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Maximum Size Matchings & Input Queued Switches Sundar Iyer , Nick McKeown High Performance Networking Group, Stanford University, http://yuba.stanford.edu Allerton 2002 Wednesday, Oct 2 nd 2002

Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

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Page 1: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

Maximum Size Matchings & Input Queued Switches

Sundar Iyer, Nick McKeownHigh Performance Networking Group,Stanford University, http://yuba.stanford.edu

Allerton 2002Wednesday, Oct 2nd 2002

Page 2: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

2

Definition - 100% Throughput

A switch gives 100% throughput if the expected size of the queues is finite for any admissible (no input or output is oversubscribed) load.

Page 3: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

3

A Characteristic Switch

N=4 N=4

1 1R

R

An input queued switch with a crossbar switching fabric

Crossbar

R

R

1

N=4

1

N=4

VOQs

Page 4: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

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Maximum Size Matching

Maximum Size Matching (MSM)

Choose a matching which maximizes the size Contrary to intuition, MSM does not give 100%

throughput

Ref: [McKeown, Anantharam, Walrand - 1996], “Achieving 100% Throughput in an Input-Queued Switch“, IEEE Infocom '96.

Page 5: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

5

Contents

1. Background & Motivation

2. Non Pre-emptive Scheduling

3. Achieving 100% throughput with CMSM

• Bernoulli i.i.d. uniform traffic• Bernoulli i.i.d. non-uniform traffic

4. Achieving 100% throughput with MSM

• Bernoulli i.i.d. uniform traffic

5. Conclusion

Page 6: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

6

An ExampleMSM does not give 100% throughput

N=2 N=2

1 1R

R

Crossbar

R

R

11=0.49

12=0.50

21=0.50

22=0.00

Ref: [Keslassy, Zhang, McKeown - 2002], “MSM is unstable for any input queued switch”, In Preparation.

VOQs

Page 7: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

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Motivation

“To understand the conditions under which the class of MSMs give 100% throughput”

Page 8: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

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Questions

Do all MSMs not achieve 100% throughput?

Is there a sub class of MSMs which achieve 100% throughput?

Do all MSMs achieve 100% throughput under uniform load?

Page 9: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

9

Contents

1. Background & Motivation

2. Non Pre-emptive Scheduling

3. Achieving 100% throughput with CMSM

• Bernoulli i.i.d. uniform traffic• Bernoulli i.i.d. non-uniform traffic

4. Achieving 100% throughput with MSM

• Bernoulli i.i.d. uniform traffic

5. Conclusion

Page 10: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

10

Non Pre-emptive Scheduling … 1Batch Scheduling

Main Idea

Scheduling cells in batches increases the choice for the matching and hence increases throughput

Allow the batch size to grow

Ref: [Dolev, Kesselman - 2000], “Bounded latency scheduling scheme for ATM cells", Computer Networks, vol. 32(3) pp.325-331, 2000.

Page 11: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

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Non Pre-emptive Scheduling … 2Batch Scheduling

N N

1 1R

R

Priority-2

Crossbar

R

R

1

N

1

N

Priority-1

Batch-(k+1)

Batch-(k)

Page 12: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

12

Non Pre-emptive Scheduling … 2Batch Scheduling

N N

1 1R

R

Priority-2

R

R

1

N

1

N

Priority-1

CrossbarBatch-(k+1)

Batch-(k)

Page 13: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

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Degree of a Batch

1

2

3

01

021

0

001

1

2

3

Batch Request Graph Degree (dv,k):

The number of cells departing from (destined to) a vertex in batch k.

Maximum Degree (Dk) The maximum degree

amongst all inputs/outputs in batch k.

Page 14: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

14

2

3

1

2

3

1

2

3

1

2

3

1

2

3

1

2

3

1

1

2

3

01

021

0

001

1

2

3

Batch Request Graph with Dk =3

2

3

1

2

3

1

Maximum Size MatchingWhy may MSM not give 100% throughput?

Page 15: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

15

Critical Maximum Size MatchingA sub-class of MSM

2

3

1

2

3

1

2

3

1

2

3

1

2

3

1

2

3

1

1

2

3

01

021

0

001

1

2

3

Batch Request Graph with Dk =3

Page 16: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

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CMSM achieves 100% throughput under non pre- emptive scheduling, if the traffic is constrained to less than cells for any input/output in B timeslots.

This introduces deterministic constraints on the arrival traffic We are interested in the traditional stochastic traffic

Previous Results

Ref: [Weller, Hajek - 1997], “Scheduling non-uniform traffic in a packet-switching system with small propagation delay,” IEEE/ACM Transactions on Networking 5(6): 813-823, 1997.

, 1B

Page 17: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

17

Arrival Traffic

, :

1, 1

1. Traffi c matrix:

where expected number of

arrivals in one timeslot

2. I f ; we say the traffi c is "admissible".

3. For a Bernoulli i.

ij ij

ij iji j

A

, ( , );

i.d arrival process:

I f we say the traffi c is unif orm.ij i jN

Page 18: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

18

Contents

1. Background & Motivation

2. Non Pre-emptive Scheduling

3. Achieving 100% throughput with CMSM

• Bernoulli i.i.d. uniform traffic• Bernoulli i.i.d. non-uniform traffic

4. Achieving 100% throughput with MSM

• Bernoulli i.i.d. uniform traffic

5. Conclusion

Page 19: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

19

CMSM with Uniform Traffic

Theorem 1:

CMSM gives 100% throughput under non pre-emptive scheduling, if the input traffic is admissible and Bernoulli i.i.d. uniform

Informal Arguments:

Let Tk be the time to schedule batch k

Then for batch k+1 we buffer new arrivals for time Tk

We expect about Tk packets at every input/output

Hence, the maximum degree of batch k +1, i.e. Dk+1 Tk

Hence for a CMSM, Tk+1 = Dk+1 Tk < Tk

Hence Tk is bounded in mean.

Page 20: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

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1( ) , 0, k k k k k cE T T T T T T

1( ) (1- ) , 0, k k k k cE T T T T T

We are going to show that

Alternatively we will first show that

1 k kT NT

Observe that

Formal ArgumentsOutline

Page 21: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

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We shall use the Chernoff bound to get

If we want to bound Dk+1, we require that all the 2N vertices are bounded

(1 ), 1{ (1 ) }

(1 )

kT

v k k k veP d T T p

1{ (1 ) } 1 2k k k vP D T T Np Q

Formal Arguments … 1Bounding the degree of a batch

Page 22: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

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Choose > 0, such that .

Choose such that

We get

1(1 )

{ }2

k k kP T T T Q

(1 )

2

(1 )

4

1(1 ) 1

2

1

Formal Arguments … 2 Bounding the deviation of the service time of a batch

Page 23: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

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Hence

1( ) (1- )

(1- ) , if

(1 )

2k k

k

k kE T T Q T Q NT

T

2 2 2 1

2 1

NQ

N

kNT(1 )

2kT

0 (1- ) kT kT

1( ) <k kE T T1( ) <k kE T T

Formal Arguments … 3 Bounding the service time of a batch

{.}P Q

Page 24: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

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Choose < (1- )/2,

This gives

Observe that Q is now a function of Tk only for a constant We can make Q as close to 1, by choosing a large Tk

4 3 1

4 2 2

ifN

QN

1

(3 )( ) ,

4k k kE T T T

(1 )

4

Formal Arguments …4 Tightening the bound

Page 25: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

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Hence, there is a constant Tc such that

Formally, using a linear Lyapunov function V(Tk) = Tk, we can say that Tk (averaged over the batch index) is bounded in mean.

1

1

(3 )( ) ,

4

(1 )( ) ,

4

k k k k c

k k k k k c

E T T T T T

E T T T T T T

Formal Arguments …5Finishing Off..

Page 26: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

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In the paper we use a quadratic Lyapunov function V(Tk) = (Tk)2 , and show that Tk

2 (averaged

over the batch index) is bounded in mean.

There are a few technical steps after this to show that the queue size (averaged over time) is bounded in mean.

Then, it follows that CMSM gives 100% throughput for Bernoulli i.i.d. uniform traffic.

Formal Arguments …6Some Final Points..

Page 27: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

27

Contents

1. Background & Motivation

2. Non Pre-emptive Scheduling

3. Achieving 100% throughput with CMSM

• Bernoulli i.i.d. uniform traffic• Bernoulli i.i.d. non-uniform traffic

4. Achieving 100% throughput with MSM

• Bernoulli i.i.d. uniform traffic

5. Conclusion

Page 28: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

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CMSM with Non-Uniform Traffic

Theorem 2:

CMSM achieves 100% throughput under non pre-emptive scheduling, if the input traffic is admissible and Bernoulli i.i.d.

Page 29: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

29

Contents

1. Background & Motivation

2. Non Pre-emptive Scheduling

3. Achieving 100% throughput with CMSM

• Bernoulli i.i.d. uniform traffic• Bernoulli i.i.d. non-uniform traffic

4. Achieving 100% throughput with MSM

• Bernoulli i.i.d. uniform traffic

5. Conclusion

Page 30: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

30

Example of a Uniform Graph

1

2

3

11

111

1

111

1

2

3

Batch Request Graph with Dk =3

2

3

1

2

3

1

2

3

1

2

3

1

2

3

1

2

3

1

Page 31: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

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MSM with Non-Uniform Traffic

Theorem 3:

MSM achieves 100% throughput under non pre-emptive scheduling, if the input traffic is admissible and Bernoulli i.i.d. uniform

Page 32: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

32

Contents

1. Background & Motivation

2. Non Pre-emptive Scheduling

3. Achieving 100% throughput with CMSM

• Bernoulli i.i.d. uniform traffic• Bernoulli i.i.d. non-uniform traffic

4. Achieving 100% throughput with MSM

• Bernoulli i.i.d. uniform traffic

5. Conclusion

Page 33: Maximum Size Matchings & Input Queued Switches Sundar Iyer, Nick McKeown High Performance Networking Group, Stanford University,

33

Conclusions

We have used the more traditional stochastic arrivals and shown using batch scheduling that

CMSM gives 100% throughput for Bernoulli i.i.d. traffic MSM gives 100% throughput for Bernoulli i.i.d. uniform traffic

It would be nice to understand the stability of MSM with uniform load with continuous scheduling.