Hardware Reference
In-Depth Information
Design
specifications
Maximum array area
A
max
Input:
Sequencing graph
of bioassay
Digital microfluidic
module library
Store
O1
O2
Mixing components
Area
Time
10 s
6 s
3 s
5s
30 s
:
20x20 array
Maximum number of
optical detectors:
4
Mix
2x2-array mixer
2x3-array mixer
2x4-array mixer
1x4-array mixer
Detectors
LED+Photodiode
4 cells
6 cells
8 cells
4 cells
O4
O3
Mix
Store
Number of reservoirs:
3
O5
Mix
Detection
Maximum bioassay
completion time
1 cell
O6
T
max
:
50 seconds
Unified Synthesis of Digital Microfluidic Biochip
Output:
Resource binding
Placement
Schedule
0
1
2
3
4
5
6
7
Operation
Resource
O1
O2
O1
O2
O3
O4
O5
O6
2x3-array mixer
2x4-array mixer
1x4-array mixer
O2
O1
Storage unit (1 cell)
O3
O4
Storage unit (1 cell)
O3
O4
O6
LED+Photodiode
O5
Biochip design results:
Array area:
8x8 array
Bioassay completion time:
25 seconds
Fig. 1.12
The high-level synthesis procedure [
41
]
The PRSA-based algorithm for digital microfluidic biochips includes two
parts, i.e., (1) the random generation of a large number of feasible synthesis
configurations for the microfluidic biochips that satisfy all the resource and
utilization constraints and dependency between operations and (2) the use of
the PRSA algorithm to select an optimized synthesis configuration from these
candidates. In this way, from a high-level specification of the bioassay, the tool
can derive synthesis results that satisfy all the constraints related to on-chip
resources and that minimize a given cost function for the given resource constraints.
Figure
1.12
illustrates the steps in the flow of high-level synthesis.
A disadvantage of the synthesis procedure of [
41
] is that it fails to consider the
routing of droplets. In some cases, all of the transportation paths for the droplets may
be blocked by other modules on the biochip, and no feasible routing solution can
be derived. To solve this problem, the authors of [
42
] proposed an improved PRSA-
based synthesis algorithm that considers the time required for the transportation of
a droplet as a criterion during design optimization. This approach can improve the
routability of the synthesis results, even though it does not generate routing paths
for the droplets or guarantee the existence of a routing solution.
Several algorithms for determining optimized droplet routing paths were pro-
posed in [
37
,
40
,
43
,
44
]. In [
37
], droplet routing was modeled as a motion-planning
problem for multiple robots, and the A
search technique was used to determine the
shortest routing path.
A fast online synthesis method that enables real-time synthesis of biochips is
proposed in [
45
]. In order to reduce the computational complexity and accelerate
the online synthesis procedure, the geometry-level synthesis procedure introduced
