Thought: We sometimes don't need to distinct Overlay and Connect

[snowleopard]

Thought: We sometimes don't need to distinct Overlay and Connect

[nobrakal]

Yep you were right, it boost a bit performances, but nothing extraordinary:

foldgWithoutEmpty' :: (a -> b) -> (Operator -> [b] -> b) -> Graph a -> b
foldgWithoutEmpty' f h = go
  where
    go (Leaf a) = f a
    go (Node co xs) = h co $ map go xs

induce :: (a -> Bool) -> Graph a -> Graph a
induce p = foldgWithoutEmpty' (\x -> if p x then Vertex x else Empty) (\co t -> Node co $ filter k t)
  where
    k (Node _ []) = False -- Constant folding to get rid of Empty leaves
    k _ = True

removeVertex

Description: Remove a vertex of the graph

Mesh

	1	10	100	1000
Alga	38.59 ns	1.350 μs	19.11 μs	207.2 μs
AlgaOld	41.80 ns	1.072 μs	14.01 μs	170.5 μs

Clique

	1	10	100	1000
Alga	39.35 ns	4.519 μs	539.3 μs	60.47 ms
AlgaOld	41.96 ns	3.419 μs	445.9 μs	155.9 ms

Circuit

	1	10	100	1000
Alga	112.6 ns	1.039 μs	10.68 μs	104.9 μs
AlgaOld	82.09 ns	857.2 ns	7.770 μs	79.26 μs

SUMMARY:

• AlgaOld was the fastest 17 times
• Alga was the fastest 4 times

There was 3 ex-aequo

ABSTRACT:
(Based on an average of the ratio between largest benchmarks)

• Alga was 1.03 times faster than AlgaOld

[snowleopard]

@nobrakal Interesting! Yes, of course you can represent graphs (or any algebraic expressions) simply by trees labelled with operators. In fact, this is similar to what I plan to use for labelled graphs :-)

See here: https://github.com/snowleopard/alga/blob/edge-labels/src/Algebra/Graph/Labelled.hs#L62-L71

There is one important advantage of the current data type that you didn't mention: its constructors exactly correspond to the algebra of graphs.

This also brings us back to the question: do we need to export the constructors? Maybe we shouldn't. Then we'll be free to choose whatever internal representation we like, including yours.

However, I still prefer to keep the 'vanilla' version of the data type in the library simply because it emerges so naturally from the underlying mathematics.

If the goal is, however, to find the most efficient representation possible, I'm quite sure it will actually be something else and it will be complex -- more complex than what you suggest. There is also a relevant discussion here: #61.

[nobrakal]

In fact, this is similar to what I plan to use for labelled graphs :-)

Haha, I missed this!

This also brings us back to the question: do we need to export the constructors?

Finally, maybe exporting constructors is not the right idea to have.

With some GHC hack, we can allow pattern-matching without constructors, using for example ViewPatterns

[snowleopard]

Yes, ViewPatterns may be the way to go.

[nobrakal]

An other option is PatternSynonyms. It is much more like what we need to hide constructors, it provide synonyms.

There is a naming problem: A pattern cannot have the same name as the constructor... But one can pose:

data Graph a = EmptyG
             | VertexG a
             | OverlayG (Graph a) (Graph a)
             | ConnectG (Graph a) (Graph a)
             deriving (Foldable, Functor, Show, Traversable)

pattern Empty :: Graph a
pattern Empty = EmptyG

pattern Vertex :: a -> Graph a
pattern Vertex a = VertexG a

pattern Overlay :: Graph a -> Graph a -> Graph a
pattern Overlay a b = OverlayG a b

pattern Connect :: Graph a -> Graph a -> Graph a
pattern Connect a b = ConnectG a b

{-# COMPLETE Empty, Vertex, Overlay, Connect #-}

Some advantages:

• They can be used to construct graphs effectively, so they can even replace lower-cased aliases.
• They can be a part of the Graph class definition.

[snowleopard]

Yes, this is a promising approach.

While we're thinking about a more efficient internal representation, I think it is also important to consider packing arguments to multi-way + and * into lists. You then end up with something like this:

data Operator = Overlay | Connect
data Graph a = Leaf a | Node Operator [Graph a]

empty = Node Overlay []
vertex = Leaf
overlays = Node Overlay
connects = Node Connect

This works thanks to the associativity of both operators.

[nobrakal]

I played a bit this afternoon and came to:

data Operator = OverlayG | ConnectG deriving (Eq,Show)
data Graph a  = Leaf a | Node Operator [Graph a]
             deriving (Foldable, Functor, Show, Traversable)


pattern Empty :: Graph a
pattern Empty <- Node _ [] where
  Empty = Node OverlayG []

pattern Vertex :: a -> Graph a
pattern Vertex a = Leaf a

pattern Overlay :: Graph a -> Graph a -> Graph a
pattern Overlay a b <- (view -> Node OverlayG [a,b]) where
  Overlay a b = Node OverlayG [a,b]

pattern Connect :: Graph a -> Graph a -> Graph a
pattern Connect a b <- (view -> Node ConnectG [a,b]) where
  Connect a b = Node ConnectG [a,b]

{-# COMPLETE Empty, Vertex, Overlay, Connect #-}
{-# COMPLETE Empty, Vertex, Node #-}

view :: Graph a -> Graph a
view (Node c [a,b])  = Node c [a,b]
view (Node c (x:xs)) = Node c [x,Node c xs]
view g = g

This is passing tests, combining view patterns and patterns synonyms can lead to some interesting results ^^.

Sadly, I think this will slow down the whole thing, since the traditional foldg will not be so efficient !

[nobrakal]

The results of the bench suite, even using custom foldg like the don't require the Connect of Overlay information, for example, I redefined hasVertex with

foldg'' :: b -> (a -> b) -> ([b] -> b) -> Graph a -> b
foldg'' e v o = go
  where
    go Empty         = e
    go (Vertex  x  ) = v x
    go (Node _ xs) = o $ map go xs

hasVertex :: Eq a => a -> Graph a -> Bool
hasVertex x = foldg'' False (==x) or

The result of the benchmarking suite

isEmpty: 0.97
vertexList: 2.33
vertexCount: 2.25
hasVertex: 1.58
edgeCount: 1.94
edgeList: 1.45
hasEdge: 1.63
addEdge: 2.03
addVertex: 2.68
removeVertex: 1.50

[snowleopard]

foldg''

We might call such folds "blindfolds" :-)

Are numbers > 1 good? I'm sure I'll keep forgetting that :D Maybe should add (good), (bad) to the table!

By the way, have you also done overlays = Node Overlay and connects = Node Connect? That should give a good speed up.

[nobrakal]

I added a small reminder:

Comparing Alga to AlgaOld . It means that the displayed number will be k such that Alga = k * AlgaOld

So these are very bad values ^^. I just saw that I haven't changed rnf, so maybe when I used pattern matching, it slowed down the whole thing.

I tired with more specialized foldg but I am not able to obtain descent results

I have pushed the try here: https://github.com/nobrakal/alga/tree/betterRepresentation

A bench is running: https://travis-ci.com/nobrakal/alga/jobs/130222270

[snowleopard]

It means that the displayed number will be k such that Alga = k * AlgaOld

I'm afraid this doesn't help me, still takes me a while to understand =) Why not add obvious (good)/(bad) labels instead? If you want to get fancy, you could also add (OK) when 0.9 < k < 1.1.

vertexList: 1.92

It's quite surprising to see such a slowdown here. We should be doing less work to traverse a tree and find all vertices -- do you have any ideas why this happens? By the way, it may be useful to test the whole Algebra.Graph API in the regression suite.

[nobrakal]

Why not add obvious (good)/(bad) labels instead?

It is done now :)

do you have any ideas why this happens?

Corrected now, it was again a problem with foldl :) Now vertexList is a bit faster:

vertexList

Description: Produce a list of the vertices in the graph

Mesh

	1	10	100	1000
Alga	42.71 ns	312.1 ns	314.5 ns	736.2 ns
AlgaOld	45.18 ns	368.3 ns	371.9 ns	695.7 ns

Clique

	1	10	100	1000
Alga	42.62 ns	1.977 μs	341.9 μs	68.43 ms
AlgaOld	45.30 ns	2.367 μs	442.3 μs	99.67 ms

SUMMARY:

• Alga was the fastest 5 times

There was 3 ex-aequo

ABSTRACT:
(Based on an average of the ratio between largest benchmarks)

• Alga was 1.15 times faster than AlgaOld

My induce is still not convincing:

foldgWithoutEmpty' :: (a -> b) -> ([b] -> b) -> ([b] -> b) -> Graph a -> b
foldgWithoutEmpty' f o c = go
  where
    go (Leaf a) = f a
    go (Node co xs) = case co of
                        OverlayG -> o $ map go xs
                        _ -> c $ map go xs

induce :: (a -> Bool) -> Graph a -> Graph a
induce p = foldgWithoutEmpty' (\x -> if p x then Vertex x else Empty) (overlays . filter k) (connects . filter k)
  where
    k (Node _ []) = False -- Constant folding to get rid of Empty leaves
    k _ = True

removeVertex

Description: Remove a vertex of the graph

Mesh

	1	10	100	1000
Alga	33.06 ns	522.7 ns	529.2 ns	1.395 μs
AlgaOld	35.66 ns	368.3 ns	362.4 ns	925.7 ns

Clique

	1	10	100	1000
Alga	32.52 ns	4.863 μs	561.3 μs	61.48 ms
AlgaOld	34.27 ns	3.098 μs	456.6 μs	172.5 ms

SUMMARY:

• AlgaOld was the fastest 10 times
• Alga was the fastest 2 times

There was 4 ex-aequo

ABSTRACT:
(Based on an average of the ratio between largest benchmarks)

• Alga was 1.07 times faster than AlgaOld

By the way, it may be useful to test the whole Algebra.Graph API in the regression suite.

Yeah of course. I don't really now where to do that (because I need to extend the configuration file in haskell-perf/graph). Here ? In nobrakal/benchAlgaPr (I am not satisfied with this repo).

[snowleopard]

Thanks @nobrakal!

Perhaps, for foldgWithoutEmpty' you need to use parameter Operator -> [b] -> b instead? That might lead to a more efficient code.

[nobrakal]

Ooops, I spent some time to figure out the the bench-suite was broken. A mesh wasn't a real mesh !

Here is the corrected times:

removeVertex

Description: Remove a vertex of the graph

Mesh

	1000
Alga	195.8 μs
AlgaOld	185.9 μs

Clique

	1000
Alga	55.75 ms
AlgaOld	163.2 ms

Circuit

	1000
Alga	98.39 μs
AlgaOld	89.24 μs

SUMMARY:

• Alga was the fastest 2 times
• AlgaOld was the fastest 2 times

There was 2 ex-aequo

ABSTRACT:
(Based on an average of the ratio between largest benchmarks)

• Alga was 1.20 times faster than AlgaOld

So there is a surprising drop for clique. Again, strangely,

induce :: (a -> Bool) -> Graph a -> Graph a
induce p = go
  where
    go (Leaf a) = if p a then Leaf a else Empty
    go (Node co xs) = Node co $ filter k $ map go xs 
    k (Node _ []) = False -- Constant folding to get rid of Empty leaves
    k _ = True

Is not faster, it is worse:

removeVertex

Description: Remove a vertex of the graph

Mesh

	1000
Alga	224.7 μs
AlgaOld	169.3 μs

Clique

	1000
Alga	68.39 ms
AlgaOld	169.2 ms

Circuit

	1000
Alga	116.9 μs
AlgaOld	80.39 μs

SUMMARY:

• AlgaOld was the fastest 4 times
• Alga was the fastest 2 times

ABSTRACT:
(Based on an average of the ratio between largest benchmarks)

• AlgaOld was 1.06 times faster than Alga

Perhaps, for foldgWithoutEmpty' you need to use parameter Operator -> [b] -> b instead? That might lead to a more efficient code.

What do you mean ?

[snowleopard]

What do you mean?

I mean the function signature should be:

foldgWithoutEmpty' :: (a -> b) -> (Operator -> [b] -> b) -> Graph a -> b
foldgWithoutEmpty' v op g = ...

The function op here deals with both types of nodes, so one of the conditionals (checking the operator of the current node) disappears/is pushed inside the function.

[nobrakal]

Again, this is a problem with edges. Maybe I should change the comparing script to use the alga representation instead of edges, but edges is what users will use.

The same code benchmarked using alga's clique:

Clique

	1000
Alga	29.79 μs
AlgaOld	34.93 μs

[snowleopard]

I agree: edges is very often used to construct graphs, so we shouldn't assume graph expressions are coming in a better shape.

[nobrakal]

So I don't know if we can make a better induce here (and because all the graphs structures are similar when building with edges, our induce is faster on very big lists nested inside a Node)

[nobrakal]

Note that the implementation described in #84 (comment) shows great results here

### Clique
#### 1000
##### (0,1)

+---------++----------+-------+
|         ||     Time |    R² |
+=========++==========+=======+
|    Alga || 76.30 ns | 1.000 |
| AlgaOld || 93.11 ms | 0.898 |
+---------++----------+-------+

##### (292,820)

+---------++----------+-------+
|         ||     Time |    R² |
+=========++==========+=======+
|    Alga || 18.99 ms | 0.971 |
| AlgaOld || 95.07 ms | 0.970 |
+---------++----------+-------+

##### (997,999)

+---------++----------+-------+
|         ||     Time |    R² |
+=========++==========+=======+
|    Alga || 45.77 ms | 0.996 |
| AlgaOld || 88.05 ms | 0.974 |
+---------++----------+-------+

##### (0,0)

+---------++----------+-------+
|         ||     Time |    R² |
+=========++==========+=======+
|    Alga || 32.41 ms | 0.999 |
| AlgaOld || 90.33 ms | 0.978 |
+---------++----------+-------+

##### (1,0)

+---------++----------+-------+
|         ||     Time |    R² |
+=========++==========+=======+
|    Alga || 45.26 ms | 1.000 |
| AlgaOld || 92.34 ms | 0.979 |
+---------++----------+-------+

##### (1,1)

+---------++----------+-------+
|         ||     Time |    R² |
+=========++==========+=======+
|    Alga || 31.54 ms | 1.000 |
| AlgaOld || 90.06 ms | 0.980 |
+---------++----------+-------+

Even with an algebraic clique:

### Clique
#### 1000
##### (0,1)

+---------++----------+-------+
|         ||     Time |    R² |
+=========++==========+=======+
|    Alga || 71.73 ns | 0.995 |
| AlgaOld || 48.15 μs | 1.000 |
+---------++----------+-------+

##### (292,820)

+---------++----------+-------+
|         ||     Time |    R² |
+=========++==========+=======+
|    Alga || 16.92 μs | 1.000 |
| AlgaOld || 53.08 μs | 1.000 |
+---------++----------+-------+

##### (997,999)

+---------++----------+-------+
|         ||     Time |    R² |
+=========++==========+=======+
|    Alga || 33.32 μs | 0.999 |
| AlgaOld || 53.66 μs | 1.000 |
+---------++----------+-------+

##### (0,0)

+---------++----------+-------+
|         ||     Time |    R² |
+=========++==========+=======+
|    Alga || 26.77 μs | 1.000 |
| AlgaOld || 48.66 μs | 1.000 |
+---------++----------+-------+

##### (1,0)

+---------++----------+-------+
|         ||     Time |    R² |
+=========++==========+=======+
|    Alga || 28.30 μs | 1.000 |
| AlgaOld || 48.14 μs | 1.000 |
+---------++----------+-------+

##### (1,1)

+---------++----------+-------+
|         ||     Time |    R² |
+=========++==========+=======+
|    Alga || 95.58 ns | 0.996 |
| AlgaOld || 48.75 μs | 1.000 |
+---------++----------+-------+

[snowleopard]

Interesting, that's an impressive speed up.