Difference between revisions of "Strassen algorithm"

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m (Strassen algorithm)
m (Strassen algorithm)
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   A_{12}^TA_{11}+A_{22}^TA_{21} & A_{12}^TA_{12}+A_{22}^TA_{22}
 
   A_{12}^TA_{11}+A_{22}^TA_{21} & A_{12}^TA_{12}+A_{22}^TA_{22}
 
\end{pmatrix}</math> such that <math>T_q(2n) = 4T_s(n) + 2n^{(_2 7)}</math> and <math>T_q(n) = 4T_s(n/2) + 2/7n^{(_2 7)} = 2/3n^{(_2 3)} + 4/7n^{(_2 7)}</math>.<math>\square</math>
 
\end{pmatrix}</math> such that <math>T_q(2n) = 4T_s(n) + 2n^{(_2 7)}</math> and <math>T_q(n) = 4T_s(n/2) + 2/7n^{(_2 7)} = 2/3n^{(_2 3)} + 4/7n^{(_2 7)}</math>.<math>\square</math>
 
'''New algorithm for two symmetric matrices:'''
 
 
For two symmetric matrices <math>A, B \in \mathbb{C}^{n \times n}</math> where <math>n \in \mathbb{N}^*</math> the runtime is for the matrix product <math>AB</math> about <math>6/7</math> that of the original algorithm in <math>\mathcal{O}(n^{(_2 7)})</math>.
 
 
'''Proof:''' For <math>B :=
 
  \begin{pmatrix}
 
  B_{11} & B_{12} \\
 
  B_{12} & B_{22}
 
  \end{pmatrix}</math>, it holds that <math>A^TB =
 
  \begin{pmatrix}
 
  A_{11}^TB_{11}+A_{12}^TB_{12} & A_{11}^TB_{12}+A_{12}^TB_{22} \\
 
  A_{12}^TB_{11}+A_{22}^TB_{12} & A_{12}^TB_{12}+A_{22}^TB_{22}
 
\end{pmatrix} =: C</math>. Putting
 
 
: <math>M_{1} := A_{12} \cdot (B_{11} + B_{12})</math>
 
: <math>M_{2} := A_{12} \cdot (B_{12} + B_{22})</math>
 
: <math>M_{3} := A_{22} \cdot (B_{12} + B_{22})</math>
 
: <math>M_{4} := (A_{12} - A_{11})\cdot B_{11}</math>
 
: <math>M_{5} := (A_{12} - A_{11})\cdot B_{12}</math>
 
: <math>M_{6} := (A_{12} - A_{22})\cdot B_{22}</math>
 
 
implies
 
 
: <math>C_{11} = M_{1} - M_{4}</math>
 
: <math>C_{12} = M_{2} - M_{5}</math>
 
: <math>C_{21} = M_{1} - M_{2} + M_{3} + M_{6}</math>
 
: <math>C_{22} = M_{2} - M_{6}            .\square</math>
 
 
'''New algorithm for a symmetric matrix:'''
 
 
For a symmetric matrix <math>A \in \mathbb{C}^{n \times n}</math> where <math>n \in \mathbb{N}^*</math> the runtime <math>T_p(n)</math> of the new algorithm is for the matrix product <math>A^2</math> by computing analogously as above about <math>3/7</math> that of the original algorithm in <math>\mathcal{O}(n^{(_2 7)}).\square</math>
 
 
'''New algorithm for a square matrix:'''
 
 
For a square matrix <math>A \in \mathbb{C}^{n \times n}</math> where <math>n \in \mathbb{N}^*</math> the runtime <math>T_r(n)</math> of the new algorithm is for the matrix product <math>A^TA</math> about <math>24/49</math> that of  the original algorithm in <math>\mathcal{O}(n^{(_2 7)}).\square</math>
 
  
 
== See also ==
 
== See also ==

Revision as of 06:48, 22 March 2022

Strassen algorithm for a symmetric matrix:

For a symmetric matrix [math]\displaystyle{ A \in \mathbb{C}^{n \times n} }[/math] where [math]\displaystyle{ n \in \mathbb{N}^* }[/math], the runtime [math]\displaystyle{ T_s(n) }[/math] of the Strassen algorithm for the matrix product [math]\displaystyle{ A^2 }[/math] is about half that of the original algorithm in [math]\displaystyle{ \mathcal{O}(n^{(_2 7)}) }[/math].

Proof: For [math]\displaystyle{ A := \begin{pmatrix} A_{11} & A_{12} \\ A_{12} & A_{22} \end{pmatrix} }[/math], it holds that [math]\displaystyle{ A^TA = \begin{pmatrix} A_{11}^TA_{11}+A_{12}^TA_{12} & A_{11}^TA_{12}+A_{12}^TA_{22} \\ A_{12}^TA_{11}+A_{22}^TA_{12} & A_{12}^TA_{12}+A_{22}^TA_{22} \end{pmatrix} }[/math] and [math]\displaystyle{ T_s(2n) = 3T_s(n) + 2n^{(_2 7)} }[/math]. Thus [math]\displaystyle{ T_s(n) = 3T_s(n/2) + 2(n/2)^{(_2 7)} }[/math] and [math]\displaystyle{ T_s(n/2) = 3T_s(n/4) + 2(n/4)^{(_2 7)} }[/math].

The geometric series yields because of [math]\displaystyle{ T_s(1) = 1 }[/math]: [math]\displaystyle{ T_s(n) = 27T_s(n/8) + 2/7n^{(_2 7)}(1+3/7 + (3/7)^2 + ...) = 3^{(_2n)} + 2/7n^{(_2 7)} (1-(3/7)^{(_2n)})/(1-3/7) }[/math] [math]\displaystyle{ = n^{(_2 3)} + \hat{2}(n^{(_2 7)}-n^{(_2 3)}) = \hat{2} (n^{(_2 3)} + n^{(_2 7)}) }[/math].[math]\displaystyle{ \square }[/math]

Strassen algorithm for a square matrix:

For a square matrix [math]\displaystyle{ A \in \mathbb{C}^{n \times n} }[/math] where [math]\displaystyle{ n \in \mathbb{N}^* }[/math], the runtime [math]\displaystyle{ T_q(n) }[/math] of the Strassen algorithm is for the matrix product [math]\displaystyle{ A^TA }[/math] about [math]\displaystyle{ 4/7 }[/math] that of the original algorithm in [math]\displaystyle{ \mathcal{O}(n^{(_2 7)}) }[/math].

Proof: For [math]\displaystyle{ A := \begin{pmatrix} A_{11} & A_{12} \\ A_{21} & A_{22} \end{pmatrix} }[/math], it holds that [math]\displaystyle{ A^TA = \begin{pmatrix} A_{11}^TA_{11}+A_{21}^TA_{21} & A_{11}^TA_{12}+A_{21}^TA_{22} \\ A_{12}^TA_{11}+A_{22}^TA_{21} & A_{12}^TA_{12}+A_{22}^TA_{22} \end{pmatrix} }[/math] such that [math]\displaystyle{ T_q(2n) = 4T_s(n) + 2n^{(_2 7)} }[/math] and [math]\displaystyle{ T_q(n) = 4T_s(n/2) + 2/7n^{(_2 7)} = 2/3n^{(_2 3)} + 4/7n^{(_2 7)} }[/math].[math]\displaystyle{ \square }[/math]

See also

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