Description of fast matrix multiplication algorithm: ⟨5×8×9:260⟩

Algorithm type

2X4Y4Z4+X4Y4Z3+2X4Y3Z3+6X3Y4Z3+X2Y6Z2+X2Y4Z4+2X3Y3Z3+X2Y5Z2+4X2Y2Z5+3X5Y2Z+X3Y4Z+19X2Y4Z2+X2Y3Z3+X3Y2Z2+2X2Y3Z2+3X2Y2Z3+X3YZ2+X2Y3Z+42X2Y2Z2+X2YZ3+18XY4Z+2XY2Z3+10X3YZ+6X2Y2Z+8XY3Z+7XY2Z2+10XYZ3+5X2YZ+38XY2Z+8XYZ2+53XYZ2X4Y4Z4X4Y4Z32X4Y3Z36X3Y4Z3X2Y6Z2X2Y4Z42X3Y3Z3X2Y5Z24X2Y2Z53X5Y2ZX3Y4Z19X2Y4Z2X2Y3Z3X3Y2Z22X2Y3Z23X2Y2Z3X3YZ2X2Y3Z42X2Y2Z2X2YZ318XY4Z2XY2Z310X3YZ6X2Y2Z8XY3Z7XY2Z210XYZ35X2YZ38XY2Z8XYZ253XYZ2*X^4*Y^4*Z^4+X^4*Y^4*Z^3+2*X^4*Y^3*Z^3+6*X^3*Y^4*Z^3+X^2*Y^6*Z^2+X^2*Y^4*Z^4+2*X^3*Y^3*Z^3+X^2*Y^5*Z^2+4*X^2*Y^2*Z^5+3*X^5*Y^2*Z+X^3*Y^4*Z+19*X^2*Y^4*Z^2+X^2*Y^3*Z^3+X^3*Y^2*Z^2+2*X^2*Y^3*Z^2+3*X^2*Y^2*Z^3+X^3*Y*Z^2+X^2*Y^3*Z+42*X^2*Y^2*Z^2+X^2*Y*Z^3+18*X*Y^4*Z+2*X*Y^2*Z^3+10*X^3*Y*Z+6*X^2*Y^2*Z+8*X*Y^3*Z+7*X*Y^2*Z^2+10*X*Y*Z^3+5*X^2*Y*Z+38*X*Y^2*Z+8*X*Y*Z^2+53*X*Y*Z

Algorithm definition

The algorithm ⟨5×8×9:260⟩ could be constructed using the following decomposition:

⟨5×8×9:260⟩ = ⟨3×4×5:47⟩ + ⟨2×4×4:26⟩ + ⟨3×4×5:47⟩ + ⟨2×4×5:32⟩ + ⟨2×4×5:32⟩ + ⟨3×4×4:38⟩ + ⟨3×4×4:38⟩.

This decomposition is defined by the following equality:

TraceMulA_1_1A_1_2A_1_3A_1_4A_1_5A_1_6A_1_7A_1_8A_2_1A_2_2A_2_3A_2_4A_2_5A_2_6A_2_7A_2_8A_3_1A_3_2A_3_3A_3_4A_3_5A_3_6A_3_7A_3_8A_4_1A_4_2A_4_3A_4_4A_4_5A_4_6A_4_7A_4_8A_5_1A_5_2A_5_3A_5_4A_5_5A_5_6A_5_7A_5_8B_1_1B_1_2B_1_3B_1_4B_1_5B_1_6B_1_7B_1_8B_1_9B_2_1B_2_2B_2_3B_2_4B_2_5B_2_6B_2_7B_2_8B_2_9B_3_1B_3_2B_3_3B_3_4B_3_5B_3_6B_3_7B_3_8B_3_9B_4_1B_4_2B_4_3B_4_4B_4_5B_4_6B_4_7B_4_8B_4_9B_5_1B_5_2B_5_3B_5_4B_5_5B_5_6B_5_7B_5_8B_5_9B_6_1B_6_2B_6_3B_6_4B_6_5B_6_6B_6_7B_6_8B_6_9B_7_1B_7_2B_7_3B_7_4B_7_5B_7_6B_7_7B_7_8B_7_9B_8_1B_8_2B_8_3B_8_4B_8_5B_8_6B_8_7B_8_8B_8_9C_1_1C_1_2C_1_3C_1_4C_1_5C_2_1C_2_2C_2_3C_2_4C_2_5C_3_1C_3_2C_3_3C_3_4C_3_5C_4_1C_4_2C_4_3C_4_4C_4_5C_5_1C_5_2C_5_3C_5_4C_5_5C_6_1C_6_2C_6_3C_6_4C_6_5C_7_1C_7_2C_7_3C_7_4C_7_5C_8_1C_8_2C_8_3C_8_4C_8_5C_9_1C_9_2C_9_3C_9_4C_9_5=TraceMulA_1_4+A_2_5A_1_1+A_2_3A_1_2+A_2_7A_1_6+A_2_8A_4_5A_4_3A_4_7A_4_8A_3_4+A_5_5A_3_1+A_5_3A_3_2+A_5_7A_3_6+A_5_8B_5_1B_4_5+B_5_6B_4_2+B_5_4B_4_3+B_5_8B_4_7+B_5_9B_3_1B_1_5+B_3_6B_1_2+B_3_4B_1_3+B_3_8B_1_7+B_3_9B_7_1B_2_5+B_7_6B_2_2+B_7_4B_2_3+B_7_8B_2_7+B_7_9B_8_1B_6_5+B_8_6B_6_2+B_8_4B_6_3+B_8_8B_6_7+B_8_9C_1_2C_1_4C_1_5C_5_1+C_6_2C_6_4C_5_3+C_6_5C_2_1+C_4_2C_4_4C_2_3+C_4_5C_3_1+C_8_2C_8_4C_3_3+C_8_5C_7_1+C_9_2C_9_4C_7_3+C_9_5+TraceMulA_1_5-A_2_5A_1_3-A_2_3A_1_7-A_2_7A_1_8-A_2_8A_3_5-A_5_5A_3_3-A_5_3A_3_7-A_5_7A_3_8-A_5_8B_5_5+B_5_6B_5_4+B_5_2B_5_3+B_5_8B_5_7+B_5_9B_3_5+B_3_6B_3_2+B_3_4B_3_3+B_3_8B_3_7+B_3_9B_7_5+B_7_6B_7_2+B_7_4B_7_3+B_7_8B_7_7+B_7_9B_8_5+B_8_6B_8_2+B_8_4B_8_3+B_8_8B_8_7+B_8_9C_5_1C_5_3C_2_1C_2_3C_3_1C_3_3C_7_1C_7_3+TraceMul-A_1_4+A_2_4A_2_1-A_1_1-A_1_2+A_2_2-A_1_6+A_2_6A_4_4A_4_1A_4_2A_4_6-A_3_4+A_5_4-A_3_1+A_5_1-A_3_2+A_5_2-A_3_6+A_5_6B_4_1B_4_5+B_4_6B_4_2+B_4_4B_4_3+B_4_8B_4_7+B_4_9B_1_1B_1_5+B_1_6B_1_2+B_1_4B_1_3+B_1_8B_1_7+B_1_9B_2_1B_2_5+B_2_6B_2_2+B_2_4B_2_3+B_2_8B_2_7+B_2_9B_6_1B_6_5+B_6_6B_6_2+B_6_4B_6_3+B_6_8B_6_7+B_6_9C_1_2C_1_4C_1_5C_6_2C_6_4C_6_5C_4_2C_4_4C_4_5C_8_2C_8_4C_8_5C_9_2C_9_4C_9_5+TraceMulA_1_4+A_1_5A_1_1+A_1_3A_1_2+A_1_7A_1_6+A_1_8A_3_4+A_3_5A_3_1+A_3_3A_3_2+A_3_7A_3_6+A_3_8B_5_1B_5_6B_5_4B_5_8B_5_9B_3_1B_3_6B_3_4B_3_8B_3_9B_7_1B_7_6B_7_4B_7_8B_7_9B_8_1B_8_6B_8_4B_8_8B_8_9C_1_1C_1_3-C_5_1+C_6_1-C_5_3+C_6_3-C_2_1+C_4_1-C_2_3+C_4_3-C_3_1+C_8_1-C_3_3+C_8_3-C_7_1+C_9_1-C_7_3+C_9_3+TraceMulA_1_4A_1_1A_1_2A_1_6A_3_4A_3_1A_3_2A_3_6B_4_1-B_5_1B_4_6-B_5_6B_4_4-B_5_4B_4_8-B_5_8B_4_9-B_5_9B_1_1-B_3_1-B_3_6+B_1_6B_1_4-B_3_4-B_3_8+B_1_8B_1_9-B_3_9B_2_1-B_7_1B_2_6-B_7_6B_2_4-B_7_4B_2_8-B_7_8B_2_9-B_7_9B_6_1-B_8_1B_6_6-B_8_6B_6_4-B_8_4B_6_8-B_8_8B_6_9-B_8_9C_1_1+C_1_2C_1_3+C_1_5C_6_1+C_6_2C_6_3+C_6_5C_4_1+C_4_2C_4_3+C_4_5C_8_1+C_8_2C_8_3+C_8_5C_9_1+C_9_2C_9_3+C_9_5+TraceMulA_2_5A_2_3A_2_7A_2_8A_4_5A_4_3A_4_7A_4_8A_5_5A_5_3A_5_7A_5_8-B_4_5+B_5_5-B_4_2+B_5_2B_5_3-B_4_3-B_4_7+B_5_7-B_1_5+B_3_5-B_1_2+B_3_2-B_1_3+B_3_3-B_1_7+B_3_7-B_2_5+B_7_5-B_2_2+B_7_2-B_2_3+B_7_3-B_2_7+B_7_7-B_6_5+B_8_5-B_6_2+B_8_2-B_6_3+B_8_3-B_6_7+B_8_7C_5_1+C_5_2C_5_4C_5_3+C_5_5C_2_1+C_2_2C_2_4C_2_3+C_2_5C_3_1+C_3_2C_3_4C_3_3+C_3_5C_7_1+C_7_2C_7_4C_7_3+C_7_5+TraceMulA_2_4+A_2_5A_2_1+A_2_3A_2_2+A_2_7A_2_6+A_2_8A_4_5+A_4_4A_4_1+A_4_3A_4_2+A_4_7A_4_6+A_4_8A_5_5+A_5_4A_5_1+A_5_3A_5_2+A_5_7A_5_6+A_5_8B_4_5B_4_2B_4_3B_4_7B_1_5B_1_2B_1_3B_1_7B_2_5B_2_2B_2_3B_2_7B_6_5B_6_2B_6_3B_6_7C_5_2-C_6_2C_5_4-C_6_4C_5_5-C_6_5-C_4_2+C_2_2C_2_4-C_4_4C_2_5-C_4_5C_3_2-C_8_2C_3_4-C_8_4C_3_5-C_8_5C_7_2-C_9_2C_7_4-C_9_4C_7_5-C_9_5

N.B.: for any matrices A, B and C such that the expression Tr(Mul(A,B,C)) is defined, one can construct several trilinear homogeneous polynomials P(A,B,C) such that P(A,B,C)=Tr(Mul(A,B,C)) (P(A,B,C) variables are A,B and C's coefficients). Each trilinear P expression encodes a matrix multiplication algorithm: the coefficient in C_i_j of P(A,B,C) is the (i,j)-th entry of the matrix product Mul(A,B)=Transpose(C).

Algorithm description

These encodings are given in compressed text format using the maple computer algebra system. In each cases, the last line could be understood as a description of the encoding with respect to classical matrix multiplication algorithm. As these outputs are structured, one can construct easily a parser to its favorite format using the maple documentation without this software.


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