 Relax Subsystem Requirements
  • Trade certainty for time (random sampling)
  • Trade accuracy for time (hashing, bloom filter)
  • Shift computation in space (fast path/slow path)

4
Reviews
  • P4 Leverage Off-System Components
  • Examples Onboard Address Recognition
    Filtering, cache
  • P5 Add Hardware to Improve Performance
  • Use memory interleaving, pipelining (
    parallelism)
  • Use Wide-word parallelism (save memory accesses)
  • Combine SRAM, DRAM (low-order bits each counter
    in SRAM for a large number of counters)
  • P6 Replace inefficient general routines with
    efficient specialized ones
  • Examples NAT using forwarding and reversing
    tables
  • P7 Avoid Unnecessary Generality
  • Examples RISC, microengine

5
P8 Don't be tied to reference implementations
  • Key Concept
  • Implementations are sometimes given (e.g. by
    manufacturers) as a way to make the specification
    of an interface precise, or show how to use a
    device
  • These do not necessarily show the right way to
    think about the problemthey are chosen for
    conceptual clarity!
  • Examples
  • Using parallel packet classification instead of
    sequential demultiplexing in TCP/IP protocols

6
P9 Pass hints across interfaces
  • Key Concept if the caller knows something the
    callee will have to compute, pass it (or
    something that makes it easier to compute) as an
    argument!
  • "hint" something that makes the recipient's
    life easier, but may not be correct
  • "tip" hint that is guaranteed to be correct
  • Caveat callee must either trust caller, or
    verify (probably should do both)
  • Example
  • Active message, the message carry the address of
    interrupt handler for fast dispatching

7
P10 Pass hints in protocol headers
  • Key Concept If sender knows something receiver
    will have to compute, pass it in the header
  • Example
  • Tag switching, packet contains extra information
    beside the destination address for fast lookup

8
P11 Optimize the Expected Case
  • Key Concept If 80 of the cases can be handled
    similarly, optimize for those cases
  • P11a Use Caches
  • A form of using state to improve performance
  • Example
  • TCP input "header prediction"
  • If an incoming packet is in order and does what
    is expected, can process in small number of
    instructions

9
P12 Add or Exploit State to Gain Speed
  • Key Concept Remember things to make it easier
    to compute them later
  • P12a Compute incrementally
  • Here the idea is to "accumulate" as you go,
    rather than computing all-at-once at the end
  • Example
  • Incremental computation of IP checksum

10
P13 Optimize Degrees of Freedom
  • Key Concept be aware of variables under ones
    control and evaluation criteria used determine
    good performance
  • Example memory-based string matching algorithm
  • possible transitions from each state for a
    character is 256 (28, ASCII coding using 8
    bit)
  • Bit-split algorithm using 8 machines, each
    machine only check for one bit, the total
    possible transitions for a character is 16 (21
    8)

11
P14 Use special techniques for finite universes
(e.g. small integers)
  • Key Concept when the domain of a function is
    small, techniques like bucket sorting, bitmaps,
    etc. become feasible.
  • Example
  • bucket sorting for NAT table lookup
  • NAT table is very sparse
  • Each bucket is accessed by hashing
  • Bucket sort
  • Partitioning an array into a finite number of
    bucket
  • Each bucket is sorted individually

12
P15 Use algorithmic techniques to create
efficient data structures
  • Key Concept once P1-P14 have been applied, think
    about how to build an ingenious data structure
    that exploits what you know
  • Examples
  • IP forwarding lookups
  • PATRICIA trees (data structure) were first
  • A special trie, with each edge of patricia tree
    labled with sequences of characters.
  • Then many other more-efficient approaches

13
TCAM
  • Ternary 0, 1 and (wildcard)
  • TCAM specified length of key and associated
    actions
  • TCAM lookup compare the query with all keys in
    parallel, output (in one cycle) the lowest memory
    location whose key matches the input
  • IP forward uses longest-prefix matching
  • DIP 010001 matches both 010001 and 01
  • Using TCAM for IP forwarding, requires put all
    longer prefixes occur before any shorter ones.

14
IP Lookup
  • All prefixes with the same length are group
    together
  • the shortest prefix 0 are in the highest memory
    address
  • The packet with DIP 110001 matches prefix of
    both P3 and P5
  • P5 is chosen due to longest-prefix matches

15
Routing Table Update
  • 11 with P1 needed to insert to routing table
  • Naïve create space in group of length-2 prefix,
    and pushing up one position all prefixes of
    length-2 and higher
  • Core routing table have 100, 000 entries ? 100,
    000 memory accesses

16
Routing Table Update
  • P13 understand the exploit degrees of freedom --
    we can add 11 at any position of group 2, not
    required after 10.
  • We can add boundary of group 2 and group 3.

17
Clever Routing Table Updating
  • the maximum memory accesses is 32 i.

18
Cautionary Questions
  • Q1 Is improvement really needed?
  • Q2 Is this really the bottleneck?
  • Q3 What impact will change have on rest of
    system?
  • Q4 Does BoE-analysis indicate significant
    improvement?
  • Q5 Is it worth adding custom hardware?
  • Q6 Can protocol change be avoided?
  • Q7 Do prototypes confirm the initial promise?
  • Q8 Will performance gains be lost if environment
    changes?

19
Summary
  • P1-P5 System-oriented Principles
  • These recognize/leverage the fact that a system
    is made up of components
  • Basic idea move the problem to somebody elses
    subsystem
  • P6-P10 Improve efficiency without destroying
    modularity
  • Pushing the envelope of module specifications
  • Basic engineering system should satisfy spec but
    not do more
  • P11-P15 Local optimization techniques
  • Speeding up a key routine
  • Apply these after you have looked at the big
    picture

20
Reminder
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