Stacking Signal TSV for Thermal
Dissipation in Global Routing
for 3D IC
National Tsing Hua University
Po-Yang Hsu,Hsien-Te Chen,
TingTing Hwang
ASPDAC’13
Outline

Introduction

Motivation

Signal TSV Assignment and Relocation for Thermal
Dissipation

Experimental Result

Conclusion
2
Introduction

Three dimensional (3D) chip stacking by ThroughSilicon-Via (TSV) has been identified as an
effective way to achieve better performance in
speed and power [2, 3].

However, such solution inevitably encounters
challenges in thermal dissipation since stacked dies
generate significant amount of heat per unit
volume.
3
Introduction

Temperature aware 3D global routing algorithm by
inserting ”thermal vias” and ”thermal wires” to lower the thermal
resistance[4]


Performance and thermalaware Steiner routing algorithm to
place signal TSVs to reduce temperature.[11]


Reduces the temperature at the cost of extra area of ”thermal
vias”[1,6-10]
Does not fully utilize the outstanding thermal conductance of TSV in
thermal dissipation.
[12] proposed a stacked-TSV power network structure to
improve thermal dissipation by fully utilizing TSVs in power
network.

only employs stacked-TSV structure in power network.
4
Motivation
- Thermal model
 The lateral thermal resistors Rlateral
are determined by heat
conductance of device material
5
Motivation
20um
6
Motivation

Relationship between temperature and distance of stacked
signal TSV to heat source
7
Signal TSV Assignment and Relocation
for Thermal Dissipation
 Overall flow of placing signal TSVs in global
8
routing
Initial TSV Assignment
9
Initial TSV Assignment
10
Initial TSV Assignment

PowDensityi,j,k : power density in grid (i,j,k) where i, j, k
denotes coordinates of the grid node in x, y, z axis direction

high lumped power density grid needs more signal TSVs to dissipate
its heat.

n : number of tiers in the design.

TSVNumi,j,k : number of signal TSVs in grid (i,j,k).
11
Initial TSV Assignment

SDi,j is defined as the stacking degree in grid (i,j), which is
computed as the number of TSV stacking at grid position (i,j).

Larger Gain value means higher power density, less TSVs, and
more stacking signal TSVs.
12
Stacked-TSV Relocation Stage
13
Hotspot grids Identification

Hotspot grid is identified by the top 10% highest thermal
criticality grids.

define a circle region to find its saver net.
14
Hotspot grids Identification

Use a matching algorithm to find the overall best
solution.

GridDist is the summation of distance from hotspot grid
to the nearest TSV of the saver net n in all tiers.

wiring overhead if we stack the TSVs of saver net n close
to the grid g.
H
S
Weighted graph
G = ( H∪S, E)
15
Hotspot grids Identification

Use a matching algorithm to find the overall best
solution.

StackingDegree is the number of tiers that a saver net
crosses.

heat dissipation ability
H
S
Weighted graph
G = ( H∪S, E)
16
Determination of
Stacking Grid

Based on the matching solution, TSV of a saver net will
be relocated near the hotspot grid.

However, there are other factors to determine if a grid
location is the best choice.

Define candidate target grids which are hotspot grids
and the adjacent grids nearby them to determine the
best target grid location for moving signal TSV.
17
Determination of
Stacking Grid

Gain function to select our target grid to place stacked signal TSV
at grid (i, j) is defined as

Consider

Distance between candidate target grid and hotspot grid

Power density

Number of TSVs

Whitespace

Wirelength
18
Determination of
Stacking Grid

Gain function to select our target grid to place stacked signal TSV
at grid (i, j) is defined as

Consider

Distance between candidate target grid and hotspot grid

The larger DSST the closer the distance between stacking
location to the hotspot grid.
19
Determination of
Stacking Grid

Gain function to select our target grid to place stacked signal TSV
at grid (i, j) is defined as

Consider

Power density

High power density grid needs more stacked signal TSV to
dissipate its heat.
20
Determination of
Stacking Grid

Gain function to select our target grid to place stacked signal TSV
at grid (i, j) is defined as

Consider

Number of TSVs

When TSV is larger, fewer number of TSVs is in grid (i,j,k).
i,j,k
21
Determination of
Stacking Grid

Gain function to select our target grid to place stacked signal TSV
at grid (i, j) is defined as

Consider

Whitespace
22
Determination of
Stacking Grid

Gain function to select our target grid to place stacked signal TSV
at grid (i, j) is defined as

Consider
Move signal TSVs to the same 2D location across
all tiers will change the routing topology and
increase wiring overhead.

Wirelength

Wirelength is the wirelength overhead in tier k if stacking
location is at grid (i,j).

smaller value of WL denotes higher wiring overhead.
i,j,k
23
Experimental Result

2005 IWLS benchmarks [20] and industrial circuits.

3D placement results are produced by a partitioning
driven placement for 3D ICs [5].

minimize the total wirelength and signal-TSV count
24
Experimental Result
Extra hardware overhead !!!
S.TSV : Total # of Stacked TSV
25
Conclusion

A new integrated architecture, stacked signal TSV, was
developed to dissipate heat.

Based on this structure, a two-stage TSV locating algorithm
has been proposed to construct the stacked signal TSVs and
fully utilize the TSV thermal conductance to optimize the
chip temperature.

Compared to previous thermal-TSV insertion method, our
proposed algorithm has zero hardware overhead incurred by
thermal-TSV.
26