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myhdl/doc/whatsnew03/whatsnew03.tex
2003-07-31 18:22:47 +00:00

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\documentclass{howto}
% \usepackage{distutils}
\usepackage{palatino}
\renewcommand{\ttdefault}{cmtt}
\renewcommand{\sfdefault}{cmss}
\newcommand{\myhdl}{\protect \mbox{MyHDL}}
\usepackage{graphicx}
% $Id$
\title{What's New in \myhdl\ 0.3}
\release{0.3}
\author{Jan Decaluwe}
\authoraddress{\email{jan@jandecaluwe.com}}
\begin{document}
\maketitle
\tableofcontents
\section{VCD output for waveform viewing\label{section-wave}}
\ifpdf
\includegraphics{tbfsm.png}
\fi
\myhdl\ now has support for waveform viewing. During simulation, signal
changes can be written to a VCD output file. The VCD file can then be
loaded and viewed in a waveform viewer tool such as \program{gtkwave}.
The user interface of this feature consists of a single function,
\function{traceSignals()}. To explain how it works, recall that in
\myhdl{}, an instance is created by calling a function that returns a
sequence of generators, and by assigning the result to an instance
name. For example:
\begin{verbatim}
tb_fsm = testbench()
\end{verbatim}
To enable VCD tracing, the instance should be created as follows
instead:
\begin{verbatim}
tb_fsm = traceSignals(testbench)
\end{verbatim}
All signals in the instance hierarchy will be traced in
an output VCD file called \file{tb_fsm.vcd}. Note that the argument of
\function{traceSignals()} consists of the uncalled function. By calling
the function under its control, \function{traceSignals()} gathers
information about the hierarchy and the signals to be traced. In
addition to a function argument, \function{traceSignals()} accepts an
arbitrary number of non-keyword and keyword arguments that will be
passed to the function call.
The restrictions on VCD tracing are as follows. First, only
\class{Signal} objects can be traced. Second, only a hierarchy of
instances returned by a pre-simulation top level function call can be
traced.
Signals are dumped in a suitable format. This format is inferred at
the \class{Signal} construction time, from the type of the initial
value. In particular, \class{bool} signals are dumped as single
bits. (This only works starting with Python2.3, when \class{bool} has
become a separate type). Likewise, \class{intbv} signals with a
defined bit width are dumped as bit vectors. To support the general
case, other types of signals are dumped as a string representation, as
returned by the standard \function{str()} function.
\begin{notice}[warning]
Support for literal string representations is not part of the VCD
standard. It is specific to \program{gtkwave}. To generate a
standard VCD file, you need to use signals with a defined bit width
only.
\end{notice}
\section{An enumeration type\label{section-enum}}
It is often desirable to define a set of identifiers. A standard
Python idiom for this purpose is to assign a range of integers to a
tuple of identifiers, like so:
\begin{verbatim}
>>> SEARCH, CONFIRM, SYNC = range(3)
>>> CONFIRM
1
\end{verbatim}
However, this technique has some drawbacks. Though it is clearly
the intention that the identifiers belong together, this information
is lost as soon as they are defined. Also, the identifiers evaluate to
integers, whereas a string representation of the identifiers
would be preferable. To solve these issues, we need an
\emph{enumeration type}.
\myhdl\ 0.3 supports enumeration types by providing a function
\function{enum()}. The arguments to \function{enum()} are the string
representations of the identifiers, and its return value is an
enumeration type. The identifiers are available as attributes of the
type. For example:
\begin{verbatim}
>>> from myhdl import enum
>>> t_State = enum('SEARCH', 'CONFIRM', 'SYNC')
>>> t_State
<Enum: SEARCH, CONFIRM, SYNC>
>>> t_State.CONFIRM
CONFIRM
\end{verbatim}
Enumeration types are often used for the state variable in a finite
state machine. In the waveform in Section~\ref{section-wave}, you see
a \class{Signal} called \code{state} which as been constructed with an
enumeration type identifier as initial value, as follows:
\begin{verbatim}
state = Signal(t_State.SEARCH)
\end{verbatim}
Note that the waveforms show the string representation of the
enumeration type identifiers.
\section{Inferring the sensitivity list for combinatorial
logic\label{section-combinatorial}}
In \myhdl{}, combinatorial logic is described by a generator function with
a sensitivity list that contains all inputs signals (the signals that
are read inside the function).
It may be easy to forget some input signals, especially it there are a
lot of them or if the code is being modified. There are various ways
to solve this. One way is to use a sophisticated editor. Another way
is direct language support. For example, recent versions of Verilog
have the \code{always~@*} construct, that infers all input
signals. The SystemVerilog 3.1 standard improves on this by
introducing the \code{always_comb} block with slightly enhanced
semantics.
\myhdl\ 0.3 provides a function called \function{always_comb()} which
is named and modeled after the SystemVerilog counterpart.
\function{always_comb()} takes a single classic function as its
argument. This function should be a locally defined function that
specifies what should happen when one of its input signals
changes. \function{always_comb()} returns a generator that is
sensitive to all inputs, and that will run the function whenever an
input changes.
For example, suppose that we have a mux module described as follows:
\begin{verbatim}
def mux(z, a, b, sel):
""" Multiplexer.
z -- mux output
a, b -- data inputs
sel -- control input
"""
def logic()
while 1:
yield a, b, sel
if sel == 1:
z.next = a
else:
z.next = b
mux_logic = logic()
return mux_logic
\end{verbatim}
Using \function{always_comb()}, we can describe it as follows instead:
\begin{verbatim}
def mux(z, a, b, sel):
""" Multiplexer.
z -- mux output
a, b -- data inputs
sel -- control input
"""
def logic()
if sel == 1:
z.next = a
else:
z.next = b
mux_logic = always_comb(logic)
return mux_logic
\end{verbatim}
\section{Inferring the list of all instances\label{section-instances}}
In \myhdl{}, the instances defined in a top level function
need to be returned explicitly. The following is a schematic
example:
\begin{verbatim}
def top(...):
...
instance_1 = module_1(...)
instance_2 = module_2(...)
...
instance_n = module_n(...)
...
return instance_1, instance_2, ... , instance_n
\end{verbatim}
This permits fine grained control: for example, it
is possible to return a different set of instances
under parameter control.
However, having to return instances explicitly can be inconvenient,
especially if there are a large number of them. Therefore, \myhdl\ 0.3
provides a function \function{instances()} which assembles a list of
all instances automatically. It is used as follows:
\begin{verbatim}
from myhdl import instances
def top(...):
...
instance_1 = module_1(...)
instance_2 = module_2(...)
...
instance_n = module_n(...)
...
return instances()
\end{verbatim}
Function \function{instances()} uses introspection to inspect the type
of the local variables defined by the calling function. In \myhdl {},
an instance is defined as a nested sequence of generators: all such
variables are looked up and assembled in a list.
\section{Inferring the list of all processes\label{section-processes}}
In addition to instances, a top level function may
also define local generators functions, which I will
call \emph{processes} because of the analogy with VHDL.
Like instances, processes need to be returned explicitly,
with the qualification that they have to be called first
to turn them into generators. The following is a schematic
example:
\begin{verbatim}
def top(...):
...
def process_1():
...
def process_2():
...
...
def process_n():
...
...
return process_1(), process_2(), ..., process_n()
\end{verbatim}
As for instances, it may be more convenient to assemble the list of
processes automatically. One option is to turn each process into an
instance by calling it and assigning the returned generator to a local
variable. Those instances will then be found by the
\function{instances()} function described in
Section~\ref{section-instances}.
Another option is to use the function \function{processes()} provided
by \myhdl\ 0.3 . This function uses introspection to find the
processes, calls each of them, and assembles the returned generators
into a list. It can be used as follows:
\begin{verbatim}
from myhdl import processes
def top(...):
...
def process_1():
...
def process_2():
...
...
def process_n():
...
...
return processes()
\end{verbatim}
To conclude, a top level function with both instances and processes
can use the following idiomatic code to return all of them:
\begin{verbatim}
return instances(), processes()
\end{verbatim}
\section{Class \class{intbv} enhancements\label{section-intbv}}
Class \class{intbv} has been enhanced with new features.
It is now possible to leave the left index of a slicing operation
unspecified. The meaning is to access ``all'' higher order bits. For
example:
\begin{verbatim}
>>> from myhdl import intbv
>>> n = intbv()
>>> hex(n)
'0x0'
>>> n[:] = 0xde
>>> hex(n)
'0xde'
>>> n[:8] = 0xfa
>>> hex(n)
'0xfade'
>>> n[8:] = 0xb4
>>> hex(n)
'0xfab4'
\end{verbatim}
\class{intbv} objects now have \var{min} and \var{max} attributes
that can be specified at construction time. The meaning is that that
only values within \code{range(min, max)} are permitted. The default
values for these attributes is \var{None}, meaning ``infinite''. For
example (traceback output shortened for clarity):
\begin{verbatim}
>>> n = intbv(min=-17, max=53)
>>> n
intbv(0)
>>> n.min
-17
>>> n.max
53
>>> n[:] = 28
>>> n
intbv(28)
>>> n[:] = -18
Traceback (most recent call last):
....
ValueError: intbv value -18 < minimum -17
>>> n[:] = 53
Traceback (most recent call last):
....
ValueError: intbv value 53 >= maximum 53
\end{verbatim}
When a slice is taken from an \class{intbv} object, the return value
is a new \class{intbv} object with a defined bit width. As in
Verilog, the value of the new \class{intbv} object is always
positive, regardless of the sign of the original value. In addition,
the \var{min} and \var{max} attributes are set implicitly:
\begin{verbatim}
>>> v = intbv()[6:]
>>> v
intbv(0)
>>> v.min
0
>>> v.max
64
\end{verbatim}
Lastly, a small change was implemented with regard to
binary operations. In previous versions, both numeric
and bit-wise operations always returned a new \class{intbv}
object, even in mixed-mode operations with \class{int}
objects. This has changed: numeric operations
return an \class{int}, and bitwise operations return
a \class{intbv}. In this way, the return value corresponds
better to the nature of the operation.
\section{Function \function{concat()} \label{section-concat}}
In previous versions, the \class{intbv} class provided a
\method{concat()} method. This method is no longer
available. Instead, there is now a \function{concat()} function in
\myhdl{}, which supports a much broader range of objects.
A function is more natural because \myhdl\ objects of various types
can be concatenated: \class{intbv} objects with a defined bit width,
\class{bool} objects, the corresponding signal objects, and bit
strings. All these objects have a defined bit width. Moreover, the
first argument doesn't need to have a defined bit width. It can also be
an unsized \class{intbv}, an \class{int}, a \class{long}, or a
corresponding signal object. Function \function{concat()} returns an
\class{intbv} object.
\section{Python 2.3 support\label{section-Python}}
Python 2.3 was released on July 29, 2003, and as of this writing, it
is the latest stable Python release.
\myhdl\ 0.3 works with both Python 2.2 and Python 2.3. In good Python
tradition, \myhdl\ code developed with Python 2.2 should run without
changes or problems in Python 2.3.
In general, I am not that keen on early upgrading. However, as it
happens, the evolution of Python enables features that are really
important or even crucial to \myhdl{}. Python 2.2 generators are the
best example: they are the cornerstone of \myhdl{}. But Python 2.3
also has significant benefits, which I will summarize below.
First, generators and the \code{yield} statement are a default Python
2.3 feature. This means that \code{from __future__ import generators}
statements are no longer required.
Second, Python 2.3 has a \class{bool} type, which is implemented as a
subtype of \class{int}. For general Python use, the implications are
rather limited - the main difference is that logical result values
will print as \code{False} and \code{True} instead of \code{0} and
\code{1}. However, in \myhdl{}, I can use the \class{bool} type to
infer a bit width. If a \class{Signal} is constructed with a
\class{bool} value, it is a single bit \class{Signal}. One application
is waveform viewing as in Section~\ref{section-wave}. In the waveform,
note how single bit signals are displayed as level changes. With
Python 2.2, the waveforms of these signals would only show value
changes, which is not as clear for single bits.
Finally, Python 2.3 is significantly faster. \myhdl\ code runs
25--35\% faster in Python 2.3. This is a very nice speedup compared to
the small burden of a straightforward upgrade.
Python is a very stable language, so upgrading to Python 2.3 is
virtually risk free. Given the additional benefits, I recommend
\myhdl\ users to do so as soon as possible. For the next major
release, the new features will become crucial and only Python 2.3 (and
higher) will be supported.
\end{document}