Changes between Version 52 and Version 53 of DataParallel/BenchmarkStatus
 Timestamp:
 Dec 2, 2010 3:59:06 AM (7 years ago)
Legend:
 Unmodified
 Added
 Removed
 Modified

DataParallel/BenchmarkStatus
v52 v53 39 39  dph.sumsq.vectorised.par.N4  111ms  3.63   40 40 41 '''S ummary''': fine[[br]]41 '''Status''': fine[[br]] 42 42 '''Todo''': Add a sequential C version. 43 43 … … 55 55 A: The sequential vectorised version is faster than with Data.Vector. Why was this? 56 56 57 '''S ummary''': fine.[[br]]57 '''Status''': fine[[br]] 58 58 '''Todo''': Add a sequential C version. 59 59 … … 68 68  dph.evens.vectorised.par.N4  859ms  1.25   69 69 70 '''S ummary''': Benchmark runs slower when number of threads increases. This benchmark invokes {{{packByTag}}} due to the filtering operation. This is probably affecting Quickhull as it also uses filtering. [[br]]70 '''Status''': Benchmark runs slower when number of threads increases. This benchmark invokes {{{packByTag}}} due to the filtering operation. This is probably affecting Quickhull as it also uses filtering. [[br]] 71 71 '''Todo''': Fix slowdown. Add a sequential C version. 72 72 … … 87 87 88 88 [[br]] 89 [http://darcs.haskell.org/libraries/dph/dphexamples/spectral/QuickSort/ QuickSort] '''(BROKEN)''':: 90 Sort a vector of doubles by recursively splitting the vector and sorting the two halves. This is a "fake" benchmark because we divide right down to twopoint vectors and construct the result using copying append. A production algorithm would switch to an inplace sort once the size of the vector reaches a few thousand elements. 91 92  '''name'''  '''runtime'''  '''speedup'''  '''notes'''  93  dph.quicksort.vectorised.par.N1  428ms  1   94  dph.quicksort.vectorised.par.N2  400ms  1.07   95  dph.quicksort.vectorised.par.N4  392ms  1.09   96 97 '''Status''': Sequential vectorised version does not compile due to a blowup in !SpecConstr. 98 99 [[br]] 89 100 [http://darcs.haskell.org/libraries/dph/dphexamples/spectral/QuickHull/ Quickhull] '''(SLOWLORIS)''':: 90 Given a set of points (in a plane), compute the sequence of points that encloses all points in the set. This benchmark is interesting as it is the simplest code that exploits the ability to implement divideandconquer algorithms with nested data parallelism.101 Given a set of points in the plane, compute the sequence of points that encloses all points in the set. This benchmark is interesting as it is the simplest code that exploits the ability to implement divideandconquer algorithms with nested data parallelism. 91 102 92 103 … … 101 112  dph.quickhull.c.seq  0.044s  3.77   102 113 103 '''Status''': Benchmark scales but is 4x slower than version using immutable Data.Vectors. This benchmarkis based around filtering operations, so the fact that Evens is also slow is probably related.114 '''Status''': Benchmark scales but is 4x slower than version using immutable Data.Vectors. !QuickHull is based around filtering operations, so the fact that Evens is also slow is probably related. 104 115 105 [http://darcs.haskell.org/packages/dph/examples/qsort/ Quicksort]::106 FIXME107 116 108 117 [[br]]