strassen matrix multiplication algorithm

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it explains matrix multiplication. its algorithm and analysis

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strassen matrix multiplication algorithm

  1. 1. Strassen's Matrix Multiplication Presented by: Ali Mamoon 07-0014
  2. 2. Contents  Matrix multiplication  Divide and Conquer  Strassen's idea  Analysis
  3. 3. Standard algorithm for i ←1 to n do for j←1 to n do cij←0 for k←1 to n do cij←cij+ aik⋅bkj N C i, j a i ,k bk , j k 1 N N N 3 3 Thus T ( N ) c cN O(N ) i1 j1k 1
  4. 4. Divide-and-Conquer  Divide-and conquer is a general algorithm design paradigm:  Divide: divide the input data S in two or more disjoint subsets S1, S2, …  Recur: solve the sub problems recursively  Conquer: combine the solutions for S1, S2, …, into a solution for S  The base case for the recursion are sub problems of constant size  Analysis can be done using recurrence equations
  5. 5. Matrix Multiplication through Divide and Conquer Approach
  6. 6. Divide-and-conquer algorithm
  7. 7. Master theorem
  8. 8. Strassen’s idea  Multiply 2×2matrices with only 7 recursive multiplications.  P1= a⋅(f–h) r=P5+ P4–P2+ P6 P2= (a+ b) ⋅h  s=P1+ P2 P3= (c+ d) ⋅e  t=P3+ P4  P4= d⋅(g–e) u=P5+ P1–P3–P7 P5= (a+ d) ⋅(e+ h)  P6= (b–d) ⋅(g+ h)  P7= (a–c) ⋅(e+ f )   Note:  7mults, 18adds/subs.  Note: No reliance on commutative of multiplication!
  9. 9. Strassen Algorithm void matmul(int *A, int *B, int *R, int n) { if (n == 1) { (*R) += (*A) * (*B); } else { matmul(A, B, R, n/4); matmul(A, B+(n/4), R+(n/4), n/4); matmul(A+2*(n/4), B, R+2*(n/4), n/4); matmul(A+2*(n/4), B+(n/4), R+3*(n/4), n/4); matmul(A+(n/4), B+2*(n/4), R, n/4); matmul(A+(n/4), B+3*(n/4), R+(n/4), n/4); matmul(A+3*(n/4), B+2*(n/4), R+2*(n/4), n/4); matmul(A+3*(n/4), B+3*(n/4), R+3*(n/4), n/4); Divide matrices in } sub-matrices and recursively multiply sub-matrices
  10. 10. Analysis of Strassen's  T(n) = 7T(n/2) + Θ(n2)  nlogba= nlog27≈n2.81  ⇒CASE1⇒T(n) = Θ(nlg7).  The number2.81may not seem much smaller than 3, but because the difference is in the exponent, the impact on running time is significant. In fact, Strassen’s algorithm beats the ordinary algorithm on today’s machines for n≥32or so.  Best to date (of theoretical interest only): Θ(n2.376…)

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