turbonss/BDZ.t2t

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BDZ Algorithm
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==Introduction==
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Coming soon...
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==The Algorithm==
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Coming soon...
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===Mapping Step===
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Coming soon...
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===Assigning Step===
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Coming soon...
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===Ranking Step===
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Coming soon...
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==Memory Consumption==
Now we detail the memory consumption to generate and to store minimal perfect hash functions
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using the BDZ algorithm. The structures responsible for memory consumption are in the
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following:
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- 3-graph:
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+ **first**: is a vector that stores //cn// integer numbers, each one representing
the first edge (index in the vector edges) in the list of
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incident edges of each vertex. The integer numbers are 4 bytes long. Therefore,
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the vector first is stored in //4cn// bytes.
+ **edges**: is a vector to represent the edges of the graph. As each edge
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is compounded by three vertices, each entry stores three integer numbers
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of 4 bytes that represent the vertices. As there are //n// edges, the
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vector edges is stored in //12n// bytes.
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+ **next**: given a vertex [figs/img139.png], we can discover the edges that
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contain [figs/img139.png] following its list of incident edges,
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which starts on first[[figs/img139.png]] and the next
edges are given by next[...first[[figs/img139.png]]...]. Therefore, the vectors first and next represent
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the linked lists of edges of each vertex. As there are three vertices for each edge,
when an edge is iserted in the 3-graph, it must be inserted in the three linked lists
of the vertices in its composition. Therefore, there are //3n// entries of integer
numbers in the vector next, so it is stored in //4*3n = 12n// bytes.
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+ **Vertices degree (vert_degree vector)**: is a vector of //cn// bytes
that represents the degree of each vertex. We can use just one byte for each
vertex because the 3-graph is sparse, once it has more vertices than edges.
Therefore, the vertices degree is represented in //cn// bytes.
- Acyclicity test:
+ **List of deleted edges obtained when we test whether the 3-graph is a forest (queue vector)**:
is a vector of //n// integer numbers containing indexes of vector edges. Therefore, it
requires //4n// bytes in internal memory.
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+ **Marked edges in the acyclicity test (marked_edges vector)**:
is a bit vector of //n// bits to indicate the edges that have already been deleted during
the acyclicity test. Therefore, it requires //n/8// bytes in internal memory.
- MPHF description
+ **function //g//**: is represented by a vector of //2cn// bits. Therefore, it is
stored in //0.25cn// bytes
+ **ranktable**: is a lookup table used to store some precomputed ranking information.
It has //(cn)/(2^b)// entries of 4-byte integer numbers. Therefore it is stored in
//(4cn)/(2^b)// bytes. The larger is b, the more compact is the resulting MPHFs and
the slower are the functions. So b imposes a trade-of between space and time.
+ **Total**: 0.25cn + (4cn)/(2^b) bytes
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Thus, the total memory consumption of BDZ algorithm for generating a minimal
perfect hash function (MPHF) is: //(28.125 + 5c)n + 0.25cn + (4cn)/(2^b) + O(1)// bytes.
As the value of constant //c// may be larger than or equal to 1.23 we have:
|| //c// | //b// | Memory consumption to generate a MPHF (in bytes) |
| 1.23 | //7// | //34.62n + O(1)// |
| 1.23 | //8// | //34.60n + O(1)// |
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| **Table 1:** Memory consumption to generate a MPHF using the BDZ algorithm.
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Now we present the memory consumption to store the resulting function.
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So we have:
|| //c// | //b// | Memory consumption to store a MPHF (in bits) |
| 1.23 | //7// | //2.77n + O(1)// |
| 1.23 | //8// | //2.61n + O(1)// |
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| **Table 2:** Memory consumption to store a MPHF generated by the BDZ algorithm.
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==Experimental Results==
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Experimental results to compare the BDZ algorithm with the other ones in the CMPH
library are presented in Botelho, Pagh and Ziviani [[1 #papers],[2 #papers]].
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==Papers==[papers]
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+ [F. C. Botelho http://www.dcc.ufmg.br/~fbotelho], R. Pagh, [N. Ziviani http://www.dcc.ufmg.br/~nivio]. [Simple and space-efficient minimal perfect hash functions papers/wads07.pdf]. //10th International Workshop on Algorithms and Data Structures (WADs'07),// Springer-Verlag Lecture Notes in Computer Science, vol. 4619, Halifax, Canada, August 2007, 139-150.
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+ [F. C. Botelho http://www.dcc.ufmg.br/~fbotelho]. [Near Space-Optimal Perfect Hashing Algorithms papers/thesis.pdf]. //Thesis Proposal//, //Department of Computer Science//, //Federal University of Minas Gerais//, July 2007.
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