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Update related work Chapter 5

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Daniel Hillerström 5 years ago
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@ -3130,7 +3130,6 @@ language.
\hline
\end{tabular}
\caption{Classification of first-class delimited control operators (listed in chronological order).}\label{tbl:classify-ctrl-delimited}
% \dhil{TODO: Possibly split into two tables: undelimited and delimited. Change the table to display the behaviour of control reifiers.}
\end{table}
%
@ -11096,8 +11095,12 @@ run. Nevertheless, this is the approach to concurrency that
OCaml~\cite{DolanWSYM15}.
%
In my MSc(R) dissertation I used a similar approach to implement a
cooperative version of the actor concurrency model of Links with
effect handlers~\cite{Hillerstrom16}.
cooperative version of the actor concurrency model of Links as a
user-definable Links library~\cite{Hillerstrom16}. This library was
used by a prototype compiler for Links to make the runtime as lean as
possible~(this compiler hooked directly into the backend of the
Multicore OCaml compiler in order to produce native code for effect
handlers~\cite{HillerstromL16}).
%
This line of work was further explored by \citet{Convent17}, who
implemented various cooperative actor-based concurrency abstractions
@ -11121,26 +11124,35 @@ higher-order operations with linearly used resumptions, whereas
operations with multi-shot resumptions, and thus, it is close in the
spirit to the schedulers we have considered in this chapter.
\paragraph{Continuation-based interleaved computation}
The very first implementation of `lightweight threads' using
continuations can possibly be credited to
\citet{Burstall69}. \citeauthor{Burstall69} used
\citeauthor{Landin65}'s J operator to arrange tree-based search, where
each branch would be reified as a continuation and put into a
queue.
\paragraph{Continuations and operating systems}
% The very first implementation of `lightweight threads' using
% continuations can possibly be credited to
% \citet{Burstall69}. \citeauthor{Burstall69} used
% \citeauthor{Landin65}'s J operator to arrange tree-based search, where
% each branch would be reified as a continuation and put into a
% queue.
The idea of using continuations to implement various facets of
operating systems is not new. However, most work has focused on
implementing some form of multi-tasking mechanism.
%
\citet{Wand80} implements a small multi-tasking kernel with support
for mutual exclusion and data protection using undelimited
continuations in the style of the catch operator of Scheme.
\citet{HaynesFW86} codify coroutines as library using call/cc.
% \citet{HaynesFW86} codify coroutines as library using call/cc.
\citet{DybvigH89} implements \emph{engines} using call/cc in Scheme
--- an engine is a kind of process abstraction which support
preemption. An engine runs a computation on some time budget. If
computation exceeds the allotted time budget, then it is
interrupted. They represent engines as reified continuations and use
the macro system of Scheme to insert clock ticks at appropriate places
in the code. \citet{HiebD90} also design the \emph{spawn-controller}
operator for programming tree-based concurrency abstractions.
in the code. % \citet{HiebD90} also design the \emph{spawn-controller}
% operator for programming tree-based concurrency abstractions.
\citet{KiselyovS07a} develop a small fault-tolerant operating system
with multi-tasking support and a file system using delimited
continuations. Their file system is considerably more sophisticated
than the one we implemented in this chapter as it supports
transactional storage, meaning user processes can roll back actions
such as file deletion and file update.
\paragraph{Resumption monad}
The resumption monad is both a semantic and programmatic abstraction
@ -16593,7 +16605,7 @@ We now define $\HPCF$ as an extension of $\BPCF$.
{
\begin{syntax}
\slab{Operation\textrm{ }symbols} &\ell \in \mathcal{L} & & \\
\slab{Signatures} &\Sigma \CatName{Sig} &::=& \cdot \mid \{\ell : A \to B\} \cup \Sigma\\
\slab{Signatures} &\Sigma\in\CatName{Sig} &::=& \cdot \mid \{\ell : A \to B\} \cup \Sigma\\
\slab{Handler\textrm{ }types} &F \in \HandlerTypeCat &::=& C \Rightarrow D\\
\slab{Computations} &M, N \in \CompCat &::=& \dots \mid \Do \; \ell \; V
\mid \Handle \; M \; \With \; H \\
@ -16732,7 +16744,7 @@ we call handler contexts.
%
{
\begin{syntax}
\slab{Handler\textrm{ }contexts} & \HC \CatName{Ctx} &::= & [\,] \mid \Handle \; \HC \; \With \; H
\slab{Handler\textrm{ }contexts} & \HC \in \CatName{HCtx} &::= & [\,] \mid \Handle \; \HC \; \With \; H
\mid \Let\;x \revto \HC\; \In\; N\\
\end{syntax}}%
%
@ -19738,6 +19750,11 @@ for helping me relearning this fact from first principles).
\chapter{Proofs of correctness of the higher-order uncurried CPS
translation}
\label{sec:proofs-cps-gen-cont}
This appendix contains the proof details for the higher-order
uncurried CPS translation.
\paragraph{Relation to prior work} This appendix is imported from
Appendix A of \citet{HillerstromLA20}.\medskip
\begin{lemma}[Substitution]\label{lem:subst-gen-cont-proof}
%
The CPS translation commutes with substitution in value terms
@ -20697,10 +20714,14 @@ dynamic language, as described above.
}
%
In this appendix we give proof details and artefacts for
Theorem~\ref{thm:complexity-effectful-counting}. Throughout this
section we let $\HCount$ denote the handler definition of $\Count$,
that is
In this appendix I give the proof details and artefacts for
Theorem~\ref{thm:complexity-effectful-counting}.
\paragraph{Relation to prior work} This appendix is imported from
Appendix C of \citet{HillerstromLL20a}.\medskip
Throughout this section we let $\HCount$ denote the handler definition
of $\Count$, that is
%
\[
\HCount \defas
@ -21127,6 +21148,8 @@ of Theorem~\ref{thm:complexity-effectful-counting}.
\stepsto& \reason{\mlab{App}}\\
&\cek{\Do\;\Branch~\Unit \mid \env'[\_ \mapsto k] \mid (\sigma, \hclo(P)) \cons \residual(bs, P)}\\
\whereX{\env' = \initial(P)}\\
\end{derivation}
\begin{derivation}
\stepsto& \reason{\mlab{Handle-Op}, $\hclo(P)^{\Branch} = \{\Branch~\Unit~r \mapsto \cdots\}$}\\
&\left\langle
\ba[m]{@{}l}
@ -21149,7 +21172,7 @@ of Theorem~\ref{thm:complexity-effectful-counting}.
\whereX{\env' = \env[r \mapsto (\sigma, \hclo(P))]}\\
\stepsto& \reason{\mlab{Let}, definition of $\residual$}\\
&\cek{r~\True \mid \env' \mid \residual(\snoc{bs}{\True} bs, P)}\\
\stepsto& \reason{\mlab{Resume}, $\val{r}\env' = (\sigma, \hclo(P))$ ($\log|\env'| = 1$ environment operations)}\\
\stepsto& \reason{\mlab{Resume}, $\val{r}\env' = (\sigma, \hclo(P))$}\\
&\cek{\Return\;\True \mid \env' \mid (\sigma, \hclo(P)) \cons \residual(\snoc{bs}{\True}, P)}
\end{derivation}
%
@ -21166,7 +21189,8 @@ of Theorem~\ref{thm:complexity-effectful-counting}.
\stepsto&^{\steps(\tree)(\snoc{bs}{\True})} \reason{by Lemma~\ref{lem:inductive-lem-aux}}\\
&\cek{z~V \mid \env'' \mid (\sigma', \hclo(P)) \cons \residual(\snoc{bs}{\True}, P)}\\
\whereX{\ba[t]{@{~}l}
z~V = \comp(\tree)(bs), \env'' = \dec{env}(\tree)(\snoc{bs}{\True})[z \mapsto (\initial(P), \Superpoint)],\\
z~V = \comp(\tree)(bs), \\
\env'' = \dec{env}(\tree)(\snoc{bs}{\True})[z \mapsto (\initial(P), \Superpoint)],\\
?k = \labs(\tree)(\snoc{bs}{\True}), \val{V}\env'' = k, \text{ and } \sigma' = \Pure(\tree)(\snoc{bs}{\True})
\ea}\\
=& \reason{definition of $\arrive$ when $1 + |bs| < n$}\\
@ -21178,15 +21202,15 @@ of Theorem~\ref{thm:complexity-effectful-counting}.
\whereX{i = c(\snoc{\snoc{bs}{\True}}{\True}) + c(\snoc{\snoc{bs}{\True}}{\False})\\
\text{ and } \env = \ascend{\False}(\snoc{bs}{\True}, P)}\\
=& \reason{definition of $\residual$ and $\purecont$}\\
&\cek{\Return\;i \mid \env \mid [((\env', x_\True, \Let\;x_\False\revto r~\False\;\In\;x_\True+x_\False) \cons \purecont(bs, P), \chi_{id})]}\\
&\langle\Return\;i \mid \env \mid [(\bl(\env', x_\True, \Let\;x_\False\revto r~\False\;\In\;x_\True+x_\False)\\ \cons \purecont(bs, P), \chi_{id})]\rangle\el\\
\whereX{\env' = \descend{\True}(bs, P)}\\
\end{derivation}
\begin{derivation}
\stepsto& \reason{\mlab{RetCont}}\\
&\cek{\Let\;x_\False\revto r~\False\;\In\;x_\True+x_\False \mid \env'' \mid [(\purecont(bs, P), \chi_{id})]}\\
\whereX{\env'' = \env'[x_\True \mapsto \val{i}\env']}\\
\stepsto& \reason{\mlab{Let}}\\
&\cek{r~\False \mid \env'' \mid [((\env'', x_\False, x_\True + x_\False) \cons \purecont(bs, P), \chi_{id})]}
\end{derivation}
\begin{derivation}
&\cek{r~\False \mid \env'' \mid [((\env'', x_\False, x_\True + x_\False) \cons \purecont(bs, P), \chi_{id})]}\\
=& \reason{definition of $\purecont$ and $\residual$}\\
&\cek{r~\False \mid \env'' \mid \residual(\snoc{bs}{\False}, P)}\\
\stepsto& \reason{\mlab{Resume}}\\
@ -21288,7 +21312,9 @@ of Theorem~\ref{thm:complexity-effectful-counting}.
&\cek{\Return\;i \mid \env \mid \residual(\snoc{bs}{\True}, P)}\\
\whereX{i = c(\snoc{bs}{\True}) \leq 2^{n - |\snoc{bs}{\True}|} = 1 \text{ and } \env = \initial(P)}\\
=& \reason{definition of $\residual$ and $\purecont$}\\
&\cek{\Return\;i \mid \env \mid [((\env',x_\True,\Let\;x_\False\revto r~\False\;\In\;x_\True+x_\False) \cons \purecont(bs, P), \chi_{id})]}\\
&\langle\Return\;i \mid \env \mid [(\bl(\env',x_\True,\Let\;x_\False\revto r~\False\;\In\;x_\True+x_\False)\\ \cons \purecont(bs, P), \chi_{id})]\rangle\el\\
\end{derivation}
\begin{derivation}
\stepsto& \reason{\mlab{RetCont}}\\
&\cek{\Let\;x_\False \revto r~\False\;\In\;x_\True + x_\False \mid \env'[x_\True \mapsto \val{i}\env'] \mid [(\purecont(bs, P), \chi_{id})]}\\
=& \reason{definition of $\val{-}$ (1 value step)}\\
@ -21312,8 +21338,6 @@ of Theorem~\ref{thm:complexity-effectful-counting}.
=& \reason{definition of $\depart$ when $1 + |bs| = n$}\\
&\cek{\Return\;j \mid \env \mid \residual(\snoc{bs}{\False}, P)}\\
\whereX{j = c(\snoc{bs}{\False}) \leq 2^{n - |\snoc{bs}{\False}|} = 1 \text{ and } \env = \initial(P)}\\
\end{derivation}
\begin{derivation}
=& \reason{definition of $\residual$ and $\purecont$}\\
&\cek{\Return\;j \mid \env \mid [((\env',x_\False,x_\True+x_\False) \cons \purecont(bs, P), \chi_{id})]}\\
\whereX{\env' = \descend{\False}(bs, P)}\\
@ -21413,6 +21437,8 @@ number of transitions used were
&3 + \steps(\tree)(\nil) + T(\nil, n)\\
=& \reason{definition of $T$}\\
&3 + \steps(\tree)(\nil) + 9*2^n + 2^{n + 1} + \displaystyle\sum_{bs' \in \mathbb{B}^{\ast}}^{1 \leq |bs'| \leq n}\steps(\tree)(bs')\\
\end{derivation}
\begin{derivation}
=& \reason{simplify}\\
&3 + \steps(\tree)(\nil) + 9*2^n + 2^{n + 1} + \displaystyle\sum_{bs' \in \mathbb{B}^{\ast}}^{1 \leq |bs'| \leq n}\steps(\tree)(bs')\\
=& \reason{reorder}\\
@ -21430,27 +21456,32 @@ number of transitions used were
\chapter{Berger count}
\label{sec:berger-count}
Here we present the $\BergerCount$ program alluded to in
Section~\ref{sec:pure-counting}, in order to fill out our overall
picture of the relationship between language expressivity and
potential program efficiency.
Berger's original program~\citep{Berger90} introduced a remarkable
search operator for predicates on \emph{infinite} streams of booleans,
and has played an important role in higher-order computability
theory~\citep{LongleyN15}. What we wish to highlight here is that if
one applies the algorithm to predicates on \emph{finite} boolean
vectors, the resulting program, though no longer interesting from a
computability perspective, still holds some interest from a complexity
standpoint: indeed, it yields what seems to be the best available
implementation of generic count within a PCF-style `functional'
language (provided one accepts the use of a primitive for call-by-need
evaluation).
We give the gist of an adaptation of Berger's search algorithm on
finite spaces.
In this appendix I will give a brief presentation of the
$\BergerCount$ program alluded to in Section~\ref{sec:pure-counting},
in order to fill out our overall picture of the relationship between
language expressivity and potential program efficiency.
\paragraph{Relation to prior work} This appendix imported from
Appendix D of \citet{HillerstromLL20a}. The code snippets in this
appendix are based on an implementation of Berger count in SML/NJ
written by John Longley. I have transcribed the code snippets, and in
certain places tweaked it for presentation.\medskip
\citeauthor{Berger90}'s original program~\cite{Berger90} introduced a
remarkable search operator for predicates on \emph{infinite} streams
of booleans, and has played an important role in higher-order
computability theory~\cite{LongleyN15}. What we wish to highlight
here is that if one applies the algorithm to predicates on
\emph{finite} boolean vectors, the resulting program, though no longer
interesting from a computability perspective, still holds some
interest from a complexity standpoint: indeed, it yields what seems to
be the best available implementation of generic count within a
PCF-style `functional' language (provided one accepts the use of a
primitive for call-by-need evaluation).
Let us consider an adaptation of Berger's search algorithm on finite
spaces.
%
{
\[
\bl
\bestshot_n: \Predicate_n \to \Point_n\\
@ -21461,8 +21492,12 @@ finite spaces.
\ba[t]{@{}l}
\Let\; f \revto \dec{memoise}~(\lambda\Unit. \bestshot''_n~pred~start)\; \In\\
\Return\;(\lambda i. \If\; i < |start| \;\Then\; start.i \;\Else\; (f~\Unit).i)
\ea\medskip\\
\ea
\el
\]
%
\[
\bl
\bestshot''_n : \Predicate_n \to \List_\Bool \to \List_\Bool\\
\bestshot''_n~pred~start \defas
\ba[t]{@{}l}
@ -21475,7 +21510,7 @@ finite spaces.
\ea
\ea
\el
\]}%
\]%
%
Given any $n$-standard predicate $P$ the function $\bestshot_n$
returns a point satisfying $P$ if one exists, or dummy point
@ -21499,10 +21534,9 @@ its argument $q$.
The above program makes use of an operation
%
{\small
\[
\dec{memoise} : (\One \to \dec{List}~\Bool) \to (\One \to \dec{List}~\Bool)
\]}%
\]%
%
which transforms a given thunk into an equivalent `memoised' version,
i.e. one that caches its value after its first invocation and
@ -21518,20 +21552,24 @@ obtained by replacing $\dec{memoise}$ by the identity.
We now show how the above idea may be exploited to yield a generic
count program (this development appears to be new).
%
{\small\[
\[
\bl
\BergerCount_n : \Predicate_n \to \Nat\\
\BergerCount_n~pred \defas \Count'_n~pred~[]~0 \medskip\\
\el
\]
\[
\bl
\Count'_n : \Predicate_n \to \List_\Bool \to \Nat \to \Nat\\
\Count'_n~pred~start~acc \defas
\ba[t]{@{}l}
\If\; |start| = n\; \Then\; acc +
(\If\; pred\,(\lambda i. start.i) \;\Then\;\Return\;1 \;\Else\;\Return\;0)\\
(\bl\If\; pred\,(\lambda i. start.i) \;\Then\;\Return\;1\\\Else\;\Return\;0)\el\\
\Else\;
\ba[t]{@{}l}
\Let\; f \revto \bestshot'_n~pred~start\; \In\\
\If\; pred~f \;\Then\; \Count''_n~start~ [f~0,\dots,f~(n-1)]~acc \;\Else\; \Return\;acc
\If\; pred~f \;\Then\; \Count''_n~start~ [f~0,\dots,f~(n-1)]~acc \\
\Else\;\Return\;acc
\ea
\ea \medskip\\
@ -21542,12 +21580,13 @@ count program (this development appears to be new).
\Else\;
\ba[t]{@{}l}
\Let\; b \revto leftmost.|start|\; \In\\
\Let\; acc' \revto \Count''_n~pred~(\dec{append}~start~[b])~leftmost~acc\; \In\\
\If\; b \; \Then\; \Count'_n~pred~(\dec{append}~start~[\False])~acc' \;\Else~\Return\;acc'
\Let\; acc' \revto \Count''_n~pred~\bl(\dec{append}~start~[b])\\leftmost~acc\; \In\el\\
\If\; b \; \Then\; \Count'_n~pred~(\dec{append}~start~[\False])~acc'\\
\Else~\Return\;acc'
\ea
\ea
\el
\]}%
\]%
%
Again, $\BergerCount_n$ is implemented by means of two mutually
recursive auxiliary functions. The function $\Count'_n$ counts the

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