\begin{code}
sumif pred a b =
- if pred == Eq then
+ if pred == Equiv then
if a == b then a + b else 0
else
if a != b then a + b else 0
versions of the example.
\begin{code}
- sumif Eq a b | a == b = a + b
- | otherwise = 0
- sumif Neq a b | a != b = a + b
- | otherwise = 0
+ sumif Equiv a b | a == b = a + b
+ | otherwise = 0
+ sumif NotEquiv a b | a != b = a + b
+ | otherwise = 0
\end{code}
% \begin{figure}
function. The following example should clarify this concept:
\begin{code}
- negVector xs = map not xs
+ negateVector xs = map not xs
\end{code}
- The code above defines a function \hs{negVector}, which takes a vector of
- booleans, and returns a vector where all the values are negated. It
- achieves this by calling the \hs{map} function, and passing it
+ 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
+ parametric polymorphic function: it does not pose any constraints on the
type of the vector elements, other than that it must be the same type as
the input type 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
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 lambda expression allows one to introduce an
anonymous function in any expression. Consider the following expression,
\end{code}
Finally, higher order arguments are not limited to just built-in
- functions, but any function defined in \CLaSH\ can have function
+ functions, but any function defined by a developer 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.
- \comment{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
% 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 or a combinatorial circuit,
- where the output solely depends on the inputs. When a circuit has state
+ Pure functions are as such a perfect match for combinatorial 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 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. In this sense the
- descriptions made in \CLaSH are the describing the combinatorial parts of
- a mealy machine.
+ 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 combinatorial 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', outp)
+ macS (State c) a b = (State c', c')
where
- outp = mac a b c
- c' = outp
+ c' = mac a b c
\end{code}
\begin{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 reflected in the type signature of the function.
+ 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
stateful descriptions using the recursive \hs{run} function:
\begin{code}
- run f s (i:inps) = o : (run f s' inps)
+ run f s (i : inps) = o : (run f s' inps)
where
(s', o) = f s i
\end{code}
- The \hs{run} function maps a list of inputs over the function that a
- developer wants to simulate, passing the state to each new iteration. Each
- value in the input list corresponds to exactly one cycle of the (implicit)
- clock. The result of the simulation is a list of outputs for every clock
- cycle. As both the \hs{run} function and the hardware description are
- plain Haskell, the complete simulation can be compiled by an optimizing
- Haskell compiler.
+ 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.
-\section{\CLaSH\ prototype}
+ 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 \CLaSH\ language as presented above can be translated to \VHDL\ using
-the prototype \CLaSH\ compiler. This compiler allows experimentation with
-the \CLaSH\ language and allows for running \CLaSH\ designs on actual FPGA
-hardware.
+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}}
\label{img:compilerpipeline}
\end{figure}
-The prototype heavily uses \GHC, the Glasgow Haskell Compiler.
-\Cref{img:compilerpipeline} shows the \CLaSH\ compiler pipeline. As you can
-see, the front-end is completely reused from \GHC, which allows the \CLaSH\
-prototype to support most of the Haskell Language. The \GHC\ front-end
-produces the program in the \emph{Core} format, which is a very small,
-functional, typed language which is relatively easy to process.
-
-The second step in the compilation process is \emph{normalization}. This
-step runs a number of \emph{meaning preserving} transformations on the
-Core program, to bring it into a \emph{normal form}. This normal form
-has a number of restrictions that make the program similar to hardware.
-In particular, a program in normal form no longer has any polymorphism
-or higher order functions.
-
-The final step is a simple translation to \VHDL.
+The output of the \GHC\ front-end is the original Haskell description
+translated to \emph{Core}~\cite{Sulzmann2007}, which is smaller, functional,
+typed 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, such a $\beta$-reduction and
+$\eta$-expansion, but also includes \emph{defunctionalization} transformations
+which reduce 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}
\label{img:4tapfir}
\end{figure}
+
+\subsection{Higher order CPU}
+
+
+\begin{code}
+type FuState = State Word
+fu :: (a -> a -> a)
+ -> [a]:n
+ -> (RangedWord n, RangedWord n)
+ -> FuState
+ -> (FuState, a)
+fu op inputs (addr1, addr2) (State out) =
+ (State out', out)
+ where
+ in1 = inputs!addr1
+ in2 = inputs!addr2
+ out' = op in1 in2
+\end{code}
+
+\begin{code}
+type CpuState = State [FuState]:4
+cpu :: Word
+ -> [(RangedWord 7, RangedWord 7)]:4
+ -> CpuState
+ -> (CpuState, Word)
+cpu input addrs (State fuss) =
+ (State fuss', out)
+ where
+ fures = [ fu const inputs!0 fuss!0
+ , fu (+) inputs!1 fuss!1
+ , fu (-) inputs!2 fuss!2
+ , fu (*) inputs!3 fuss!3
+ ]
+ (fuss', outputs) = unzip fures
+ inputs = 0 +> 1 +> input +> outputs
+ out = head outputs
+\end{code}
+
\section{Related work}
Many functional hardware description languages have been developed over the
years. Early work includes such languages as $\mu$\acro{FP}~\cite{muFP}, an
projects / matthijs / master-project / dsd-paper.git / blobdiff