1. Even Wiik Thomassen
  2. thesis


Even Wiik Thomassen  committed 12d49a3

More on conclusion.

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File benchmarks.tex

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-\subsection{Pipeline benchmarks}
+\section{Pipeline benchmarks}
 To be able to evaluate PyHaskell's performance, it is necessary to profile
 where the runtime is spent. When benchmarking, PyHaskell is provided with the

File conclusion.tex

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+The RPython translation toolchain from the PyPy project can be used to write
+\glspl{vm} in a high-level programming language, RPython. To reduce the
+overhead from the many abstractions provided by RPython,
+\eg garbage collection, excetions the toolchain provides a meta-tracing
+\gls{jit}. The meta-tracer can be used by any \gls{vm} written in RPython,
+almost automatically.
+The \glspl{vm} written in RPython cover many programming languages, most of
+them object-oriented, but none yet that are purely functional or lazy.
+Therefore this report posed the following question: \emph{Is the RPython
+translation toolchain suitable for purely functional and lazy languages, \eg
+the Haskell language?}
+, such as automatic
+memory management, inheritance, exceptions, and more.
+I set out to answer two specific research questions:
+    \item \emph{Can Haskell benefit from trace-based \gls{jit} optimization
+            techniques?}
+PyHaskell, a prototype Haskell \gls{vm} with a meta-tracing \gls{jit} compiler,
 The conclusion should briefly summarize the problem

File frontmatter.tex

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 PyHaskell, en virtuell maskin-prototype for Haskell med en meta-tracing
 JIT-kompilator skrevet i RPython, viser at RPython toolchain er egnet for Haskell.
-Selvom meta-traceren øker PyHaskells hastighet kraftig, kan den enda ikke slå
+Selv om meta-traceren øker PyHaskells hastighet kraftig, kan den enda ikke slå