High-Level Synthesis-II

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High-Level Synthesis-II. Virendra Singh Indian Institute of Science Bangalore virendra@computer.org. IEP on Digital System Synthesis @ IIT Kanpur. Architectural Synthesis. Architectural Level Abstraction Datapath Controller Architectural Synthesis - PowerPoint PPT Presentation

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High-Level Synthesis-II

Virendra SinghIndian Institute of Science

Bangalorevirendra@computer.org

IEP on Digital System Synthesis @ IIT Kanpur

Dec 18,2007 HLS@iitk 2

Architectural SynthesisArchitectural Level Abstraction

Datapath

Controller

Architectural Synthesis

• Constructing the macroscopic structure of a digital circuit starting from behavioural models that can be captured from Data flow or Sequencing Graph

Dec 18,2007 HLS@iitk 3

Architectural Synthesis

Objective

• Area

• Cycle time

• Latency

• Throughput

Worst case bound

Evaluation

Architectural Exploration

Dec 18,2007 HLS@iitk 4

Architectural Synthesis

Architectural synthesis tool can select an appropriate design point according to some user specific criterion and construct corresponding user specific Datapath and Controller

Circuit Specification for Architectural Synthesis

• Behavioural circuit model

• Details about resources being used and constraints

•Capture by Sequencing Graph

Dec 18,2007 HLS@iitk 5

Architectural Synthesis

Resources

• Functional Resources

• Primitive Resources

• Application Specific Resources

• Memory Resources

• Interface Resources

Dec 18,2007 HLS@iitk 6

Architectural Synthesis

Circuit Specification

• Sequencing Graph

• A set of functional resources, fully characterized in terms of area and execution delay

• A set of constraints

Dec 18,2007 HLS@iitk 7

Architectural Synthesis

Computation: Differential Equation Solver

xl = x + dx

ul = u – (3*x*u*dx) – (3*y*dx)

c = xl < a

Data Flow Graph (DFG): represent operation and data dependencies

Dec 18,2007 HLS@iitk 8

Data Flow Graph

* * * +

*

*

* + <

--

1 2

3

4

5

6

7

8

9

10

11

x

3

u dx 3 yu

dxx dx

u

dx y a

c

xl

yl

ul

Dec 18,2007 HLS@iitk 9

Sequencing Graph

* * * +

*

*

* + <

--

NOP

NOP

1 2

3

4

5

6

7

8

9

10

11

Dec 18,2007 HLS@iitk 10

Hierarchical Sequencing Graph

NOP

*

CALL

+

*

*+

NOP

NOP

NOP

a.0

a.3

a.2

a.1

a.4

a.n

b.0

b.n

b.2b.1

Dec 18,2007 HLS@iitk 11

Architectural Synthesis

Architectural Synthesis and optimization consistes of two stages

1. Placing the operation in time and in space, i.e., determining their time interval of execution and binding to resources

2. Determining detailed interconnection of the datapath and the logic-level specifications of the control unit

Dec 18,2007 HLS@iitk 12

Temporal Domain: Scheduling

Delay D = {di; i = 0,1, 2, ….. n}

Start time T ={ti; i= 0, 1, …., n)

Scheduling: Task of determining the start timing, subject to preceding constraints specified by sequencing graph

Latency λ = tn – t0

Dec 18,2007 HLS@iitk 13

Temporal Domain: Scheduling

A scheduled sequencing graph is a vertex-weighted sequencing graph, where each vertex is labeled by its start time

Operation Start time

V1,V2, v6,v8, v10 1

V3, v7, v9,v11 2

V4 3

V5 4

Chaining

Dec 18,2007 HLS@iitk 14

Temporal Domain: Scheduling

* * * +

*

*

* + <

--

NOP

NOP

1 2

3

4

5

6

7

8

9

10

11

TIME 1

TIME 2

TIME 3

TIME 4

Dec 18,2007 HLS@iitk 15

Temporal Domain: Scheduling

*

*

*

+

*

*

*

+

<

-

-

NOP

NOP

1

2

3

4

5

6

7

8

9

10

11

TIME 1

TIME 2

TIME 3

TIME 4

TIME 5

TIME 6

TIME 7

Dec 18,2007 HLS@iitk 16

Spatial Domain: Binding

A fundamental concept that relates operation to resources is binding

• Resource types

• Resource sharing

Simple case of binding is a dedicated resources

Dec 18,2007 HLS@iitk 17

Spatial Domain: Binding

β(v1) = (1,1)

β(v2) = (1,2)

β(v3) = (1,3)

β(v4) = (2,1)

β(v5) = (2,2)

..

Dec 18,2007 HLS@iitk 18

Spatial Domain: Binding

* * * +

*

*

* + <

--

NOP

NOP

1 2

3

4

5

6

7

8

9

10

11

TIME 1

TIME 2

TIME 3

TIME 4

Dec 18,2007 HLS@iitk 19

Spatial Domain: Binding

A necessary condition for resource binding to produce a valid circuit implementation is that operation corresponding to the shared resource do not execute concurrently

A resource binding can be represented by a labeled hyper-graph, where the vertex set V represents operations and the edge set Eβ represents the binding of the operation to the resources

Dec 18,2007 HLS@iitk 20

Spatial Domain: Binding

* * * +

*

*

* + <

--

NOP

NOP

1 2

3

4

5

6

7

8

9

10

11

TIME 1

TIME 2

TIME 3

TIME 4

n

(1,1) (1,2) (1,3) (1,4)(2,2)

(2,1)

Dec 18,2007 HLS@iitk 21

Spatial Domain: Binding

* * * +

* **+

<

--

NOP

NOP

1 2

3

4

5

6

78

9

10

11

TIME 1

TIME 2

TIME 3

TIME 4

0

n

Dec 18,2007 HLS@iitk 22

Sequencing Graph

* * * +

*

*

* + <

--

NOP

NOP

1 2

3

4

5

6

7

8

9

10

11

Dec 18,2007 HLS@iitk 23

Hierarchical Sequencing Graph

NOP

*

CALL

+

*

*+

NOP

NOP

NOP

a.0

a.3

a.2

a.1

a.4

a.n

b.0

b.n

b.2b.1

(1,2)

(1,1)

(2,1)

Dec 18,2007 HLS@iitk 24

Synchronization

* SYN

+ +

NOP

NOP

0

1a

2 3

n

Dec 18,2007 HLS@iitk 25

Synchronization

*SYN

+ +

NOP

NOP

0

1

a

2 3

n

* SYN

+ +

NOP

NOP

0

1a

2 3

n

Dec 18,2007 HLS@iitk 26

Synchronization

*SYN

+

+

NOP

NOP

0

1

a

2

3

n

Dec 18,2007 HLS@iitk 27

Area/Performance Estimation

Accurate area and performance estimation is not an easy task

Schedule: provides latency

Binding: provides information about the area

Dec 18,2007 HLS@iitk 28

Retiming

+

Host

δ

+

δ

+

δ δ

Dec 18,2007 HLS@iitk 29

Retiming

Vg

Vh

Va

Vf

Vb

Ve

Vc Vd

7 7 70

3 3 3

3

00

0 0

0

00

11 1 1

Dec 18,2007 HLS@iitk 30

Retiming

Vg

Vh

Va

Vf

Vb

Ve

Vc Vd

7 7 70

3 3 3

3

00

0 0

0

00

1 11 1

Delay = 24

Dec 18,2007 HLS@iitk 31

Retiming

Vg

Vh

Va

Vf

Vb

Ve

Vc Vd

7 7 70

3 3 3

3

00

0 0

1

00

11 0 1

Dec 18,2007 HLS@iitk 32

ASAP Scheduling

* * * +

*

*

* + <

--

NOP

NOP

1 2

3

4

5

6

7

8

9

10

11

TIME 1

TIME 2

TIME 3

TIME 4

Dec 18,2007 HLS@iitk 33

ASAP Scheduling

ASAP(Gs(V,E)){

Schedule v0 by setting t0s = 1;

repeat{

select vertex vi whose predecessors are all scheduled;

schedule vi by setting tis = max{tjs+ dj}

} untill (vn is scheduled)

return ts

}

Dec 18,2007 HLS@iitk 34

ALAP Scheduling

* *

*+

*

**+ <

--

NOP

NOP

1 2

3

4

5

6

7 8

9

10

11

TIME 1

TIME 2

TIME 3

TIME 4

Dec 18,2007 HLS@iitk 35

Scheduling under Timing Constraints

Scheduling under latency constraints

Absolute constraints on start time

Relative constraints

Relative timing constraints are positive integers specified for some operation pair vi, vj

A minimum timing constraint lij ≥ 0 requires tj ≥ ti+lij

A maximum timing constraint uij ≤ 0 requires tj

≤ ti+uij

Dec 18,2007 HLS@iitk 36

Constraint Graph

* *

+ +

NOP

NOP

0

13

2 4

n

Min

Time

4Max

Time

3

Dec 18,2007 HLS@iitk 37

Constraint Graph0

4

* *

+ +

NOP

NOP

13

2

n

Min

Time

4

Max

Time

3

* *

+ +

NOP

NOP

13

2

n

4

0

0 04

222- 3

11

Dec 18,2007 HLS@iitk 38

Relative SchedulingScheduling under unbounded delay

The anchors of a constraint graph G(V,E) consists of the source vertex v0and all vertices with unbounded delay

Redundant anchor

Dec 18,2007 HLS@iitk 39

Sequencing Graph

1

3

* SYN

+ +

NOP

NOP

0

a

2

n

Dec 18,2007 HLS@iitk 40

Scheduling with Resource Constraint

Scheduling under resource constraints

• computing area/latency trade-off points

Problems

• Intractable problem

•Area-performance trade-off points are affected by the other factors - non-resource dominated circuits

Dec 18,2007 HLS@iitk 41

Scheduling with Resource Constraint

ILP Formulation

Binary decision variable X = {xil}

1. Start time of each operation is unique

Σl xil = 1

2. Sequencing relations represented by Gs(V,E) must be satisfied

Σl xil ≥ Σl xjl + dj

3. Resource bound must be met at every schedule step

Σk Σm xim ≤ ak

Dec 18,2007 HLS@iitk 42

ILP FormulationAll operation must start only once

x0,1 = 1

x1,1 = 1

x2,1 = 1

x3,2 = 1

x4,3 = 1

x5,4 = 1

x6,1 + x6,2 = 1

x7,2 + x7,3 = 1

x8,1 + x8,2+x8,3 = 1

x9,2 + x9,3+x9,4 = 1

x10,1 + x10,2+x10,3 = 1

x11,2 + x11,3+x11,4 = 1

xn,5 = 1

Dec 18,2007 HLS@iitk 43

ILP FormulationConstraints – based on sequencing

(more than one starting time for at least one operation)

2 x7,2 + 3 x7,3 – x6,1 – 2 x6,2 – 1 ≥ 0

2 x9,2 + 3 x9,3 + 4 x9,4 – x8,1 – 2 x8,2 – 3 x8,3 – 1 ≥ 0

2 x11,2 + 3 x11,3 + 4 x11,4 – x10,1 – 2 x10,2 – 3 x10,3 – 1 ≥ 0

4 x5,4 – 2 x7,2 – 3 x7,3 – 1 ≥ 0

5 xn,5 – 2 x9,2 – 3 x9,3 – 4 x9,4 – 1 ≥ 0

5 xn,5 – 2 x11,2 – 3 x11,3 – 4 x11,4 – 1 ≥ 0

Dec 18,2007 HLS@iitk 44

ILP FormulationResource Constraints

x1,1 + x2,2 + x6,1 + x8,1 ≤ 2

x3,2 + x6,2 + x7,2 + x8,2 ≤ 2

x7,3 + x8,3 ≤ 2

x10,1 ≤ 2

x9,2 + x10,2 + x11,2 ≤ 2

x4,3 + x9,3 + x10,3 + x11,3 ≤ 2

x5,4 + x9,4 +x11,4 ≤ 2

Dec 18,2007 HLS@iitk 45

ILP Formulation

Optimize ΣiΣl l.xil

x6,1 + 2 x6,2 + 3 x7,2 + 3 x7,3 + x8,1 + 2 x8,2 + 3 x8,3

+ 2 x9,2 + 3 x9,3 + 4 x9,4 + x10,1 + 2 x10,2 + 3 x10,3

+ 2 x11,2 + 3 x11,3 + 4 x11,4

Dec 18,2007 HLS@iitk 46

Resource SharingResource sharing: Assignment of resource to more than one operation

Goal: Reduce area

Resource binding: explicit definition of mapping between resources and operation

Binding may imply some resources are shared

Dec 18,2007 HLS@iitk 47

Optimum Schedulingunder Resource Constraint

* *

*

+

*

**+

<

--

NOP

NOP

1 2

3

4

5

6

7 8

9

10

11

TIME 1

TIME 2

TIME 3

TIME 4

Dec 18,2007 HLS@iitk 48

Scheduled Sequencing Graph

* *

*

+

*

**+

<

--

NOP

NOP

1 2

3

4

5

6

7 8

9

10

11

TIME 1

TIME 2

TIME 3

TIME 4

Dec 18,2007 HLS@iitk 49

Compatibility Graph

3

6

1 8

7 2

4

9

10

115

Dec 18,2007 HLS@iitk 50

Conflict Graph

3

6

1 8

7 2

4

9

10

115

Dec 18,2007 HLS@iitk 51

Transitive orientation of Compatibility Graph

3

6

1 8

7 2

4

9

10

115

Dec 18,2007 HLS@iitk 52

Resource Sharing in Non-Hierarchical Seq. Graph

Searching for binding compatible

Σr bir = a

Σbir Σ xim ≤ 1

Dec 18,2007 HLS@iitk 53

Scheduled and Bound Sequencing Graph

* *

*

+

*

**+

<

--

NOP

NOP

1 2

3

4

5

6

7 8

9

10

11

TIME 1

TIME 2

TIME 3

TIME 4

(1,1)

(1,2)

(2,1)

(2,2)

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