A Fast Output-Sensitive Algorithm for Boolean Matrix Multiplication
We use randomness to exploit the potential sparsity of the Boolean matrix product in order to speed up the computation of the product. Our new fast output-sensitive algorithm for Boolean matrix product and its witnesses is randomized and provides the Boolean product and its witnesses almost certainl...
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| Vydané v: | Algorithmica Ročník 61; číslo 1; s. 36 - 50 |
|---|---|
| Hlavný autor: | |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Boston
Springer US
01.09.2011
|
| Predmet: | |
| ISSN: | 0178-4617, 1432-0541, 1432-0541 |
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| Abstract | We use randomness to exploit the potential sparsity of the Boolean matrix product in order to speed up the computation of the product. Our new fast output-sensitive algorithm for Boolean matrix product and its witnesses is randomized and provides the Boolean product and its witnesses almost certainly. Its worst-case time performance is expressed in terms of the input size and the number of non-zero entries of the product matrix. It runs in time
, where the input matrices have size
n
×
n
, the number of non-zero entries in the product matrix is at most
s
,
ω
is the exponent of the fast matrix multiplication and
denotes
O
(
f
(
n
)log
d
n
) for some constant
d
. By the currently best bound on
ω
, its running time can be also expressed as
. Our algorithm is substantially faster than the output-sensitive column-row method for Boolean matrix product for
s
larger than
n
1.232
and it is never slower than the fast
-time algorithm for this problem. By applying the fast rectangular matrix multiplication, we can refine our upper bound further to the form
, where
ω
(
p
,
q
,
t
) is the exponent of the fast multiplication of an
n
p
×
n
q
matrix by an
n
q
×
n
t
matrix.
We also present a partial derandomization of our algorithm as well as its generalization to include the Boolean product of rectangular Boolean matrices. Finally, we show several applications of our output-sensitive algorithms. |
|---|---|
| AbstractList | We use randomness to exploit the potential sparsity of the Boolean matrix product in order to speed up the computation of the product. Our new fast outputsensitive algorithm for Boolean matrix product and its witnesses is randomized and provides the Boolean product and its witnesses almost certainly. Its worst-case time performance is expressed in terms of the input size and the number of non-zero entries of the product matrix. It runs in time (O) over tilde (n(2)s(omega/2-1)), where the input matrices have size nxn, the number of non-zero entries in the product matrix is at most s, omega is the exponent of the fast matrix multiplication and (O) over tilde (f(n)) denotes O(f(n)log(d) n) for some constant d. By the currently best bound on., its running time can be also expressed as (O) over tilde (n(2)s(0.188)). Our algorithm is substantially faster than the output-sensitive column-row method for Boolean matrix product for s larger than n(1.232) and it is never slower than the fast (O) over tilde (n(omega))-time algorithm for this problem. By applying the fast rectangular matrix multiplication, we can refine our upper bound further to the form (O) over tilde (n(omega(1/2) (logns, 1,1))), where omega(p, q, t) is the exponent of the fast multiplication of an n(p) x n(q) matrix by an n(q) x n(t) matrix. We also present a partial derandomization of our algorithm as well as its generalization to include the Boolean product of rectangular Boolean matrices. Finally, we show several applications of our output-sensitive algorithms. We use randomness to exploit the potential sparsity of the Boolean matrix product in order to speed up the computation of the product. Our new fast output-sensitive algorithm for Boolean matrix product and its witnesses is randomized and provides the Boolean product and its witnesses almost certainly. Its worst-case time performance is expressed in terms of the input size and the number of non-zero entries of the product matrix. It runs in time , where the input matrices have size n × n , the number of non-zero entries in the product matrix is at most s , ω is the exponent of the fast matrix multiplication and denotes O ( f ( n )log d n ) for some constant d . By the currently best bound on ω , its running time can be also expressed as . Our algorithm is substantially faster than the output-sensitive column-row method for Boolean matrix product for s larger than n 1.232 and it is never slower than the fast -time algorithm for this problem. By applying the fast rectangular matrix multiplication, we can refine our upper bound further to the form , where ω ( p , q , t ) is the exponent of the fast multiplication of an n p × n q matrix by an n q × n t matrix. We also present a partial derandomization of our algorithm as well as its generalization to include the Boolean product of rectangular Boolean matrices. Finally, we show several applications of our output-sensitive algorithms. |
| Author | Lingas, Andrzej |
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| Cites_doi | 10.1016/0020-0190(71)90006-8 10.1006/jcom.1998.0476 10.4007/annals.2004.160.781 10.1023/A:1009716300509 10.1007/BF01940874 10.1016/0885-064X(89)90015-0 10.1016/S0019-9958(85)80024-3 10.1016/0304-3975(75)90009-2 10.1016/S0747-7171(08)80013-2 10.1007/3-540-49543-6_18 10.1006/jcss.1999.1690 10.1137/0204027 10.1016/j.tcs.2007.02.053 10.1214/aop/1176996762 |
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| Keywords | Rectangular matrix multiplication Boolean matrix multiplication Time complexity Output-sensitive algorithm |
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| SubjectTerms | Algorithm Analysis and Problem Complexity Algorithms Computer and Information Sciences Computer Science Computer Sciences Computer Systems Organization and Communication Networks Data Structures and Information Theory Data- och informationsvetenskap (Datateknik) Datavetenskap (Datalogi) Mathematics of Computing Natural Sciences Naturvetenskap Theory of Computation |
| Title | A Fast Output-Sensitive Algorithm for Boolean Matrix Multiplication |
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