ADPfusion-0.1.0.0: ADPfusion.cabal
name: ADPfusion
version: 0.1.0.0
author: Christian Hoener zu Siederdissen, 2011-2012
copyright: Christian Hoener zu Siederdissen, 2011-2012
homepage: http://www.tbi.univie.ac.at/~choener/adpfusion
maintainer: choener@tbi.univie.ac.at
category: Algorithms, Data Structures, Bioinformatics
license: BSD3
license-file: LICENSE
build-type: Simple
stability: experimental
cabal-version: >= 1.6.0
synopsis:
Efficient, high-level dynamic programming.
description:
ADPfusion combines stream-fusion (using the stream interface
provided by the vector library) and type-level programming to
provide highly efficient dynamic programming combinators.
.
From the programmers' viewpoint, ADPfusion behaves very much
like the original ADP implementation
<http://bibiserv.techfak.uni-bielefeld.de/adp/> developed by
Robert Giegerich and colleagues, though both combinator
semantics and backtracking are different.
.
The library internals, however, are designed not only to speed
up ADP by a large margin (which this library does), but also to
provide further runtime improvements by allowing the programmer
to switch over to other kinds of data structures with better
time and space behaviour. Most importantly, dynamic programming
tables can be strict, removing indirections present in lazy,
boxed tables.
.
As a simple benchmark, consider the Nussinov78 algorithm which
translates to three nested for loops (for C). In the figure,
four different approaches are compared using inputs with size
100 characters to 1000 characters in increments of 100
characters. "C" is an implementation ("./C/" directory) in "C"
using "gcc -O3". "ADP" is the original ADP approach (see link
above), while "GAPC" uses the "GAP" language
(<http://gapc.eu/>).
<<https://github.com/choener/ADPfusion/gaplike-performance.png>>
.
Please note that actual performance will depend much on table
layout and data structures accessed during calculations, but in
general performance is very good: close to C and better than
other high-level approaches (that I know of).
.
.
.
Even complex ADP code tends to be completely optimized to loops
that use only unboxed variables (Int# and others,
indexIntArray# and others).
.
Completely novel (compared to ADP), is the idea of allowing
efficient monadic combinators. This facilitates writing code
that performs backtracking, or samples structures
stochastically, among others things.
.
This version is still highly experimental and makes use of
multiple recent improvements in GHC. This is particularly true
for the monadic interface.
.
.
.
Newley added are the ADP.Fusion.GAPlike modules. These allow
for writing grammars with only one (non)-terminal combinator.
The logic for index manipulation is now moved into data types
for terminals and non-terminals.
.
While this change leads to slightly more complicated instances
for each new terminal or non-terminal, the overall code
complexity is significantly lower. In addition, Constraint
Kinds make complex interactions between (non)-terminals
possible, while still managing to produce high-performance
code.
.
The final goal would, of course, be to have no inter-terminal
combinators anymore.
.
* GHC 7.6, LLVM, and -fnew-codegen recommended: gives a speedup
of x2 for GAPcriterion
.
.
.
.
Long term goals: Outer indices with more than two dimensions,
specialized table design, a combinator library, a library for
computational biology.
.
Two algorithms from the realm of computational biology are
provided as examples on how to write dynamic programming
algorithms using this library:
<http://hackage.haskell.org/package/Nussinov78> and
<http://hackage.haskell.org/package/RNAFold>.
.
Changes since 0.0.1.2:
.
* require GHC 7.6
.
* ADP.Fusion.GAPlike module for (almost) combinator-less grammars
.
* ConstraintKinds for constrained parsers in GAPlike.
.
.
.
Changes since 0.0.1.0:
.
* compatibility with GHC 7.4
.
* note: still using fundeps & and TFs together. The TF-only version does not optimize as well (I know why but not yet how to fix it)
.
.
.
Using the new code generator?
.
The new code generator is not official yet, but I recommend trying it out:
<<https://github.com/choener/ADPfusion/gaplike-newcodegen.png>>
Extra-Source-Files:
README.md
ADP/Fusion/QuickCheck.hs
ADP/Fusion/QuickCheck/Arbitrary.hs
Flag devel
description: build criterion benchmarks and pull in QuickCheck
default: False
library
build-depends:
base >= 4 && < 5,
ghc-prim,
primitive == 0.5.* ,
vector == 0.10.* ,
PrimitiveArray == 0.4.*
exposed-modules:
ADP.Fusion
ADP.Fusion.Monadic
ADP.Fusion.Monadic.Internal
ADP.Fusion.GAPlike
ghc-options:
-O2 -funbox-strict-fields
executable GAPcriterion
buildable:
False
if flag(devel)
buildable:
True
build-depends:
criterion == 0.6.* ,
QuickCheck == 2.5
other-modules:
ADP.Fusion.GAPlike.DevelCommon
ADP.Fusion.GAPlike.Criterion
ADP.Fusion.GAPlike.QuickCheck
main-is:
Tests/GAPcriterion.hs
ghc-options:
-fllvm -O2 -funbox-strict-fields -optlo-O3 -optlo-std-compile-opts
if impl(GHC > 7.4)
ghc-options:
-fnew-codegen
source-repository head
type: git
location: git://github.com/choener/ADPfusion