Description of fast matrix multiplication algorithm: ⟨4×9×11:280⟩

Algorithm type

8X4Y4Z4+4X4Y3Z3+6X2Y6Z2+4X2Y5Z2+2X2Y5Z+18X2Y4Z2+10XY6Z+4X2Y3Z2+6XY5Z+52X2Y2Z2+12XY4Z+4X2YZ2+16XY3Z+2X2YZ+66XY2Z+66XYZ8X4Y4Z44X4Y3Z36X2Y6Z24X2Y5Z22X2Y5Z18X2Y4Z210XY6Z4X2Y3Z26XY5Z52X2Y2Z212XY4Z4X2YZ216XY3Z2X2YZ66XY2Z66XYZ8*X^4*Y^4*Z^4+4*X^4*Y^3*Z^3+6*X^2*Y^6*Z^2+4*X^2*Y^5*Z^2+2*X^2*Y^5*Z+18*X^2*Y^4*Z^2+10*X*Y^6*Z+4*X^2*Y^3*Z^2+6*X*Y^5*Z+52*X^2*Y^2*Z^2+12*X*Y^4*Z+4*X^2*Y*Z^2+16*X*Y^3*Z+2*X^2*Y*Z+66*X*Y^2*Z+66*X*Y*Z

Algorithm definition

The algorithm ⟨4×9×11:280⟩ could be constructed using the following decomposition:

⟨4×9×11:280⟩ = ⟨2×3×3:15⟩ + ⟨2×3×4:20⟩ + ⟨2×3×4:20⟩ + ⟨2×3×4:20⟩ + ⟨2×3×4:20⟩ + ⟨2×3×4:20⟩ + ⟨2×3×3:15⟩ + ⟨2×3×4:20⟩ + ⟨2×3×3:15⟩ + ⟨2×3×4:20⟩ + ⟨2×3×4:20⟩ + ⟨2×3×4:20⟩ + ⟨2×3×4:20⟩ + ⟨2×3×4:20⟩ + ⟨2×3×3:15⟩.

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_1_9A_2_1A_2_2A_2_3A_2_4A_2_5A_2_6A_2_7A_2_8A_2_9A_3_1A_3_2A_3_3A_3_4A_3_5A_3_6A_3_7A_3_8A_3_9A_4_1A_4_2A_4_3A_4_4A_4_5A_4_6A_4_7A_4_8A_4_9B_1_1B_1_2B_1_3B_1_4B_1_5B_1_6B_1_7B_1_8B_1_9B_1_10B_1_11B_2_1B_2_2B_2_3B_2_4B_2_5B_2_6B_2_7B_2_8B_2_9B_2_10B_2_11B_3_1B_3_2B_3_3B_3_4B_3_5B_3_6B_3_7B_3_8B_3_9B_3_10B_3_11B_4_1B_4_2B_4_3B_4_4B_4_5B_4_6B_4_7B_4_8B_4_9B_4_10B_4_11B_5_1B_5_2B_5_3B_5_4B_5_5B_5_6B_5_7B_5_8B_5_9B_5_10B_5_11B_6_1B_6_2B_6_3B_6_4B_6_5B_6_6B_6_7B_6_8B_6_9B_6_10B_6_11B_7_1B_7_2B_7_3B_7_4B_7_5B_7_6B_7_7B_7_8B_7_9B_7_10B_7_11B_8_1B_8_2B_8_3B_8_4B_8_5B_8_6B_8_7B_8_8B_8_9B_8_10B_8_11B_9_1B_9_2B_9_3B_9_4B_9_5B_9_6B_9_7B_9_8B_9_9B_9_10B_9_11C_1_1C_1_2C_1_3C_1_4C_2_1C_2_2C_2_3C_2_4C_3_1C_3_2C_3_3C_3_4C_4_1C_4_2C_4_3C_4_4C_5_1C_5_2C_5_3C_5_4C_6_1C_6_2C_6_3C_6_4C_7_1C_7_2C_7_3C_7_4C_8_1C_8_2C_8_3C_8_4C_9_1C_9_2C_9_3C_9_4C_10_1C_10_2C_10_3C_10_4C_11_1C_11_2C_11_3C_11_4=TraceMulA_1_1A_1_2A_1_3A_2_1A_2_2A_2_3B_1_1-B_4_1-B_1_9B_1_2-B_4_2-B_1_10B_1_3-B_4_3-B_1_11B_2_1-B_5_1-B_2_9B_2_2-B_5_2-B_2_10B_2_3-B_5_3-B_2_11-B_6_1+B_3_1-B_3_9B_3_2-B_6_2-B_3_10B_3_3-B_6_3-B_3_11C_1_1+C_1_3C_1_2+C_1_4C_2_1+C_2_3C_2_2+C_2_4C_3_1+C_3_3C_3_2+C_3_4+TraceMulA_3_4A_3_5A_3_6A_4_4A_4_5A_4_6-B_1_4+B_4_4-B_4_8-B_1_5+B_4_5-B_4_9-B_1_6+B_4_6-B_4_10-B_1_7+B_4_7-B_4_11-B_2_4+B_5_4-B_5_8-B_2_5+B_5_5-B_5_9-B_2_6+B_5_6-B_5_10-B_2_7+B_5_7-B_5_11-B_3_4+B_6_4-B_6_8-B_3_5+B_6_5-B_6_9-B_3_6+B_6_6-B_6_10-B_3_7+B_6_7-B_6_11C_4_1+C_4_3C_4_2+C_4_4C_5_1+C_5_3C_5_4+C_5_2C_6_1+C_6_3C_6_2+C_6_4C_7_1+C_7_3C_7_2+C_7_4+TraceMulA_3_7A_3_8A_3_9A_4_7A_4_8A_4_9-B_7_4-B_1_8+B_7_8-B_7_5-B_1_9+B_7_9-B_7_6-B_1_10+B_7_10-B_7_7-B_1_11+B_7_11-B_8_4-B_2_8+B_8_8-B_8_5-B_2_9+B_8_9-B_8_6-B_2_10+B_8_10-B_8_7-B_2_11+B_8_11-B_9_4-B_3_8+B_9_8-B_9_5-B_3_9+B_9_9-B_9_6-B_3_10+B_9_10-B_9_7-B_3_11+B_9_11C_8_3C_8_4C_9_3C_9_4C_10_3C_10_4C_11_3C_11_4+TraceMulA_1_7A_1_8A_1_9A_2_7A_2_8A_2_9-B_4_8+B_7_8-B_7_1-B_4_9+B_7_9-B_7_2-B_4_10+B_7_10-B_7_3-B_4_11+B_7_11-B_5_8+B_8_8-B_8_1-B_5_9+B_8_9-B_8_2-B_5_10+B_8_10-B_8_3-B_5_11+B_8_11-B_6_8+B_9_8-B_9_1-B_6_9+B_9_9-B_9_2-B_6_10+B_9_10-B_9_3-B_6_11+B_9_11C_8_1C_8_2C_9_1C_9_2C_10_1C_10_2C_11_1C_11_2+TraceMulA_3_1+A_3_4A_3_2+A_3_5A_3_3+A_3_6A_4_1+A_4_4A_4_2+A_4_5A_4_3+A_4_6B_1_4B_1_5B_1_6B_1_7B_2_4B_2_5B_2_6B_2_7B_3_4B_3_5B_3_6B_3_7C_4_3C_4_4C_1_3+C_5_3C_1_4+C_5_4C_2_3+C_6_3C_2_4+C_6_4C_3_3+C_7_3C_3_4+C_7_4+TraceMulA_3_1+A_3_7A_3_2+A_3_8A_3_3+A_3_9A_4_1+A_4_7A_4_2+A_4_8A_4_3+A_4_9B_1_8B_1_9B_1_10B_1_11B_2_8B_2_9B_2_10B_2_11B_3_8B_3_9B_3_10B_3_11C_8_1+C_8_3C_8_2+C_8_4C_1_3+C_9_3+C_1_1+C_9_1C_1_4+C_9_4+C_1_2+C_9_2C_2_3+C_10_3+C_2_1+C_10_1C_2_4+C_10_4+C_2_2+C_10_2C_3_3+C_11_3+C_3_1+C_11_1C_3_4+C_11_4+C_3_2+C_11_2+TraceMul-A_1_1+A_3_1-A_1_2+A_3_2-A_1_3+A_3_3-A_2_1+A_4_1-A_2_2+A_4_2A_4_3-A_2_3B_1_1-B_7_1-B_1_5B_1_2-B_7_2-B_1_6B_1_3-B_7_3-B_1_7B_2_1-B_8_1-B_2_5B_2_2-B_8_2-B_2_6B_2_3-B_8_3-B_2_7B_3_1-B_9_1-B_3_5B_3_2-B_9_2-B_3_6B_3_3-B_9_3-B_3_7C_1_3C_1_4C_2_3C_2_4C_3_3C_3_4+TraceMulA_1_1+A_3_4A_1_2+A_3_5A_1_3+A_3_6A_2_1+A_4_4A_2_2+A_4_5A_2_3+A_4_6-B_1_4B_4_1-B_1_5B_4_2-B_1_6B_4_3-B_1_7-B_2_4B_5_1-B_2_5B_5_2-B_2_6B_5_3-B_2_7-B_3_4B_6_1-B_3_5B_6_2-B_3_6B_6_3-B_3_7-C_4_1-C_4_2C_1_3-C_5_1C_1_4-C_5_2C_2_3-C_6_1C_2_4-C_6_2C_3_3-C_7_1C_3_4-C_7_2+TraceMulA_1_1+A_1_4A_1_2+A_1_5A_1_3+A_1_6A_2_1+A_2_4A_2_2+A_2_5A_2_3+A_2_6B_4_1B_4_2B_4_3B_5_1B_5_2B_5_3B_6_1B_6_2B_6_3C_1_1+C_5_1C_1_2+C_5_2C_2_1+C_6_1C_2_2+C_6_2C_3_1+C_7_1C_3_2+C_7_2+TraceMul-A_1_4+A_3_4-A_1_5+A_3_5-A_1_6+A_3_6-A_2_4+A_4_4A_4_5-A_2_5-A_2_6+A_4_6-B_4_4+B_7_4B_4_1-B_4_5+B_7_5B_4_2-B_4_6+B_7_6B_4_3-B_4_7+B_7_7-B_5_4+B_8_4B_5_1-B_5_5+B_8_5B_5_2-B_5_6+B_8_6B_5_3-B_5_7+B_8_7-B_6_4+B_9_4B_6_1-B_6_5+B_9_5B_6_2-B_6_6+B_9_6B_6_3-B_6_7+B_9_7C_4_1C_4_2C_5_1C_5_2C_6_1C_6_2C_7_1C_7_2+TraceMulA_1_4+A_1_7A_1_5+A_1_8A_1_6+A_1_9A_2_4+A_2_7A_2_5+A_2_8A_2_6+A_2_9B_4_8B_4_9B_4_10B_4_11B_5_8B_5_9B_5_10B_5_11B_6_8B_6_9B_6_10B_6_11C_4_3+C_8_3+C_4_1+C_8_1C_4_4+C_8_4+C_4_2+C_8_2C_5_3+C_9_3+C_5_1+C_9_1C_5_4+C_9_4+C_5_2+C_9_2C_6_3+C_10_3+C_6_1+C_10_1C_6_4+C_10_4+C_6_2+C_10_2C_7_3+C_11_3+C_7_1+C_11_1C_11_4+C_7_4+C_7_2+C_11_2+TraceMul-A_1_1+A_3_1+A_3_7-A_1_2+A_3_2+A_3_8-A_1_3+A_3_3+A_3_9-A_2_1+A_4_1+A_4_7-A_2_2+A_4_2+A_4_8A_4_3-A_2_3+A_4_9-B_1_8B_7_1-B_1_9B_7_2-B_1_10B_7_3-B_1_11-B_2_8B_8_1-B_2_9B_8_2-B_2_10B_8_3-B_2_11-B_3_8B_9_1-B_3_9B_9_2-B_3_10B_9_3-B_3_11C_8_1C_8_2C_1_1+C_1_3+C_9_1C_1_2+C_1_4+C_9_2C_2_1+C_2_3+C_10_1C_2_2+C_2_4+C_10_2C_3_1+C_3_3+C_11_1C_3_2+C_3_4+C_11_2+TraceMul-A_1_4+A_3_4-A_1_7-A_1_5+A_3_5-A_1_8-A_1_6+A_3_6-A_1_9-A_2_4+A_4_4-A_2_7A_4_5-A_2_5-A_2_8-A_2_6+A_4_6-A_2_9-B_7_4+B_4_8-B_7_5+B_4_9-B_7_6+B_4_10-B_7_7+B_4_11-B_8_4+B_5_8-B_8_5+B_5_9-B_8_6+B_5_10-B_8_7+B_5_11-B_9_4+B_6_8-B_9_5+B_6_9-B_9_6+B_6_10-B_9_7+B_6_11C_4_3+C_8_3+C_4_1C_4_4+C_8_4+C_4_2C_5_3+C_9_3+C_5_1C_5_4+C_9_4+C_5_2C_6_3+C_10_3+C_6_1C_6_4+C_10_4+C_6_2C_7_3+C_11_3+C_7_1C_11_4+C_7_4+C_7_2+TraceMul-A_1_4+A_3_4+A_3_7-A_1_7-A_1_5+A_3_5+A_3_8-A_1_8-A_1_6+A_3_6+A_3_9-A_1_9-A_2_4+A_4_4+A_4_7-A_2_7A_4_5-A_2_5+A_4_8-A_2_8-A_2_6+A_4_6+A_4_9-A_2_9B_7_4B_7_5B_7_6B_7_7B_8_4B_8_5B_8_6B_8_7B_9_4B_9_5B_9_6B_9_7C_4_3+C_8_3C_4_4+C_8_4C_5_3+C_9_3C_5_4+C_9_4C_6_3+C_10_3C_6_4+C_10_4C_7_3+C_11_3C_11_4+C_7_4+TraceMulA_1_1-A_3_1-A_3_7+A_1_7A_1_2-A_3_2-A_3_8+A_1_8A_1_3-A_3_3-A_3_9+A_1_9A_2_1-A_4_1-A_4_7+A_2_7A_2_2-A_4_2-A_4_8+A_2_8A_2_3-A_4_3-A_4_9+A_2_9B_7_1B_7_2B_7_3B_8_1B_8_2B_8_3B_9_1B_9_2B_9_3C_1_1+C_9_1C_1_2+C_9_2C_2_1+C_10_1C_2_2+C_10_2C_3_1+C_11_1C_3_2+C_11_2

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.


Back to main table