Hardware Reference
In-Depth Information
Chapter 5
A Survey of Relevant Literature
5.1
Equations Under Synchronous Composition
Sequential synthesis offers a collection of problems that can be modeled by FSM
equations under synchronous composition. Some have been addressed in the past
with various techniques in different logic synthesis applications.
5.1.1
Hierarchical Optimization and Don't Care Sequences
In place of designing a huge monolithic FSM and then optimizing it by state
reduction and encoding, it is convenient to work with a network of smaller FSMs.
However, if each of them is optimized in isolation, part of the implementation
flexibility is lost, because no use is made of the global network information.
Hierarchical optimization calls for optimizing the FSMs of a network capturing
the global network information by means of don't care conditions. The goal of
hierarchical optimization is to optimize the FSMs of a network capturing the global
network information by means of don't care conditions. This paradigm follows the
approach taken in multi-level combinational synthesis since the beginning [27, 29],
where a lot of effort has been invested in capturing the don't cares conditions and
devising efficient algorithms to compute them or their subsets [44, 54, 57, 95].
The first source of don't care sets is due to external limitations on controlla-
bility and observability. In particular
input controllability don't cares
and
output
observability don't cares
have been defined for multi-level combinational networks
(see [57, 95]).
Definition 5.1.1.
The
input controllability don't care set
, CDC
in
, includes all
input vectors that are never produced by the environment at the network's inputs.
The
output observability don't care sets
, ODC
o
u
t
, denote all input vectors that
represent situations when an output is not observed by the environment.
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