The Concurrent Matching Switch Architecture Bill Lin (University of California, San Diego) Isaac Keslassy (Technion, Israel)
IEEE INFOCOM, Barcelona, April 23-29, Motivation Traffic demands expected to grow, driven in part by increasing broadband adoption 10x increase in broadband subscription in just last 3 years, already over 100 million subscribers Gbps fiber to homes emerging (GPON, GEPON, EPON, BPON …) Larger routers needed for consolidation Operators need scalable routers that provide good performance
IEEE INFOCOM, Barcelona, April 23-29, Limitations of Previous Routers Output-Queueing (OQ) Switch Well-known to provide good performance, but scalability hampered by need for internal N speedup Crossbar Switches, using Input-Queueing (IQ) or Combined Input-Output Queueing (CIOQ) Huge body of literature, but scalability hampered by need for centralized scheduling and arbitrary per- packet switch configurations
IEEE INFOCOM, Barcelona, April 23-29, Limitations of Previous Routers Load-Balanced Routers No centralized scheduler Scalable fixed configuration switch fabric in optics Guarantees 100% throughput 100 Tb/s design with 160 Gb/s linecards shown But packets may be delivered “out-of-order”
IEEE INFOCOM, Barcelona, April 23-29, Out R R R R/N R R R Basic Load-Balanced Router R/N In Linecards A1 A2 A3 B1 C1 C2 B1 B2 C1
IEEE INFOCOM, Barcelona, April 23-29, Out R R R R/N R R R Basic Load-Balanced Router R/N In Linecards A1 A2 A3 B1 C1 C2 B1 B2 C1 Many Fabric Options (any spreading device) Space: Full uniform mesh Wavelength: Static WDM Time: Round-robin switches Just need fixed uniform rate channels at R/N No dynamic switch reconfigurations Many Fabric Options (any spreading device) Space: Full uniform mesh Wavelength: Static WDM Time: Round-robin switches Just need fixed uniform rate channels at R/N No dynamic switch reconfigurations
IEEE INFOCOM, Barcelona, April 23-29, Out R R R R/N R R R Basic Load-Balanced Router R/N In Linecards A1 A2 A3 B1 C1 C2 B1 B2 C1 Out of Order !
IEEE INFOCOM, Barcelona, April 23-29, Packet Ordering Problem Out-of-order packet delivery is undesirable (e.g. bad for TCP) Previous techniques (e.g. EDF, UFS, FOFF) Accumulate and delay packets at input/middle ports And/or delay and re-order packets at middle/output ports However, these techniques are unsatisfactory because they add substantial delays
IEEE INFOCOM, Barcelona, April 23-29, Impact on Avg. Delay (N = 128, uniform traffic) Basic Load-Balanced UFS FOFF Significant Delay
IEEE INFOCOM, Barcelona, April 23-29, Concurrent Matching Switch (CMS) Basic idea Retain load-balanced router structure and scalability of a fixed optical mesh, no dynamic reconfiguration Instead of packets, load-balance “request tokens” to N parallel “schedulers” Each scheduler independently solves its own matching Packets delivered in order based on matching results Goal is to provide much lower average delay than accumulation-based methods for ensuring packet order while retaining 100% throughput and scalability
IEEE INFOCOM, Barcelona, April 23-29, Out R R R R R R Architecture Linecards A1 B1 C1 C2 C1 B2 C2 Retain Fixed Configuration Meshes BUT move packet buffers to INPUT A2 A3 A4
IEEE INFOCOM, Barcelona, April 23-29, Out R R R R R R Architecture Linecards A1 B1 C1 C2 C1 B2 C2 A2 A3 A Add N 2 Token Counters
IEEE INFOCOM, Barcelona, April 23-29, Out R R R R R R Arrival Phase Linecards A1 C1 C2 C1 C2 A2 A3 A B1 B2 A1 A2 B1 B2 C2 C3 C4
IEEE INFOCOM, Barcelona, April 23-29, Out R R R R R R Arrival Phase Linecards A1 C1 C2 C1 C2 A2 A3 A B1 B2 B1 B2 C2 C3 C4 A1 A2
IEEE INFOCOM, Barcelona, April 23-29, Out R R R R R R Arrival Phase Linecards A1 C1 C2 C1 C2 A2 A3 A B1 B2 A1 A2 B1 B2 C2 C3 C4
IEEE INFOCOM, Barcelona, April 23-29, Out R R R R R R Arrival Phase Linecards A1 C1 C2 C1 C2 A2 A3 A B1 B2 A1 A2 B1 B2 C2 C3 C4
IEEE INFOCOM, Barcelona, April 23-29, Out R R R R R R Matching Phase Linecards A1 C1 C2 A2 A3 A B1 B2 A1 A2 B1 B2 C1 C2 C1 C2 C3 C4
IEEE INFOCOM, Barcelona, April 23-29, Out R R R R R R Matching Phase Linecards A1 C1 C B1 A2 A3 A4 B1 A1 A2 C1 B1 B2 C2 C1 C2 C3 C4
IEEE INFOCOM, Barcelona, April 23-29, Out R R R R R R Matching Phase Linecards A1 C1 C B1 A2 A3 A4 B1 B2 C3 C4 A1 A2 C1 B1 C1 B2 C2
IEEE INFOCOM, Barcelona, April 23-29, Out R R R R R R Departure Phase Linecards A1 C1 C B1 A2 A3 A4 B1 B2 C3 C4 A1 A2 C1 B1 C1 B2 C2
IEEE INFOCOM, Barcelona, April 23-29, Distributed Operation All linecards operate in parallel in a fully distributed manner Arrival, matching, and departure phases overlap in a pipeline manner
IEEE INFOCOM, Barcelona, April 23-29, Main Ideas Each middle linecard acts as a “micro-router” with 1/N th of the arrival traffic Therefore, it gets N time slots to think about the schedule, time complexity amortized by a factor of N If each micro-router can guarantee 100% throughput, so can the overall switch Each micro-router can work the way that it wants, leveraging huge body of existing work on scheduling CMS provides a new way of aggregating routers together. Therefore, provides a new way of thinking about scaling routers.
IEEE INFOCOM, Barcelona, April 23-29, Practicality Well-studied randomized approximations to Maximum Weighted Matching have been shown to achieve very good results [Tassiulas 1998] [Giaccone, Prabhakar & Shah, 2003] These algorithms only require O(N) complexity using sequential hardware, but can provide 100% throughput guarantees with no speedup and good delay results Amortized over N time slots, CMS with these scheduling algorithms can achieve O(1) time complexity (independent of switch size) 100% throughput Good delay results Packet ordering
IEEE INFOCOM, Barcelona, April 23-29, Experimental Results (N = 128, uniform traffic) Basic Load-Balanced UFS FOFF CMS Difference of N time slots for matching phase
IEEE INFOCOM, Barcelona, April 23-29, Conclusions CMS is scalable Leverages scalability of fixed optical meshes Fully distributed Can achieve O(1) time complexity CMS achieves good performance Guarantees 100% throughput Guarantees packet ordering Experimentally achieves low packet delays CMS provides new way of thinking about scaling routers and connects huge body of existing literature on scheduling to load-balanced routers
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