From Miles to Millimeter:On-chip Communication

Networks

Alessandro PintoU.C. Berkeley

apinto@eecs.berkeley.edu

Alessandro Pinto

What

Communication synthesisWhat is the “best way” of transferring information between entities

Problem FormulationWho wants to communicate with whomHow he aspects the communication mechanism to behaveWhat is possible to built todayHow to build a communication architecture that is cheap and satisfies the entities constraints while being feasible

Alessandro Pinto

Chips are small, why bother?“As designs scale to newer technologies, they get smaller and their wiresget shorter, and the relative change in the speed of wires to thespeed of gates is modest.” M.A.Horowitz et.al “The future of wires”

“The real wire problem arises with increasing chip complexity and global communication costs.” M.A.Horowitz et.al “The future of wires”

Scaling

Local Wire

Global Wire

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Networks vs. On-Chip Networks

Internet major concern was to guarantee connectivity in case of attackCost is mostly staticBuffers memory is not a problem (512MB is still cheap)Number and complexity of protocol layer is important only for performance issues

Full connectivity is not the major concern

Now cost is mostly dynamic (power)Registers are expensive

The protocol must be very lightIn the future error correction might become a reality

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Communication Platform Stack

Application Space

Implementation Space

API

Topology Design

Protocol Design

Routing

Network Layer

MAC Layer

Physical Level

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The ProblemArchPltBuilderArchPltBuilder

RTOS

μC1

HW

MEM

μC2

DSP

μC1

μC2

DSP

MEM

RTOS

HWHW

MEM

To Silicon

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Basic Definitions: Comm. Graph

G(V,E,P,)V=S U V’ U D

S,D not emtpyP=Xi pi is a performance domain: E(G) PIf the graph is placed : V(G) Pos

Ce: E(G) Cost, Cv: V(G) CostCG = eE(G) Ce + vV(G) Cv

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A More General Defintion

Two types of quantitiesSeries (e.g. position of nodes)Parallel (e.g. bandwidth). Must sum up to 0 on a cut

P=PS X PP

Communication GraphG(V,E,P,, ): E(G) PP

: V(G) PS

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Flows

Defined as usual in flow networks

f: V(G) x V(G) PP

Flow between two nodes:F(u,v) = max (f(u,v))

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Graph Ordering

G1 G2S1 = S2, D1=D2, 1|S1,D1= 2|S2,D2

|V’1||V’2| For all si,dj, F1(si,dj) F2(si,dj)

G1 implements G2

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Communication Constraints Graph

Obs.: if V’= the F(u,v) = (e(u,v))

Def.: A Communication Constraint Graph is a communication graph such that V’=

Specification

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Implementation Graph

Given a communicaiton grpah G, define J(G) = {G’ |G’ G }

')('min GGJG

C

Def.: The Implementation Graph of a communication graph G is the solution to the optimization problem

Implementation

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The Optimization Problem

Given a Communication Constraint Graph G, find its Implementation Graph G’

Obs.:Two vertices s.t. (n1) = (n2) can be considered to be the same vertexAn edge s.t. (e) = 0 can be removedE connected minimum tree with n leaves has at most n-2 non leaves verticesA connected tree can be obtained by contraction or by removing edges

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The Optimization Problem

S1

S2

D1

D2

Gtosbj

GC )'(min','

defA

Gdsetosbj

GC

ji

)(''

,),(

)'(min','

(e)

f(S1,D2)

S1

S2

D1

D2

n1

n3

n4

n2

AIN

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Put the protocol into the picture

As you noticed I use for the flowsThree possibilities:

The topology design relies on the protocolThe protocol performance/cost impact the topology

The protocol design relies on the topologyThe topology performance/cost impact the protocol

A joint optimization is carried out (best result but very difficult)

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Splitting the nodes

Each AIN is split into two nodes:Network Switching Node (NSN)Network Interface Node (NIN)

NIN NSN

SNetwork

One pair for each S/D

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Trade Off Example

Characterize each source with ba,bm,bl,br

Average b., maximum b., maximum burst length, maximum blocking rate

Simple back-pressure mechanism: activate a signal to freeze the source (correspond to slowing down the source)

NIN NSN

S

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Trade Off Example: case 1

Optimize the protocol consideringQueue lengthBlocking time

Optimize the topology in the average caseThis is an abstraction of the protocol performances

i

ii

SSSS

br

baeNSNNINetosbj

brNbrk

)(),,(.

)(min

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Trade Off Example: case 2

G’ is given (the topology is fixed)For each (si,dj), F(si,dj) is known

All the things we have seen in classFind the routing algorithmFind the flow control algorithm

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Just a Taste of the LibraryPitch

Thickness

DielectricSpace

Mn

Mn+1

lcrit

buffer buffer

sopt

0

0.2

0.4

0.6

0.8

1

1.2

1.4

M1 M2 M3 M4 M5 M6

Energy(pJ)

050

100150200250300350400450

M1 M2 M3 M4 M5 M6

Sopt(*minsize)

pscrit 17

crits l

lfEP

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Conclusions

The notion of communication graph has been introduced An optimization problem has been derived for the synthesis of networksThe interaction between protocol and topology optimization has been analyzed

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Future Work

Get the software runningFind a good NLP package

Solve other mixed integer programming problems

Path uniqueness Interface with other tools

Protocol synthesisEdge covering Interface Synthesis

Use it