% should be used if it is desired that the figures are to be displayed in
% draft mode.
%
+
\documentclass[conference,pdf,a4paper,10pt,final,twoside,twocolumn]{IEEEtran}
% Add the compsoc option for Computer Society conferences.
%
-
-
-
% *** CITATION PACKAGES ***
%
\usepackage{cite}
% Macro for certain acronyms in small caps. Doesn't work with the
% default font, though (it contains no smallcaps it seems).
\def\acro#1{{\small{#1}}}
+\def\acrotiny#1{{\scriptsize{#1}}}
\def\VHDL{\acro{VHDL}}
\def\GHC{\acro{GHC}}
\def\CLaSH{{\small{C}}$\lambda$a{\small{SH}}}
+\def\CLaSHtiny{{\scriptsize{C}}$\lambda$a{\scriptsize{SH}}}
% Macro for pretty printing haskell snippets. Just monospaced for now, perhaps
% we'll get something more complex later on.
\newenvironment{xlist}[1][\rule{0em}{0em}]{%
\begin{list}{}{%
\settowidth{\labelwidth}{#1:}
- \setlength{\labelsep}{0.5cm}
+ \setlength{\labelsep}{0.5em}
\setlength{\leftmargin}{\labelwidth}
\addtolength{\leftmargin}{\labelsep}
+ \addtolength{\leftmargin}{\parindent}
\setlength{\rightmargin}{0pt}
\setlength{\listparindent}{\parindent}
\setlength{\itemsep}{0 ex plus 0.2ex}
\usepackage{xcolor}
\def\comment#1{{\color[rgb]{1.0,0.0,0.0}{#1}}}
+\usepackage{cleveref}
+\crefname{figure}{figure}{figures}
+\newcommand{\fref}[1]{\cref{#1}}
+\newcommand{\Fref}[1]{\Cref{#1}}
+
+\usepackage{epstopdf}
+
+\epstopdfDeclareGraphicsRule{.svg}{pdf}{.pdf}{rsvg-convert --format=pdf < #1 > \noexpand\OutputFile}
+
%include polycode.fmt
%include clash.fmt
% author names and affiliations
% use a multiple column layout for up to three different
% affiliations
-\author{\IEEEauthorblockN{Christiaan P.R. Baaij, Matthijs Kooijman, Jan Kuper, Marco E.T. Gerards, Bert Molenkamp, Sabih H. Gerez}
-\IEEEauthorblockA{University of Twente, Department of EEMCS\\
+\author{\IEEEauthorblockN{Christiaan P.R. Baaij, Matthijs Kooijman, Jan Kuper, Marco E.T. Gerards}%, Bert Molenkamp, Sabih H. Gerez}
+\IEEEauthorblockA{%Computer Architecture for Embedded Systems (CAES)\\
+Department of EEMCS, University of Twente\\
P.O. Box 217, 7500 AE, Enschede, The Netherlands\\
-c.p.r.baaij@@utwente.nl, matthijs@@stdin.nl}}
+c.p.r.baaij@@utwente.nl, matthijs@@stdin.nl, j.kuper@@utwente.nl}}
% \and
% \IEEEauthorblockN{Homer Simpson}
% \IEEEauthorblockA{Twentieth Century Fox\\
\begin{abstract}
%\boldmath
-The abstract goes here.
+\CLaSH\ is a functional hardware description language that borrows both its
+syntax and semantics from the functional programming language Haskell. Circuit
+descriptions can be translated to synthesizable VHDL using the prototype
+\CLaSH\ compiler. As the circuit descriptions are made in plain Haskell,
+simulations can also be compiled by a Haskell compiler.
+
+The use of polymorphism and higher-order functions allow a circuit designer to
+describe more abstract and general specifications than are possible in the
+traditional hardware description languages.
\end{abstract}
% IEEEtran.cls defaults to using nonbold math in the Abstract.
% This preserves the distinction between vectors and scalars. However,
\section{Introduction}
-Hardware description languages has allowed the productivity of hardware
+Hardware description languages have allowed the productivity of hardware
engineers to keep pace with the development of chip technology. Standard
Hardware description languages, like \VHDL~\cite{VHDL2008} and
Verilog~\cite{Verilog}, allowed an engineer to describe circuits using a
ForSyDe1,Wired,reFLect}. The idea of using functional languages for hardware
descriptions started in the early 1980s \cite{Cardelli1981, muFP,DAISY,FHDL},
a time which also saw the birth of the currently popular hardware description
-languages such as \VHDL. The merit of using a functional language to describe
-hardware comes from the fact that basic combinatorial circuits are equivalent
-to mathematical functions and that functional languages are very good at
+languages such as \VHDL. Functional languages are especially suited to
+describe hardware because combinational circuits can be directly modeled
+as mathematical functions and that functional languages are very good at
describing and composing mathematical functions.
-In an attempt to decrease the amount of work involved with creating all the
-required tooling, such as parsers and type-checkers, many functional hardware
-description languages are embedded as a domain specific language inside the
-functional language Haskell \cite{Hydra,Hawk1,Lava,ForSyDe1,Wired}. This
-means that a developer is given a library of Haskell~\cite{Haskell} functions
-and types that together form the language primitives of the domain specific
-language. As a result of how the signals are modeled and abstracted, the
-functions used to describe a circuit also build a large domain-specific
-datatype (hidden from the designer) which can be further processed by an
-embedded compiler. This compiler actually runs in the same environment as the
-description; as a result compile-time and run-time become hard to define, as
-the embedded compiler is usually compiled by the same Haskell compiler as the
-circuit description itself.
+In an attempt to decrease the amount of work involved in creating all the
+required tooling, such as parsers and type-checkers, many functional
+hardware description languages \cite{Hydra,Hawk1,Lava,ForSyDe1,Wired}
+are embedded as a domain specific language inside the functional
+language Haskell \cite{Haskell}. This means that a developer is given a
+library of Haskell functions and types that together form the language
+primitives of the domain specific language. The primitive functions used
+to describe a circuit do not actually process any signals, but instead
+compose a large domain-specific datatype (which is usually hidden from
+the designer). This datatype is then further processed by an embedded
+circuit compiler. This circuit compiler actually runs in the same
+environment as the description; as a result compile-time and run-time
+become hard to define, as the embedded circuit compiler is usually
+compiled by the same Haskell compiler as the circuit description itself.
The approach taken in this research is not to make another domain specific
language embedded in Haskell, but to use (a subset of) the Haskell language
itself for the purpose of describing hardware. By taking this approach, we can
capture certain language constructs, such as Haskell's choice elements
-(if-constructs, case-constructs, pattern matching, etc.), which are not
+(if-expressions, case-expressions, pattern matching, etc.), which are not
available in the functional hardware description languages that are embedded
-in Haskell as a domain specific languages. As far as the authors know, such
+in Haskell as a domain specific language. As far as the authors know, such
extensive support for choice-elements is new in the domain of functional
-hardware description language. As the hardware descriptions are plain Haskell
-functions, these descriptions can be compiled for simulation using using the
-optimizing Haskell compiler \GHC.
+hardware description languages. As the hardware descriptions are plain Haskell
+functions, these descriptions can be compiled to an executable binary
+for simulation using an optimizing Haskell compiler such as the Glasgow
+Haskell Compiler (\GHC)~\cite{ghc}.
Where descriptions in a conventional hardware description language have an
explicit clock for the purpose state and synchronicity, the clock is implied
-in this research. The functions describe the behavior of the hardware between
-clock cycles, as such, only synchronous systems can be described. Many
-functional hardware description models signals as a stream of all values over
-time; state is then modeled as a delay on this stream of values. The approach
-taken in this research is to make the current state of a circuit part of the
-input of the function and the updated state part of the output.
+in this research. A developer describes the behavior of the hardware between
+clock cycles. Many functional hardware description model signals as a stream
+of all values over time; state is then modeled as a delay on this stream of
+values. The approach taken in this research is to make the current state of a
+circuit part of the input of the function and the updated state part of the
+output. The current abstraction of state and time limits the descriptions to
+synchronous hardware, there however is room within the language to eventually
+add a different abstraction mechanism that will allow for the modeling of
+asynchronous systems.
Like the standard hardware description languages, descriptions made in a
functional hardware description language must eventually be converted into a
-netlist. This research also features a prototype translator called \CLaSH\
-(pronounced: clash), which converts the Haskell code to equivalently behaving
-synthesizable \VHDL\ code, ready to be converted to an actual netlist format
-by an optimizing \VHDL\ synthesis tools.
+netlist. This research also features a prototype translator, which has the
+same name as the language: \CLaSH\footnote{\CLaSHtiny: \acrotiny{CAES}
+Language for Synchronous Hardware} (pronounced: clash). This compiler converts
+the Haskell code to equivalently behaving synthesizable \VHDL\ code, ready to
+be converted to an actual netlist format by an (optimizing) \VHDL\ synthesis
+tool.
+
+Besides trivial circuits such as variants of both the \acro{FIR} filter and
+the simple \acro{CPU} shown in \Cref{sec:usecases}, the \CLaSH\ compiler has
+also been shown to work for non-trivial descriptions. \CLaSH\ has been able to
+successfully translate the functional description of a streaming reduction
+circuit~\cite{reductioncircuit} for floating point numbers.
\section{Hardware description in Haskell}
\subsection{Function application}
The basic syntactic elements of a functional program are functions
- and function application. These have a single obvious \VHDL\
- translation: each top level function becomes a hardware component,
- where each argument is an input port and the result value is the
- (single) output port. This output port can have a complex type (such
- as a tuple), so having just a single output port does not create a
- limitation.
-
- Each function application in turn becomes a component instantiation.
- Here, the result of each argument expression is assigned to a
- signal, which is mapped to the corresponding input port. The output
- port of the function is also mapped to a signal, which is used as
- the result of the application itself.
+ and function application. These have a single obvious translation to a
+ netlist format:
+ \begin{inparaenum}
+ \item every function is translated to a component,
+ \item every function argument is translated to an input port,
+ \item the result value of a function is translated to an output port,
+ and
+ \item function applications are translated to component instantiations.
+ \end{inparaenum}
+ The output port can have a structured type (such as a tuple), so having
+ just a single output port does not pose any limitation. The actual
+ arguments of a function application are assigned to signals, which are
+ then mapped to the corresponding input ports of the component. The output
+ port of the function is also mapped to a signal, which is used as the
+ result of the application itself.
Since every top level function generates its own component, the
- hierarchy of function calls is reflected in the final \VHDL\
- output as well, creating a hierarchical \VHDL\ description of the
- hardware. This separation in different components makes the
- resulting \VHDL\ output easier to read and debug.
-
- Example that defines the \texttt{mac} function by applying the
- \texttt{add} and \texttt{mul} functions to calculate $a * b + c$:
-
-\begin{code}
-mac a b c = add (mul a b) c
-\end{code}
-
-\begin{figure}
-\centerline{\includegraphics{mac}}
-\caption{Combinatorial Multiply-Accumulate (curried)}
-\label{img:mac-comb}
-\end{figure}
+ hierarchy of function calls is reflected in the final netlist,% aswell,
+ creating a hierarchical description of the hardware. The separation in
+ different components makes it easier for a developer to understand and
+ possibly hand-optimize the resulting \VHDL\ output of the \CLaSH\
+ compiler.
+
+ As an example we can see the netlist of the |mac| function in
+ \Cref{img:mac-comb}; the |mac| function applies both the |mul| and |add|
+ function to calculate $a * b + c$:
+
+ \begin{code}
+ mac a b c = add (mul a b) c
+ \end{code}
+
+ \begin{figure}
+ \centerline{\includegraphics{mac.svg}}
+ \caption{Combinatorial Multiply-Accumulate}
+ \label{img:mac-comb}
+ \end{figure}
+
+ The result of using a structural input type can be seen in
+ \cref{img:mac-comb-nocurry} where the |mac| function now uses a single
+ input tuple for the |a|, |b|, and |c| arguments:
+
+ \begin{code}
+ mac (a, b, c) = add (mul a b) c
+ \end{code}
+
+ \begin{figure}
+ \centerline{\includegraphics{mac-nocurry.svg}}
+ \caption{Combinatorial Multiply-Accumulate (complex input)}
+ \label{img:mac-comb-nocurry}
+ \end{figure}
+
+ \subsection{Choice}
+ In Haskell, choice can be achieved by a large set of syntactic elements,
+ consisting of: \hs{case} expressions, \hs{if-then-else} expressions,
+ pattern matching, and guards. The most general of these are the \hs{case}
+ expressions (\hs{if} expressions can be very directly translated to
+ \hs{case} expressions). A \hs{case} expression is translated to a
+ multiplexer, where the control value is fed into a number of
+ comparators and their output is used to compose the selection port
+ of the multiplexer. The result of each alternative is linked to the
+ corresponding input port on the multiplexer.
+ % A \hs{case} expression can in turn simply be translated to a conditional
+ % assignment in \VHDL, where the conditions use equality comparisons
+ % against the constructors in the \hs{case} expressions.
+ We can see two versions of a contrived example below, the first
+ using a \hs{case} expression and the other using an \hs{if-then-else}
+ expression. Both examples sums two values when they are
+ equal or non-equal (depending on the given predicate, the \hs{pred}
+ variable) and returns 0 otherwise. The \hs{pred} variable has the
+ following, user-defined, enumeration datatype:
+
+ \begin{code}
+ data Pred = Equal | NotEqual
+ \end{code}
-\begin{figure}
-\centerline{\includegraphics{mac-nocurry}}
-\caption{Combinatorial Multiply-Accumulate (uncurried)}
-\label{img:mac-comb-nocurry}
-\end{figure}
+ The naive netlist corresponding to both versions of the example is
+ depicted in \Cref{img:choice}.
- \subsection{Choices}
- Although describing components and connections allows describing a
- lot of hardware designs already, there is an obvious thing missing:
- choice. We need some way to be able to choose between values based
- on another value. In Haskell, choice is achieved by \hs{case}
- expressions, \hs{if} expressions, pattern matching and guards.
-
- The easiest of these are of course case expressions (and \hs{if}
- expressions, which can be very directly translated to \hs{case}
- expressions). A \hs{case} expression can in turn simply be
- translated to a conditional assignment in \VHDL, where the
- conditions use equality comparisons against the constructors in the
- \hs{case} expressions.
-
- A slightly more complex (but very powerful) form of choice is
- pattern matching. A function can be defined in multiple clauses,
- where each clause specifies a pattern. When the arguments match the
- pattern, the corresponding clause will be used.
-
- A pattern match (with optional guards) can also be implemented using
- conditional assignments in \VHDL, where the condition is the logical
- and of comparison results of each part of the pattern as well as the
- guard.
-
- Contrived example that sums two values when they are equal or
- non-equal (depending on the predicate given) and returns 0
- otherwise. This shows three implementations, one using and if
- expression, one using only case expressions and one using pattern
- matching and guards.
+ \begin{code}
+ sumif pred a b = case pred of
+ Equal -> case a == b of
+ True -> a + b
+ False -> 0
+ NotEqual -> case a != b of
+ True -> a + b
+ False -> 0
+ \end{code}
\begin{code}
- sumif pred a b = if pred == Eq && a == b ||
- pred == Neq && a != b
- then a + b
- else 0
+ sumif pred a b =
+ if pred == Equal then
+ if a == b then a + b else 0
+ else
+ if a != b then a + b else 0
+ \end{code}
- sumif pred a b = case pred of
- Eq -> case a == b of
- True -> a + b
- False -> 0
- Neq -> case a != b of
- True -> a + b
- False -> 0
-
- sumif Eq a b | a == b = a + b
- sumif Neq a b | a != b = a + b
- sumif _ _ _ = 0
+ \begin{figure}
+ \centerline{\includegraphics{choice-case.svg}}
+ \caption{Choice - sumif}
+ \label{img:choice}
+ \end{figure}
+
+ A user-friendly and also very powerful form of choice is pattern
+ matching. A function can be defined in multiple clauses, where each clause
+ corresponds to a pattern. When an argument matches a pattern, the
+ corresponding clause will be used. Expressions can also contain guards,
+ where the expression is only executed if the guard evaluates to true, and
+ continues with the next clause if the guard evaluates to false. Like
+ \hs{if-then-else} expressions, pattern matching and guards have a
+ (straightforward) translation to \hs{case} expressions and can as such be
+ mapped to multiplexers. A third version of the earlier example, using both
+ pattern matching and guards, can be seen below. The guard is the
+ expression that follows the vertical bar (\hs{|}) and precedes the
+ assignment operator (\hs{=}). The \hs{otherwise} guards always evaluate to
+ \hs{true}.
+
+ The version using pattern matching and guards corresponds to the same
+ naive netlist representation (\Cref{img:choice}) as the earlier two
+ versions of the example.
+
+ \begin{code}
+ sumif Equal a b | a == b = a + b
+ | otherwise = 0
+ sumif NotEqual a b | a != b = a + b
+ | otherwise = 0
\end{code}
- \comment{TODO: Pretty picture}
+ % \begin{figure}
+ % \centerline{\includegraphics{choice-ifthenelse}}
+ % \caption{Choice - \emph{if-then-else}}
+ % \label{img:choice}
+ % \end{figure}
\subsection{Types}
- Translation of two most basic functional concepts has been
- discussed: function application and choice. Before looking further
- into less obvious concepts like higher-order expressions and
- polymorphism, the possible types that can be used in hardware
- descriptions will be discussed.
-
- Some way is needed to translate every value used to its hardware
- equivalents. In particular, this means a hardware equivalent for
- every \emph{type} used in a hardware description is needed.
-
- The following types are \emph{built-in}, meaning that their hardware
- translation is fixed into the \CLaSH\ compiler. A designer can also
- define his own types, which will be translated into hardware types
- using translation rules that are discussed later on.
-
- \subsection{Built-in types}
+ Haskell is a statically-typed language, meaning that the type of a
+ variable or function is determined at compile-time. Not all of Haskell's
+ typing constructs have a clear translation to hardware, this section will
+ therefore only deal with the types that do have a clear correspondence
+ to hardware. The translatable types are divided into two categories:
+ \emph{built-in} types and \emph{user-defined} types. Built-in types are
+ those types for which a fixed translation is defined within the \CLaSH\
+ compiler. The \CLaSH\ compiler has generic translation rules to
+ translated the user-defined types described below.
+
+ The \CLaSH\ compiler is able to infer unspecified types,
+ meaning that a developer does not have to annotate every function with a
+ type signature (even if it is good practice to do so).
+
+ % Translation of two most basic functional concepts has been
+ % discussed: function application and choice. Before looking further
+ % into less obvious concepts like higher-order expressions and
+ % polymorphism, the possible types that can be used in hardware
+ % descriptions will be discussed.
+ %
+ % Some way is needed to translate every value used to its hardware
+ % equivalents. In particular, this means a hardware equivalent for
+ % every \emph{type} used in a hardware description is needed.
+ %
+ % The following types are \emph{built-in}, meaning that their hardware
+ % translation is fixed into the \CLaSH\ compiler. A designer can also
+ % define his own types, which will be translated into hardware types
+ % using translation rules that are discussed later on.
+
+ \subsubsection{Built-in types}
+ The following types have fixed translations defined within the \CLaSH\
+ compiler:
\begin{xlist}
- \item[\hs{Bit}]
- This is the most basic type available. It can have two values:
- \hs{Low} and \hs{High}. It is mapped directly onto the
- \texttt{std\_logic} \VHDL\ type.
- \item[\hs{Bool}]
- This is a basic logic type. It can have two values: \hs{True}
- and \hs{False}. It is translated to \texttt{std\_logic} exactly
- like the \hs{Bit} type (where a value of \hs{True} corresponds
- to a value of \hs{High}). Supporting the Bool type is
- particularly useful to support \hs{if ... then ... else ...}
- expressions, which always have a \hs{Bool} value for the
- condition.
- \item[\hs{SizedWord}, \hs{SizedInt}]
- These are types to represent integers. A \hs{SizedWord} is unsigned,
- while a \hs{SizedInt} is signed. These types are parametrized by a
- length type, so you can define an unsigned word of 32 bits wide as
- follows:
-
- \begin{code}
- type Word32 = SizedWord D32
- \end{code}
-
- Here, a type synonym \hs{Word32} is defined that is equal to the
- \hs{SizedWord} type constructor applied to the type \hs{D32}. \hs{D32}
- is the \emph{type level representation} of the decimal number 32,
- making the \hs{Word32} type a 32-bit unsigned word. These types are
- translated to the \VHDL\ \texttt{unsigned} and \texttt{signed}
- respectively.
- \item[\hs{Vector}]
- This is a vector type, that can contain elements of any other type and
+ \item[\bf{Bit}]
+ the most basic type available. It can have two values:
+ \hs{Low} or \hs{High}.
+ % It is mapped directly onto the \texttt{std\_logic} \VHDL\ type.
+ \item[\bf{Bool}]
+ this is a basic logic type. It can have two values: \hs{True}
+ or \hs{False}.
+ % It is translated to \texttt{std\_logic} exactly like the \hs{Bit}
+ % type (where a value of \hs{True} corresponds to a value of
+ % \hs{High}).
+ Supporting the Bool type is required in order to support the
+ \hs{if-then-else} expression, which requires a \hs{Bool} value for
+ the condition.
+ \item[\bf{SizedWord}, \bf{SizedInt}]
+ these are types to represent integers. A \hs{SizedWord} is unsigned,
+ while a \hs{SizedInt} is signed. Both are parametrizable in their
+ size.
+ % , so you can define an unsigned word of 32 bits wide as follows:
+
+ % \begin{code}
+ % type Word32 = SizedWord D32
+ % \end{code}
+
+ % Here, a type synonym \hs{Word32} is defined that is equal to the
+ % \hs{SizedWord} type constructor applied to the type \hs{D32}.
+ % \hs{D32} is the \emph{type level representation} of the decimal
+ % number 32, making the \hs{Word32} type a 32-bit unsigned word. These
+ % types are translated to the \VHDL\ \texttt{unsigned} and
+ % \texttt{signed} respectively.
+ \item[\bf{Vector}]
+ this is a vector type that can contain elements of any other type and
has a fixed length. The \hs{Vector} type constructor takes two type
arguments: the length of the vector and the type of the elements
- contained in it. The state type of an 8 element register bank would
- then for example be:
-
- \begin{code}
- type RegisterState = Vector D8 Word32
- \end{code}
-
- Here, a type synonym \hs{RegisterState} is defined that is equal to
- the \hs{Vector} type constructor applied to the types \hs{D8} (The
- type level representation of the decimal number 8) and \hs{Word32}
- (The 32 bit word type as defined above). In other words, the
- \hs{RegisterState} type is a vector of 8 32-bit words. A fixed size
- vector is translated to a \VHDL\ array type.
- \item[\hs{RangedWord}]
- This is another type to describe integers, but unlike the previous
+ contained in it. The short-hand notation used for the vector type in
+ the rest of paper is: \hs{[a|n]}. Where the \hs{a} is the element
+ type, and \hs{n} is the length of the vector. Note that this is
+ a notation used in this paper only, vectors are slightly more
+ verbose in real \CLaSH\ descriptions.
+ % The state type of an 8 element register bank would then for example
+ % be:
+
+ % \begin{code}
+ % type RegisterState = Vector D8 Word32
+ % \end{code}
+
+ % Here, a type synonym \hs{RegisterState} is defined that is equal to
+ % the \hs{Vector} type constructor applied to the types \hs{D8} (The
+ % type level representation of the decimal number 8) and \hs{Word32}
+ % (The 32 bit word type as defined above). In other words, the
+ % \hs{RegisterState} type is a vector of 8 32-bit words. A fixed size
+ % vector is translated to a \VHDL\ array type.
+ \item[\bf{Index}]
+ this is another type to describe integers, but unlike the previous
two it has no specific bit-width, but an upper bound. This means that
its range is not limited to powers of two, but can be any number.
- A \hs{RangedWord} only has an upper bound, its lower bound is
- implicitly zero. The main purpose of the \hs{RangedWord} type is to be
+ An \hs{Index} only has an upper bound, its lower bound is
+ implicitly zero. The main purpose of the \hs{Index} type is to be
used as an index to a \hs{Vector}.
- \comment{TODO: Perhaps remove this example?} To define an index for
- the 8 element vector above, we would do:
+ % \comment{TODO: Perhaps remove this example?} To define an index for
+ % the 8 element vector above, we would do:
- \begin{code}
- type RegisterIndex = RangedWord D7
- \end{code}
+ % \begin{code}
+ % type RegisterIndex = RangedWord D7
+ % \end{code}
- Here, a type synonym \hs{RegisterIndex} is defined that is equal to
- the \hs{RangedWord} type constructor applied to the type \hs{D7}. In
- other words, this defines an unsigned word with values from
- 0 to 7 (inclusive). This word can be be used to index the
- 8 element vector \hs{RegisterState} above. This type is translated to
- the \texttt{unsigned} \VHDL type.
+ % Here, a type synonym \hs{RegisterIndex} is defined that is equal to
+ % the \hs{RangedWord} type constructor applied to the type \hs{D7}. In
+ % other words, this defines an unsigned word with values from
+ % 0 to 7 (inclusive). This word can be be used to index the
+ % 8 element vector \hs{RegisterState} above. This type is translated
+ % to the \texttt{unsigned} \VHDL type.
\end{xlist}
- \subsection{User-defined types}
+ \subsubsection{User-defined types}
There are three ways to define new types in Haskell: algebraic
data-types with the \hs{data} keyword, type synonyms with the \hs{type}
- keyword and type renamings with the \hs{newtype} keyword. \GHC\
- offers a few more advanced ways to introduce types (type families,
- existential typing, {\small{GADT}}s, etc.) which are not standard
- Haskell. These are not currently supported.
+ keyword and datatype renaming constructs with the \hs{newtype} keyword.
+ \GHC\ offers a few more advanced ways to introduce types (type families,
+ existential typing, {\acro{GADT}}s, etc.) which are not standard Haskell.
+ As it is currently unclear how these advanced type constructs correspond
+ to hardware, they are for now unsupported by the \CLaSH\ compiler.
Only an algebraic datatype declaration actually introduces a
- completely new type, for which we provide the \VHDL\ translation
- below. Type synonyms and renamings only define new names for
- existing types (where synonyms are completely interchangeable and
- renamings need explicit conversion). Therefore, these do not need
- any particular \VHDL\ translation, a synonym or renamed type will
- just use the same representation as the original type. The
- distinction between a renaming and a synonym does no longer matter
- in hardware and can be disregarded in the generated \VHDL.
-
- For algebraic types, we can make the following distinction:
+ completely new type. Type synonyms and type renaming only define new
+ names for existing types, where synonyms are completely interchangeable
+ and type renaming requires explicit conversions. Therefore, these do not
+ need any particular translation, a synonym or renamed type will just use
+ the same representation as the original type. For algebraic types, we can
+ make the following distinctions:
\begin{xlist}
\item[\bf{Single constructor}]
Algebraic datatypes with a single constructor with one or more
fields, are essentially a way to pack a few values together in a
- record-like structure. An example of such a type is the following pair
- of integers:
-
-\begin{code}
-data IntPair = IntPair Int Int
-\end{code}
-
- Haskell's builtin tuple types are also defined as single
- constructor algebraic types and are translated according to this
- rule by the \CLaSH\ compiler. These types are translated to \VHDL\
- record types, with one field for every field in the constructor.
+ record-like structure. Haskell's built-in tuple types are also defined
+ as single constructor algebraic types (but with a bit of
+ syntactic sugar). An example of a single constructor type is the
+ following pair of integers:
+ \begin{code}
+ data IntPair = IntPair Int Int
+ \end{code}
+ % These types are translated to \VHDL\ record types, with one field
+ % for every field in the constructor.
\item[\bf{No fields}]
Algebraic datatypes with multiple constructors, but without any
fields are essentially a way to get an enumeration-like type
containing alternatives. Note that Haskell's \hs{Bool} type is also
- defined as an enumeration type, but we have a fixed translation for
- that. These types are translated to \VHDL\ enumerations, with one
- value for each constructor. This allows references to these
- constructors to be translated to the corresponding enumeration value.
+ defined as an enumeration type, but that there is a fixed translation
+ for that type within the \CLaSH\ compiler. An example of such an
+ enumeration type is the type that represents the colors in a traffic
+ light:
+ \begin{code}
+ data TrafficLight = Red | Orange | Green
+ \end{code}
+ % These types are translated to \VHDL\ enumerations, with one
+ % value for each constructor. This allows references to these
+ % constructors to be translated to the corresponding enumeration
+ % value.
\item[\bf{Multiple constructors with fields}]
Algebraic datatypes with multiple constructors, where at least
- one of these constructors has one or more fields are not
- currently supported.
+ one of these constructors has one or more fields are currently not
+ supported.
\end{xlist}
- \subsection{Polymorphic functions}
- A powerful construct in most functional language is polymorphism.
- This means the arguments of a function (and consequentially, values
- within the function as well) do not need to have a fixed type.
- Haskell supports \emph{parametric polymorphism}, meaning a
- function's type can be parameterized with another type.
-
- As an example of a polymorphic function, consider the following
- \hs{append} function's type:
+ \subsection{Polymorphism}
+ A powerful feature of most (functional) programming languages is
+ polymorphism, it allows a function to handle values of different data
+ types in a uniform way. Haskell supports \emph{parametric
+ polymorphism}~\cite{polymorphism}, meaning functions can be written
+ without mention of any specific type and can be used transparently with
+ any number of new types.
+
+ As an example of a parametric polymorphic function, consider the type of
+ the following \hs{append} function, which appends an element to a
+ vector:\footnote{The \hs{::} operator is used to annotate a function
+ with its type.}
- TODO: Use vectors instead of lists?
-
\begin{code}
- append :: [a] -> a -> [a]
+ append :: [a|n] -> a -> [a|n + 1]
\end{code}
This type is parameterized by \hs{a}, which can contain any type at
- all. This means that append can append an element to a list,
- regardless of the type of the elements in the list (but the element
- added must match the elements in the list, since there is only one
- \hs{a}).
-
- This kind of polymorphism is extremely useful in hardware designs to
- make operations work on a vector without knowing exactly what elements
- are inside, routing signals without knowing exactly what kinds of
- signals these are, or working with a vector without knowing exactly
- how long it is. Polymorphism also plays an important role in most
- higher order functions, as we will see in the next section.
-
- The previous example showed unconstrained polymorphism (TODO: How is
- this really called?): \hs{a} can have \emph{any} type. Furthermore,
- Haskell supports limiting the types of a type parameter to specific
- class of types. An example of such a type class is the \hs{Num}
- class, which contains all of Haskell's numerical types.
-
- Now, take the addition operator, which has the following type:
-
+ all. This means that \hs{append} can append an element to a vector,
+ regardless of the type of the elements in the list (as long as the type of
+ the value to be added is of the same type as the values in the vector).
+ This kind of polymorphism is extremely useful in hardware designs to make
+ operations work on a vector without knowing exactly what elements are
+ inside, routing signals without knowing exactly what kinds of signals
+ these are, or working with a vector without knowing exactly how long it
+ is. Polymorphism also plays an important role in most higher order
+ functions, as we will see in the next section.
+
+ Another type of polymorphism is \emph{ad-hoc
+ polymorphism}~\cite{polymorphism}, which refers to polymorphic
+ functions which can be applied to arguments of different types, but which
+ behave differently depending on the type of the argument to which they are
+ applied. In Haskell, ad-hoc polymorphism is achieved through the use of
+ type classes, where a class definition provides the general interface of a
+ function, and class instances define the functionality for the specific
+ types. An example of such a type class is the \hs{Num} class, which
+ contains all of Haskell's numerical operations. A designer can make use
+ of this ad-hoc polymorphism by adding a constraint to a parametrically
+ polymorphic type variable. Such a constraint indicates that the type
+ variable can only be instantiated to a type whose members supports the
+ overloaded functions associated with the type class.
+
+ As an example we will take a look at type signature of the function
+ \hs{sum}, which sums the values in a vector:
\begin{code}
- (+) :: Num a => a -> a -> a
+ sum :: Num a => [a|n] -> a
\end{code}
This type is again parameterized by \hs{a}, but it can only contain
- types that are \emph{instances} of the \emph{type class} \hs{Num}.
- Our numerical built-in types are also instances of the \hs{Num}
- class, so we can use the addition operator on \hs{SizedWords} as
- well as on {SizedInts}.
-
- In \CLaSH, unconstrained polymorphism is completely supported. Any
- function defined can have any number of unconstrained type
- parameters. The \CLaSH compiler will infer the type of every such
- argument depending on how the function is applied. There is one
- exception to this: The top level function that is translated, can
- not have any polymorphic arguments (since it is never applied, so
- there is no way to find out the actual types for the type
- parameters).
-
- \CLaSH does not support user-defined type classes, but does use some
- of the builtin ones for its builtin functions (like \hs{Num} and
- \hs{Eq}).
-
- \subsection{Higher order}
+ types that are \emph{instances} of the \emph{type class} \hs{Num}, so that
+ we know that the addition (+) operator is defined for that type.
+ \CLaSH's built-in numerical types are also instances of the \hs{Num}
+ class, so we can use the addition operator (and thus the \hs{sum}
+ function) with \hs{SizedWords} as well as with \hs{SizedInts}.
+
+ In \CLaSH, parametric polymorphism is completely supported. Any function
+ defined can have any number of unconstrained type parameters. The \CLaSH\
+ compiler will infer the type of every such argument depending on how the
+ function is applied. There is however one constraint: the top level
+ function that is being translated can not have any polymorphic arguments.
+ The arguments can not be polymorphic as the function is never applied and
+ consequently there is no way to determine the actual types for the type
+ parameters.
+
+ \CLaSH\ does not support user-defined type classes, but does use some
+ of the standard Haskell type classes for its built-in function, such as:
+ \hs{Num} for numerical operations, \hs{Eq} for the equality operators, and
+ \hs{Ord} for the comparison/order operators.
+
+ \subsection{Higher-order functions \& values}
Another powerful abstraction mechanism in functional languages, is
- the concept of \emph{higher order functions}, or \emph{functions as
+ the concept of \emph{higher-order functions}, or \emph{functions as
a first class value}. This allows a function to be treated as a
value and be passed around, even as the argument of another
- function. Let's clarify that with an example:
+ function. The following example should clarify this concept:
\begin{code}
- notList xs = map not xs
- \end{code}
-
- This defines a function \hs{notList}, with a single list of booleans
- \hs{xs} as an argument, which simply negates all of the booleans in
- the list. To do this, it uses the function \hs{map}, which takes
- \emph{another function} as its first argument and applies that other
- function to each element in the list, returning again a list of the
- results.
-
- As you can see, the \hs{map} function is a higher order function,
- since it takes another function as an argument. Also note that
- \hs{map} is again a polymorphic function: It does not pose any
- constraints on the type of elements in the list passed, other than
- that it must be the same as the type of the argument the passed
- function accepts. The type of elements in the resulting list is of
- course equal to the return type of the function passed (which need
- not be the same as the type of elements in the input list). Both of
- these can be readily seen from the type of \hs{map}:
-
- \begin{code}
- map :: (a -> b) -> [a] -> [b]
+ negateVector xs = map not xs
\end{code}
-
- As an example from a common hardware design, let's look at the
- equation of a FIR filter.
-
- \begin{equation}
- y_t = \sum\nolimits_{i = 0}^{n - 1} {x_{t - i} \cdot h_i }
- \end{equation}
- A FIR filter multiplies fixed constants ($h$) with the current and
- a few previous input samples ($x$). Each of these multiplications
- are summed, to produce the result at time $t$.
-
- This is easily and directly implemented using higher order
- functions. Consider that the vector \hs{hs} contains the FIR
- coefficients and the vector \hs{xs} contains the current input sample
- in front and older samples behind. How \hs{xs} gets its value will be
- show in the next section about state.
+ The code above defines the \hs{negateVector} function, which takes a
+ vector of booleans, \hs{xs}, and returns a vector where all the values are
+ negated. It achieves this by calling the \hs{map} function, and passing it
+ \emph{another function}, boolean negation, and the vector of booleans,
+ \hs{xs}. The \hs{map} function applies the negation function to all the
+ elements in the vector.
+
+ The \hs{map} function is called a higher-order function, since it takes
+ another function as an argument. Also note that \hs{map} is again a
+ parametric polymorphic function: it does not pose any constraints on the
+ type of the input vector, other than that its elements must have the same
+ type as the first argument of the function passed to \hs{map}. The element
+ type of the resulting vector is equal to the return type of the function
+ passed, which need not necessarily be the same as the element type of the
+ input vector. All of these characteristics can readily be inferred from
+ the type signature belonging to \hs{map}:
\begin{code}
- fir ... = foldl1 (+) (zipwith (*) xs hs)
+ map :: (a -> b) -> [a|n] -> [b|n]
\end{code}
- Here, the \hs{zipwith} function is very similar to the \hs{map}
- function: It takes a function two lists and then applies the
- function to each of the elements of the two lists pairwise
- (\emph{e.g.}, \hs{zipwith (+) [1, 2] [3, 4]} becomes
- \hs{[1 + 3, 2 + 4]}.
-
- The \hs{foldl1} function takes a function and a single list and applies the
- function to the first two elements of the list. It then applies to
- function to the result of the first application and the next element
- from the list. This continues until the end of the list is reached.
- The result of the \hs{foldl1} function is the result of the last
- application.
-
- As you can see, the \hs{zipwith (*)} function is just pairwise
- multiplication and the \hs{foldl1 (+)} function is just summation.
-
- To make the correspondence between the code and the equation even
- more obvious, we turn the list of input samples in the equation
- around. So, instead of having the the input sample received at time
- $t$ in $x_t$, $x_0$ now always stores the current sample, and $x_i$
- stores the $ith$ previous sample. This changes the equation to the
- following (Note that this is completely equivalent to the original
- equation, just with a different definition of $x$ that better suits
- the \hs{x} from the code):
-
- \begin{equation}
- y_t = \sum\nolimits_{i = 0}^{n - 1} {x_i \cdot h_i }
- \end{equation}
-
- So far, only functions have been used as higher order values. In
+ So far, only functions have been used as higher-order values. In
Haskell, there are two more ways to obtain a function-typed value:
partial application and lambda abstraction. Partial application
means that a function that takes multiple arguments can be applied
expression, that adds one to every element of a vector:
\begin{code}
- map ((+) 1) xs
+ map (+ 1) xs
\end{code}
- Here, the expression \hs{(+) 1} is the partial application of the
+ Here, the expression \hs{(+ 1)} is the partial application of the
plus operator to the value \hs{1}, which is again a function that
- adds one to its argument.
-
- A labmda expression allows one to introduce an anonymous function
- in any expression. Consider the following expression, which again
- adds one to every element of a list:
+ adds one to its (next) argument. A lambda expression allows one to
+ introduce an anonymous function in any expression. Consider the following
+ expression, which again adds one to every element of a vector:
\begin{code}
map (\x -> x + 1) xs
\end{code}
- Finally, higher order arguments are not limited to just builtin
- functions, but any function defined in \CLaSH can have function
+ Finally, not only built-in functions can have higher order
+ arguments, but any function defined in \CLaSH can have function
arguments. This allows the hardware designer to use a powerful
abstraction mechanism in his designs and have an optimal amount of
- code reuse.
+ code reuse. The only exception is again the top-level function: if a
+ function-typed argument is not applied with an actual function, no
+ hardware can be generated.
- TODO: Describe ALU example (no code)
+ % \comment{TODO: Describe ALU example (no code)}
\subsection{State}
- A very important concept in hardware it the concept of state. In a
+ A very important concept in hardware is the concept of state. In a
stateful design, the outputs depend on the history of the inputs, or the
state. State is usually stored in registers, which retain their value
during a clock cycle. As we want to describe more than simple
- combinatorial designs, \CLaSH\ needs an abstraction mechanism for state.
+ combinational designs, \CLaSH\ needs an abstraction mechanism for state.
An important property in Haskell, and in most other functional languages,
is \emph{purity}. A function is said to be \emph{pure} if it satisfies two
\item when the function is called, it should not have observable
side-effects.
\end{inparaenum}
- This purity property is important for functional languages, since it
- enables all kinds of mathematical reasoning that could not be guaranteed
- correct for impure functions. Pure functions are as such a perfect match
- for a combinatorial circuit, where the output solely depends on the
- inputs. When a circuit has state however, it can no longer be simply
- described by a pure function. Simply removing the purity property is not a
- valid option, as the language would then lose many of it mathematical
- properties. In an effort to include the concept of state in pure
- functions, the current value of the state is made an argument of the
- function; the updated state becomes part of the result.
+ % This purity property is important for functional languages, since it
+ % enables all kinds of mathematical reasoning that could not be guaranteed
+ % correct for impure functions.
+ Pure functions are as such a perfect match for combinational circuits,
+ where the output solely depends on the inputs. When a circuit has state
+ however, it can no longer be simply described by a pure function.
+ % Simply removing the purity property is not a valid option, as the
+ % language would then lose many of it mathematical properties.
+ In \CLaSH\ we deal with the concept of state in pure functions by making
+ current value of the state an additional argument of the function and the
+ updated state part of result. In this sense the descriptions made in
+ \CLaSH\ are the combinational parts of a mealy machine.
+
+ A simple example is adding an accumulator register to the earlier
+ multiply-accumulate circuit, of which the resulting netlist can be seen in
+ \Cref{img:mac-state}:
+
+ \begin{code}
+ macS (State c) a b = (State c', c')
+ where
+ c' = mac a b c
+ \end{code}
+
+ \begin{figure}
+ \centerline{\includegraphics{mac-state.svg}}
+ \caption{Stateful Multiply-Accumulate}
+ \label{img:mac-state}
+ \end{figure}
+
+ The \hs{State} keyword indicates which arguments are part of the current
+ state, and what part of the output is part of the updated state. This
+ aspect will also be reflected in the type signature of the function.
+ Abstracting the state of a circuit in this way makes it very explicit:
+ which variables are part of the state is completely determined by the
+ type signature. This approach to state is well suited to be used in
+ combination with the existing code and language features, such as all the
+ choice elements, as state values are just normal values. We can simulate
+ stateful descriptions using the recursive \hs{run} function:
- A simple example is the description of an accumulator circuit:
\begin{code}
- acc :: Word -> State Word -> (State Word, Word)
- acc inp (State s) = (State s', outp)
+ run f s (i : inps) = o : (run f s' inps)
where
- outp = s + inp
- s' = outp
+ (s', o) = f s i
\end{code}
- This approach makes the state of a function very explicit: which variables
- are part of the state is completely determined by the type signature. This
- approach to state is well suited to be used in combination with the
- existing code and language features, such as all the choice constructs, as
- state values are just normal values.
-\section{\CLaSH\ prototype}
+
+ The \hs{(:)} operator is the list concatenation operator, where the
+ left-hand side is the head of a list and the right-hand side is the
+ remainder of the list. The \hs{run} function applies the function the
+ developer wants to simulate, \hs{f}, to the current state, \hs{s}, and the
+ first input value, \hs{i}. The result is the first output value, \hs{o},
+ and the updated state \hs{s'}. The next iteration of the \hs{run} function
+ is then called with the updated state, \hs{s'}, and the rest of the
+ inputs, \hs{inps}. It is assumed that there is one input per clock cycle.
+ Also note how the order of the input, output, and state in the \hs{run}
+ function corresponds with the order of the input, output and state of the
+ \hs{macS} function described earlier.
+
+ As both the \hs{run} function, the hardware description, and the test
+ inputs are plain Haskell, the complete simulation can be compiled to an
+ executable binary by an optimizing Haskell compiler, or executed in an
+ Haskell interpreter. Both simulation paths are much faster than first
+ translating the description to \VHDL\ and then running a \VHDL\
+ simulation, where the executable binary has an additional simulation speed
+ bonus in case there is a large set of test inputs.
+
+\section{\CLaSH\ compiler}
+An important aspect in this research is the creation of the prototype
+compiler, which allows us to translate descriptions made in the \CLaSH\
+language as described in the previous section to synthesizable \VHDL, allowing
+a designer to actually run a \CLaSH\ design on an \acro{FPGA}.
+
+The Glasgow Haskell Compiler (\GHC) is an open-source Haskell compiler that
+also provides a high level API to most of its internals. The availability of
+this high-level API obviated the need to design many of the tedious parts of
+the prototype compiler, such as the parser, semantic checker, and especially
+the type-checker. The parser, semantic checker, and type-checker together form
+the front-end of the prototype compiler pipeline, as depicted in
+\Cref{img:compilerpipeline}.
+
+\begin{figure}
+\centerline{\includegraphics{compilerpipeline.svg}}
+\caption{\CLaSHtiny\ compiler pipeline}
+\label{img:compilerpipeline}
+\end{figure}
+
+The output of the \GHC\ front-end is the original Haskell description
+translated to \emph{Core}~\cite{Sulzmann2007}, which is smaller, typed,
+functional language that is relatively easier to process than the larger
+Haskell language. A description in \emph{Core} can still contain properties
+which have no direct translation to hardware, such as polymorphic types and
+function-valued arguments. Such a description needs to be transformed to a
+\emph{normal form}, which only contains properties that have a direct
+translation. The second stage of the compiler, the \emph{normalization} phase,
+exhaustively applies a set of \emph{meaning-preserving} transformations on the
+\emph{Core} description until this description is in a \emph{normal form}.
+This set of transformations includes transformations typically found in
+reduction systems for lambda calculus~\cite{lambdacalculus}, such a
+$\beta$-reduction and $\eta$-expansion, but also includes self-defined
+transformations that are responsible for the reduction of higher-order
+functions to `regular' first-order functions.
+
+The final step in the compiler pipeline is the translation to a \VHDL\
+\emph{netlist}, which is a straightforward process due to resemblance of a
+normalized description and a set of concurrent signal assignments. We call the
+end-product of the \CLaSH\ compiler a \VHDL\ \emph{netlist} as the resulting
+\VHDL\ resembles an actual netlist description and not idiomatic \VHDL.
+
+\section{Use cases}
+\label{sec:usecases}
+\subsection{FIR Filter}
+As an example of a common hardware design where the use of higher-order
+functions leads to a very natural description is a \acro{FIR} filter, which is
+basically the dot-product of two vectors:
+
+\begin{equation}
+y_t = \sum\nolimits_{i = 0}^{n - 1} {x_{t - i} \cdot h_i }
+\end{equation}
+
+A \acro{FIR} filter multiplies fixed constants ($h$) with the current
+and a few previous input samples ($x$). Each of these multiplications
+are summed, to produce the result at time $t$. The equation of a \acro{FIR}
+filter is indeed equivalent to the equation of the dot-product, which is
+shown below:
+
+\begin{equation}
+\mathbf{a}\bullet\mathbf{b} = \sum\nolimits_{i = 0}^{n - 1} {a_i \cdot b_i }
+\end{equation}
+
+We can easily and directly implement the equation for the dot-product
+using higher-order functions:
+
+\begin{code}
+as *+* bs = foldl1 (+) (zipWith (*) as bs)
+\end{code}
-foo\par bar
+The \hs{zipWith} function is very similar to the \hs{map} function seen
+earlier: It takes a function, two vectors, and then applies the function to
+each of the elements in the two vectors pairwise (\emph{e.g.}, \hs{zipWith (*)
+[1, 2] [3, 4]} becomes \hs{[1 * 3, 2 * 4]}).
+
+The \hs{foldl1} function takes a binary function, a single vector, and applies
+the function to the first two elements of the vector. It then applies the
+function to the result of the first application and the next element in the
+vector. This continues until the end of the vector is reached. The result of
+the \hs{foldl1} function is the result of the last application. It is obvious
+that the \hs{zipWith (*)} function is pairwise multiplication and that the
+\hs{foldl1 (+)} function is summation.
+
+Returning to the actual \acro{FIR} filter, we will slightly change the
+equation describing it, so as to make the translation to code more obvious and
+concise. What we do is change the definition of the vector of input samples
+and delay the computation by one sample. Instead of having the input sample
+received at time $t$ stored in $x_t$, $x_0$ now always stores the newest
+sample, and $x_i$ stores the $ith$ previous sample. This changes the equation
+to the following (note that this is completely equivalent to the original
+equation, just with a different definition of $x$ that will better suit the
+transformation to code):
+
+\begin{equation}
+y_t = \sum\nolimits_{i = 0}^{n - 1} {x_i \cdot h_i }
+\end{equation}
+
+The complete definition of the \acro{FIR} filter in code then becomes:
+
+\begin{code}
+fir (State (xs,hs)) x = (State (x >> xs,hs), xs *+* hs)
+\end{code}
+
+Where the vector \hs{hs} contains the \acro{FIR} coefficients and the vector
+\hs{xs} contains the previous input sample in front and older samples behind.
+The code for the shift (\hs{>>}) operator, that adds the new input sample
+(\hs{x}) to the list of previous input samples (\hs{xs}) and removes the
+oldest sample, is shown below:
+
+\begin{code}
+x >> xs = x +> init xs
+\end{code}
+
+The \hs{init} function returns all but the last element of a vector, and the
+concatenate operator (\hs{+>}) adds a new element to the front of a vector.
+The resulting netlist of a 4-taps \acro{FIR} filter, created by specializing
+the vectors of the \acro{FIR} code to a length of 4, is depicted in
+\Cref{img:4tapfir}.
+
+\begin{figure}
+\centerline{\includegraphics{4tapfir.svg}}
+\caption{4-taps \acrotiny{FIR} Filter}
+\label{img:4tapfir}
+\end{figure}
+
+\subsection{Higher order CPU}
+
+\begin{code}
+fu op inputs (addr1, addr2) = regIn
+ where
+ in1 = inputs!addr1
+ in2 = inputs!addr2
+ regIn = op in1 in2
+\end{code}
+
+\begin{code}
+cpu :: Word -> [(Index 6, Index 6) | 4]
+ -> State [Word | 4] -> (State [Word | 4], Word)
+cpu input addrs (State fuss) = (State fuss', out)
+ where
+ fuss' = [ fu const inputs (addrs!0) (fuss!0)
+ , fu (+) inputs (addrs!1) (fuss!1)
+ , fu (-) inputs (addrs!2) (fuss!2)
+ , fu (*) inputs (addrs!3) (fuss!3)
+ ]
+ inputs = 0 +> (1 +> (input +> fuss))
+ out = head fuss
+\end{code}
\section{Related work}
+This section describes the features of existing (functional) hardware
+description languages and highlights the advantages that this research has
+over existing work.
+
Many functional hardware description languages have been developed over the
years. Early work includes such languages as $\mu$\acro{FP}~\cite{muFP}, an
extension of Backus' \acro{FP} language to synchronous streams, designed
particularly for describing and reasoning about regular circuits. The
Ruby~\cite{Ruby} language uses relations, instead of functions, to describe
-circuits, and has a particular focus on layout. \acro{HML}~\cite{HML2} is a
-hardware modeling language based on the strict functional language
-\acro{ML}, and has support for polymorphic types and higher-order functions.
-Published work suggests that there is no direct simulation support for
-\acro{HML}, and that the translation to \VHDL\ is only partial.
+circuits, and has a particular focus on layout.
+
+\acro{HML}~\cite{HML2} is a hardware modeling language based on the strict
+functional language \acro{ML}, and has support for polymorphic types and
+higher-order functions. Published work suggests that there is no direct
+simulation support for \acro{HML}, but that a description in \acro{HML} has to
+be translated to \VHDL\ and that the translated description can then be
+simulated in a \VHDL\ simulator. Also not all of the mentioned language
+features of \acro{HML} could be translated to hardware. The \CLaSH\ compiler
+on the other hand can correctly translate all of the language constructs
+mentioned in this paper to a netlist format.
Like this work, many functional hardware description languages have some sort
of foundation in the functional programming language Haskell.
Hawk~\cite{Hawk1} uses Haskell to describe system-level executable
specifications used to model the behavior of superscalar microprocessors. Hawk
specifications can be simulated, but there seems to be no support for
-automated circuit synthesis. The ForSyDe~\cite{ForSyDe2} system uses Haskell
-to specify abstract system models, which can (manually) be transformed into an
-implementation model using semantic preserving transformations. ForSyDe has
-several simulation and synthesis backends, though synthesis is restricted to
-the synchronous subset of the ForSyDe language.
+automated circuit synthesis.
+
+The ForSyDe~\cite{ForSyDe2} system uses Haskell to specify abstract system
+models, which can (manually) be transformed into an implementation model using
+semantic preserving transformations. A designer can model systems using
+heterogeneous models of computation, which include continuous time,
+synchronous and untimed models of computation. Using so-called domain
+interfaces a designer can simulate electronic systems which have both analog
+as digital parts. ForSyDe has several backends including simulation and
+automated synthesis, though automated synthesis is restricted to the
+synchronous model of computation within ForSyDe. Unlike \CLaSH\ there is no
+support for the automated synthesis of descriptions that contain polymorphism
+or higher-order functions.
Lava~\cite{Lava} is a hardware description language that focuses on the
structural representation of hardware. Besides support for simulation and
generators when viewed from a synthesis viewpoint, in that the language
elements of Haskell, such as choice, can be used to guide the circuit
generation. If a developer wants to insert a choice element inside an actual
-circuit he will have to specify this explicitly as a component. In this
-respect \CLaSH\ differs from Lava, in that all the choice elements, such as
-case-statements and pattern matching, are synthesized to choice elements in the
-eventual circuit. As such, richer control structures can both be specified and
-synthesized in \CLaSH\ compared to any of the languages mentioned in this
-section.
+circuit he will have to explicitly instantiate a multiplexer-like component.
+
+In this respect \CLaSH\ differs from Lava, in that all the choice elements,
+such as case-statements and pattern matching, are synthesized to choice
+elements in the eventual circuit. As such, richer control structures can both
+be specified and synthesized in \CLaSH\ compared to any of the languages
+mentioned in this section.
The merits of polymorphic typing, combined with higher-order functions, are
now also recognized in the `main-stream' hardware description languages,
-exemplified by the new \VHDL-2008 standard~\cite{VHDL2008}. \VHDL-2008 has
-support to specify types as generics, thus allowing a developer to describe
-polymorphic components. Note that those types still require an explicit
-generic map, whereas type-inference and type-specialization are implicit in
-\CLaSH.
+exemplified by the new \VHDL-2008 standard~\cite{VHDL2008}. \VHDL-2008 support
+for generics has been extended to types and subprograms, allowing a developer to describe components with polymorphic ports and function-valued arguments. Note that the types and subprograms still require an explicit generic map, whereas types can be automatically inferred, and function-values can be automatically propagated by the \CLaSH\ compiler. There are also no (generally available) \VHDL\ synthesis tools that currently support the \VHDL-2008 standard, and thus the synthesis of polymorphic types and function-valued arguments.
% Wired~\cite{Wired},, T-Ruby~\cite{T-Ruby}, Hydra~\cite{Hydra}.
%
% use section* for acknowledgement
-\section*{Acknowledgment}
-
-
-The authors would like to thank...
-
-
-
-
+% \section*{Acknowledgment}
+%
+% The authors would like to thank...
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+\bibliography{clash}
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