Description of fast matrix multiplication algorithm: ⟨7×7×19:643⟩

Algorithm type

2X5Y7Z6+X5Y7Z5+X4Y7Z5+13X4Y4Z4+X4Y4Z3+6X3Y4Z4+3X2Y7Z2+2X4Y3Z3+7X3Y4Z3+4X3Y3Z4+X2Y4Z4+XY7Z2+2X3Y3Z3+16X2Y3Z3+6X2Y3Z2+6X2Y2Z3+24XY3Z3+183X2Y2Z2+6XY4Z+2XYZ4+9X3YZ+12X2Y2Z+12X2YZ2+20XY3Z+11XY2Z2+20XYZ3+25X2YZ+60XY2Z+61XYZ2+126XYZ2X5Y7Z6X5Y7Z5X4Y7Z513X4Y4Z4X4Y4Z36X3Y4Z43X2Y7Z22X4Y3Z37X3Y4Z34X3Y3Z4X2Y4Z4XY7Z22X3Y3Z316X2Y3Z36X2Y3Z26X2Y2Z324XY3Z3183X2Y2Z26XY4Z2XYZ49X3YZ12X2Y2Z12X2YZ220XY3Z11XY2Z220XYZ325X2YZ60XY2Z61XYZ2126XYZ2*X^5*Y^7*Z^6+X^5*Y^7*Z^5+X^4*Y^7*Z^5+13*X^4*Y^4*Z^4+X^4*Y^4*Z^3+6*X^3*Y^4*Z^4+3*X^2*Y^7*Z^2+2*X^4*Y^3*Z^3+7*X^3*Y^4*Z^3+4*X^3*Y^3*Z^4+X^2*Y^4*Z^4+X*Y^7*Z^2+2*X^3*Y^3*Z^3+16*X^2*Y^3*Z^3+6*X^2*Y^3*Z^2+6*X^2*Y^2*Z^3+24*X*Y^3*Z^3+183*X^2*Y^2*Z^2+6*X*Y^4*Z+2*X*Y*Z^4+9*X^3*Y*Z+12*X^2*Y^2*Z+12*X^2*Y*Z^2+20*X*Y^3*Z+11*X*Y^2*Z^2+20*X*Y*Z^3+25*X^2*Y*Z+60*X*Y^2*Z+61*X*Y*Z^2+126*X*Y*Z

Algorithm definition

The algorithm ⟨7×7×19:643⟩ could be constructed using the following decomposition:

⟨7×7×19:643⟩ = ⟨4×4×10:120⟩ + ⟨3×4×9:83⟩ + ⟨4×3×10:92⟩ + ⟨3×4×10:92⟩ + ⟨3×3×10:69⟩ + ⟨4×4×9:104⟩ + ⟨4×3×9:83⟩.

This decomposition is defined by the following equality:

TraceMulA_1_1A_1_2A_1_3A_1_4A_1_5A_1_6A_1_7A_2_1A_2_2A_2_3A_2_4A_2_5A_2_6A_2_7A_3_1A_3_2A_3_3A_3_4A_3_5A_3_6A_3_7A_4_1A_4_2A_4_3A_4_4A_4_5A_4_6A_4_7A_5_1A_5_2A_5_3A_5_4A_5_5A_5_6A_5_7A_6_1A_6_2A_6_3A_6_4A_6_5A_6_6A_6_7A_7_1A_7_2A_7_3A_7_4A_7_5A_7_6A_7_7B_1_1B_1_2B_1_3B_1_4B_1_5B_1_6B_1_7B_1_8B_1_9B_1_10B_1_11B_1_12B_1_13B_1_14B_1_15B_1_16B_1_17B_1_18B_1_19B_2_1B_2_2B_2_3B_2_4B_2_5B_2_6B_2_7B_2_8B_2_9B_2_10B_2_11B_2_12B_2_13B_2_14B_2_15B_2_16B_2_17B_2_18B_2_19B_3_1B_3_2B_3_3B_3_4B_3_5B_3_6B_3_7B_3_8B_3_9B_3_10B_3_11B_3_12B_3_13B_3_14B_3_15B_3_16B_3_17B_3_18B_3_19B_4_1B_4_2B_4_3B_4_4B_4_5B_4_6B_4_7B_4_8B_4_9B_4_10B_4_11B_4_12B_4_13B_4_14B_4_15B_4_16B_4_17B_4_18B_4_19B_5_1B_5_2B_5_3B_5_4B_5_5B_5_6B_5_7B_5_8B_5_9B_5_10B_5_11B_5_12B_5_13B_5_14B_5_15B_5_16B_5_17B_5_18B_5_19B_6_1B_6_2B_6_3B_6_4B_6_5B_6_6B_6_7B_6_8B_6_9B_6_10B_6_11B_6_12B_6_13B_6_14B_6_15B_6_16B_6_17B_6_18B_6_19B_7_1B_7_2B_7_3B_7_4B_7_5B_7_6B_7_7B_7_8B_7_9B_7_10B_7_11B_7_12B_7_13B_7_14B_7_15B_7_16B_7_17B_7_18B_7_19C_1_1C_1_2C_1_3C_1_4C_1_5C_1_6C_1_7C_2_1C_2_2C_2_3C_2_4C_2_5C_2_6C_2_7C_3_1C_3_2C_3_3C_3_4C_3_5C_3_6C_3_7C_4_1C_4_2C_4_3C_4_4C_4_5C_4_6C_4_7C_5_1C_5_2C_5_3C_5_4C_5_5C_5_6C_5_7C_6_1C_6_2C_6_3C_6_4C_6_5C_6_6C_6_7C_7_1C_7_2C_7_3C_7_4C_7_5C_7_6C_7_7C_8_1C_8_2C_8_3C_8_4C_8_5C_8_6C_8_7C_9_1C_9_2C_9_3C_9_4C_9_5C_9_6C_9_7C_10_1C_10_2C_10_3C_10_4C_10_5C_10_6C_10_7C_11_1C_11_2C_11_3C_11_4C_11_5C_11_6C_11_7C_12_1C_12_2C_12_3C_12_4C_12_5C_12_6C_12_7C_13_1C_13_2C_13_3C_13_4C_13_5C_13_6C_13_7C_14_1C_14_2C_14_3C_14_4C_14_5C_14_6C_14_7C_15_1C_15_2C_15_3C_15_4C_15_5C_15_6C_15_7C_16_1C_16_2C_16_3C_16_4C_16_5C_16_6C_16_7C_17_1C_17_2C_17_3C_17_4C_17_5C_17_6C_17_7C_18_1C_18_2C_18_3C_18_4C_18_5C_18_6C_18_7C_19_1C_19_2C_19_3C_19_4C_19_5C_19_6C_19_7=TraceMulA_4_4A_4_5A_4_6A_4_7A_5_4A_1_1+A_5_5A_1_2+A_5_6A_1_3+A_5_7A_6_4A_2_1+A_6_5A_2_2+A_6_6A_2_3+A_6_7A_7_4A_3_1+A_7_5A_3_2+A_7_6A_3_3+A_7_7B_4_10B_4_11B_4_12B_4_13B_4_14B_4_15B_4_16B_4_17B_4_18B_4_19B_5_10B_1_1+B_5_11B_1_2+B_5_12B_1_3+B_5_13B_1_4+B_5_14B_1_5+B_5_15B_1_6+B_5_16B_1_7+B_5_17B_1_8+B_5_18B_1_9+B_5_19B_6_10B_2_1+B_6_11B_2_2+B_6_12B_2_3+B_6_13B_2_4+B_6_14B_2_5+B_6_15B_2_6+B_6_16B_2_7+B_6_17B_2_8+B_6_18B_2_9+B_6_19B_7_10B_3_1+B_7_11B_3_2+B_7_12B_3_3+B_7_13B_3_4+B_7_14B_3_5+B_7_15B_3_6+B_7_16B_3_7+B_7_17B_3_8+B_7_18B_3_9+B_7_19C_10_4C_10_5C_10_6C_10_7C_11_4C_1_1+C_11_5C_1_2+C_11_6C_1_3+C_11_7C_12_4C_2_1+C_12_5C_2_2+C_12_6C_2_3+C_12_7C_13_4C_3_1+C_13_5C_3_2+C_13_6C_3_3+C_13_7C_14_4C_4_1+C_14_5C_4_2+C_14_6C_4_3+C_14_7C_15_4C_5_1+C_15_5C_5_2+C_15_6C_5_3+C_15_7C_16_4C_6_1+C_16_5C_6_2+C_16_6C_6_3+C_16_7C_17_4C_7_1+C_17_5C_7_2+C_17_6C_7_3+C_17_7C_18_4C_8_1+C_18_5C_8_2+C_18_6C_8_3+C_18_7C_19_4C_9_1+C_19_5C_9_2+C_19_6C_9_3+C_19_7+TraceMulA_1_4-A_5_4A_1_5-A_5_5A_1_6-A_5_6A_1_7-A_5_7A_2_4-A_6_4A_2_5-A_6_5A_2_6-A_6_6A_2_7-A_6_7A_3_4-A_7_4A_3_5-A_7_5A_3_6-A_7_6A_3_7-A_7_7B_4_1+B_4_11B_4_2+B_4_12B_4_3+B_4_13B_4_4+B_4_14B_4_5+B_4_15B_4_6+B_4_16B_4_7+B_4_17B_4_8+B_4_18B_4_9+B_4_19B_5_1+B_5_11B_5_2+B_5_12B_5_3+B_5_13B_5_4+B_5_14B_5_5+B_5_15B_5_6+B_5_16B_5_7+B_5_17B_5_8+B_5_18B_5_9+B_5_19B_6_1+B_6_11B_6_2+B_6_12B_6_3+B_6_13B_6_4+B_6_14B_6_5+B_6_15B_6_6+B_6_16B_6_7+B_6_17B_6_8+B_6_18B_6_9+B_6_19B_7_1+B_7_11B_7_2+B_7_12B_7_3+B_7_13B_7_4+B_7_14B_7_5+B_7_15B_7_6+B_7_16B_7_7+B_7_17B_7_8+B_7_18B_7_9+B_7_19C_1_1C_1_2C_1_3C_2_1C_2_2C_2_3C_3_1C_3_2C_3_3C_4_1C_4_2C_4_3C_5_1C_5_2C_5_3C_6_1C_6_2C_6_3C_7_1C_7_2C_7_3C_8_1C_8_2C_8_3C_9_1C_9_2C_9_3+TraceMulA_4_1A_4_2A_4_3-A_1_1+A_5_1-A_1_2+A_5_2-A_1_3+A_5_3-A_2_1+A_6_1-A_2_2+A_6_2-A_2_3+A_6_3-A_3_1+A_7_1-A_3_2+A_7_2-A_3_3+A_7_3B_1_10B_1_1+B_1_11B_1_2+B_1_12B_1_3+B_1_13B_1_4+B_1_14B_1_5+B_1_15B_1_6+B_1_16B_1_7+B_1_17B_1_8+B_1_18B_1_9+B_1_19B_2_10B_2_1+B_2_11B_2_2+B_2_12B_2_3+B_2_13B_2_4+B_2_14B_2_5+B_2_15B_2_6+B_2_16B_2_7+B_2_17B_2_8+B_2_18B_2_9+B_2_19B_3_10B_3_1+B_3_11B_3_2+B_3_12B_3_3+B_3_13B_3_4+B_3_14B_3_5+B_3_15B_3_6+B_3_16B_3_7+B_3_17B_3_8+B_3_18B_3_9+B_3_19C_10_4C_10_5C_10_6C_10_7C_11_4C_11_5C_11_6C_11_7C_12_4C_12_5C_12_6C_12_7C_13_4C_13_5C_13_6C_13_7C_14_4C_14_5C_14_6C_14_7C_15_4C_15_5C_15_6C_15_7C_16_4C_16_5C_16_6C_16_7C_17_4C_17_5C_17_6C_17_7C_18_4C_18_5C_18_6C_18_7C_19_4C_19_5C_19_6C_19_7+TraceMulA_1_4A_1_1+A_1_5A_1_2+A_1_6A_1_3+A_1_7A_2_4A_2_1+A_2_5A_2_2+A_2_6A_2_3+A_2_7A_3_4A_3_1+A_3_5A_3_2+A_3_6A_3_3+A_3_7B_4_10B_4_11B_4_12B_4_13B_4_14B_4_15B_4_16B_4_17B_4_18B_4_19B_5_10B_5_11B_5_12B_5_13B_5_14B_5_15B_5_16B_5_17B_5_18B_5_19B_6_10B_6_11B_6_12B_6_13B_6_14B_6_15B_6_16B_6_17B_6_18B_6_19B_7_10B_7_11B_7_12B_7_13B_7_14B_7_15B_7_16B_7_17B_7_18B_7_19C_10_1C_10_2C_10_3-C_1_1+C_11_1-C_1_2+C_11_2-C_1_3+C_11_3-C_2_1+C_12_1-C_2_2+C_12_2-C_2_3+C_12_3-C_3_1+C_13_1-C_3_2+C_13_2-C_3_3+C_13_3-C_4_1+C_14_1-C_4_2+C_14_2-C_4_3+C_14_3-C_5_1+C_15_1-C_5_2+C_15_2-C_5_3+C_15_3-C_6_1+C_16_1-C_6_2+C_16_2-C_6_3+C_16_3-C_7_1+C_17_1-C_7_2+C_17_2-C_7_3+C_17_3-C_8_1+C_18_1-C_8_2+C_18_2-C_8_3+C_18_3-C_9_1+C_19_1-C_9_2+C_19_2-C_9_3+C_19_3+TraceMulA_1_1A_1_2A_1_3A_2_1A_2_2A_2_3A_3_1A_3_2A_3_3B_1_10-B_5_10B_1_11-B_5_11B_1_12-B_5_12B_1_13-B_5_13B_1_14-B_5_14B_1_15-B_5_15B_1_16-B_5_16B_1_17-B_5_17B_1_18-B_5_18B_1_19-B_5_19B_2_10-B_6_10B_2_11-B_6_11B_2_12-B_6_12B_2_13-B_6_13B_2_14-B_6_14B_2_15-B_6_15B_2_16-B_6_16B_2_17-B_6_17B_2_18-B_6_18B_2_19-B_6_19B_3_10-B_7_10B_3_11-B_7_11B_3_12-B_7_12B_3_13-B_7_13B_3_14-B_7_14B_3_15-B_7_15B_3_16-B_7_16B_3_17-B_7_17B_3_18-B_7_18B_3_19-B_7_19C_10_1+C_10_5C_10_2+C_10_6C_10_3+C_10_7C_11_1+C_11_5C_11_2+C_11_6C_11_3+C_11_7C_12_1+C_12_5C_12_2+C_12_6C_12_3+C_12_7C_13_1+C_13_5C_13_2+C_13_6C_13_3+C_13_7C_14_1+C_14_5C_14_2+C_14_6C_14_3+C_14_7C_15_1+C_15_5C_15_2+C_15_6C_15_3+C_15_7C_16_1+C_16_5C_16_2+C_16_6C_16_3+C_16_7C_17_1+C_17_5C_17_2+C_17_6C_17_3+C_17_7C_18_1+C_18_5C_18_2+C_18_6C_18_3+C_18_7C_19_1+C_19_5C_19_2+C_19_6C_19_3+C_19_7+TraceMulA_4_4A_4_5A_4_6A_4_7A_5_4A_5_5A_5_6A_5_7A_6_4A_6_5A_6_6A_6_7A_7_4A_7_5A_7_6A_7_7B_4_1B_4_2B_4_3B_4_4B_4_5B_4_6B_4_7B_4_8B_4_9-B_1_1+B_5_1-B_1_2+B_5_2B_5_3-B_1_3-B_1_4+B_5_4-B_1_5+B_5_5-B_1_6+B_5_6-B_1_7+B_5_7-B_1_8+B_5_8-B_1_9+B_5_9-B_2_1+B_6_1-B_2_2+B_6_2-B_2_3+B_6_3B_6_4-B_2_4-B_2_5+B_6_5-B_2_6+B_6_6-B_2_7+B_6_7-B_2_8+B_6_8-B_2_9+B_6_9-B_3_1+B_7_1-B_3_2+B_7_2-B_3_3+B_7_3B_7_4-B_3_4-B_3_5+B_7_5-B_3_6+B_7_6-B_3_7+B_7_7-B_3_8+B_7_8-B_3_9+B_7_9C_1_4C_1_1+C_1_5C_1_2+C_1_6C_1_3+C_1_7C_2_4C_2_1+C_2_5C_2_2+C_2_6C_2_3+C_2_7C_3_4C_3_1+C_3_5C_3_2+C_3_6C_3_3+C_3_7C_4_4C_4_1+C_4_5C_4_2+C_4_6C_4_3+C_4_7C_5_4C_5_1+C_5_5C_5_2+C_5_6C_5_3+C_5_7C_6_4C_6_1+C_6_5C_6_2+C_6_6C_6_3+C_6_7C_7_4C_7_1+C_7_5C_7_2+C_7_6C_7_3+C_7_7C_8_4C_8_1+C_8_5C_8_2+C_8_6C_8_3+C_8_7C_9_4C_9_1+C_9_5C_9_2+C_9_6C_9_3+C_9_7+TraceMulA_4_1+A_4_5A_4_2+A_4_6A_4_3+A_4_7A_5_1+A_5_5A_5_2+A_5_6A_5_3+A_5_7A_6_1+A_6_5A_6_2+A_6_6A_6_3+A_6_7A_7_1+A_7_5A_7_2+A_7_6A_7_3+A_7_7B_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_9C_1_4-C_11_4C_1_5-C_11_5C_1_6-C_11_6C_1_7-C_11_7C_2_4-C_12_4C_2_5-C_12_5C_2_6-C_12_6C_2_7-C_12_7C_3_4-C_13_4C_3_5-C_13_5C_3_6-C_13_6C_3_7-C_13_7C_4_4-C_14_4C_4_5-C_14_5C_4_6-C_14_6C_4_7-C_14_7C_5_4-C_15_4C_5_5-C_15_5C_5_6-C_15_6C_5_7-C_15_7C_6_4-C_16_4C_6_5-C_16_5C_6_6-C_16_6C_6_7-C_16_7C_7_4-C_17_4C_7_5-C_17_5C_7_6-C_17_6C_7_7-C_17_7C_8_4-C_18_4C_8_5-C_18_5C_8_6-C_18_6C_8_7-C_18_7C_9_4-C_19_4C_9_5-C_19_5C_9_6-C_19_6C_9_7-C_19_7

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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