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Network Algorithms, Lecture 3: Exact Lookups

Network Algorithms, Lecture 3: Exact Lookups. George Varghese. Course Goal. Network Algorithms : Algorithms for key bottlenecks in a router (lookups, switching, QoS) How to attack new bottlenecks: Changing world -> measurement, security

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Network Algorithms, Lecture 3: Exact Lookups

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  1. Network Algorithms, Lecture 3: Exact Lookups George Varghese

  2. Course Goal • Network Algorithms: Algorithms for key bottlenecks in a router (lookups, switching, QoS) • How to attack new bottlenecks: Changing world -> measurement, security • Algorithmics: Models and Principles. System thinking + Hardware + Algorithms

  3. Plan for Rest of Lecture • Part 1: Exact Match Algorithms • Part 2: Small Transition to Longest Match

  4. Context 1 Challenge-and-response' is a formula describing the free play of forces that provokes new departures in individual and social life. An effective challenge stimulates men to creative action ---- Arnold Toynbee • Query species key K. Retrieve state associate with K. Memory references crucial. • Simplest lookup problem, yet crucial for a bridge. Birthed by 3 challenges

  5. Challenges that led to Bridges • Challenge: Ethernets under fire. Routers slow. • Packet repeater learning bridge

  6. Challenge 2: Wire Speed • Without wire speed, can lose packets to forward in stream of packets to filter. • Finesse: 2 lookups per port in 51.2 usec

  7. Attention to Algorithmics • Architecture: 4-port cheap DRAM with cycle time of 100 nsec for packet bufers and lookup memory. Bus parallelism, memory bandwidth, page mode. • Data Copying: Ethernet chips used DMA, packets copied from one port to other by flpping pointers. • Control Overhead: Interrupt overhead minimized by processor polling, staying in a loop after a packet interrupt. • Lookups: Used caveats. Wrote software to verify lookup bottleneck (Q2)

  8. Eight cautionary questions • Q1, Worth improving performance? Yes. • Q2, Really a bottleneck? 68,000 code timing did not meet 25.6 usec budget. • Q3 Impact on system? Allows wire-speed. • Q4, Initial analysis shows benefits? DRAM references = log 8000, so 1.3 usec. • Q5, Worth adding custom hardware? Cheap using a PAL. • Q6, Do Prototypes confirm promise? Lab prototype tested before product was built. • Q7: Sensitive to environment changes? Worst-case design

  9. Challenge 3: Higher Speeds • Scaling via hashing for FDDI bridge (10 Mbps). Collisions? Use Perfect hashing. • A(x) * M(x) / G(x), A(x) picked randomly

  10. Improvement 1: Wide Words Intuition: More choice (d words per location) Srinivasan-Varghese H(C) A, B, C D, -, -

  11. Improvement 2: Parallelism Intuition: k independent choices (Broder-Karlin) X A B H3(B) H1(B) H2(B)

  12. State of the Art: d-left Intuition: Combine  d-left: Broder, Mitzenmacher X, Y A, L R, B H3(B) H1(B) H2(B)

  13. Binary Search can also work • Use hardware parallelism. • Seemingly clever. Easier way to see this?

  14. Lessons • Challenge-Response: Bridges invented to solve a problem (slow multi-protocol routers) not present today. • Cost-Performance: is what justies bridges today in so-called switches together with a small number of extra features like VLANs. • Introduced techniques: Broke wire-speed barrier, spread to routers, ideas like fast lookups, trading updates for lookup speed, minimal hardware all became classical.

  15. Summary • P1: Relax Specification for efficiency • P2: Utilize degrees of freedom • P3: Shift Computation in Time • P4: Avoid Waste seen in a holistic view • P5: Add State for efficiency • P6: Exploit hardware parallelism and memories. • P7: Pass information (e.g., hints) in interfaces • P8: Use finite universe methods (bucket-sort etc) • P9: Use algorithmic thinking • P10: Optimize the Expected Case

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