Description of fast matrix multiplication algorithm: ⟨7×12×13:724⟩

Algorithm type

25X4Y4Z4+8X4Y4Z3+3X4Y3Z4+5X3Y4Z4+2X4Y3Z3+2X4Y2Z4+7X3Y4Z3+X2Y6Z2+X2Y4Z4+X5Y2Z2+X3Y3Z3+2X2Y4Z3+3X4Y2Z2+32X3Y3Z2+27X2Y4Z2+32X2Y3Z3+7X2Y2Z4+2X4Y2Z+2X4YZ2+48X3Y3Z+2X3Y2Z2+4X2Y4Z+2X2Y3Z2+4X2Y2Z3+3XY4Z2+48XY3Z3+X3YZ2+X2Y3Z+143X2Y2Z2+XY4Z+XY2Z3+X3YZ+2X2Y2Z+3X2YZ2+2XY3Z+5XY2Z2+47X2YZ+137XY2Z+12XYZ2+94XYZ25X4Y4Z48X4Y4Z33X4Y3Z45X3Y4Z42X4Y3Z32X4Y2Z47X3Y4Z3X2Y6Z2X2Y4Z4X5Y2Z2X3Y3Z32X2Y4Z33X4Y2Z232X3Y3Z227X2Y4Z232X2Y3Z37X2Y2Z42X4Y2Z2X4YZ248X3Y3Z2X3Y2Z24X2Y4Z2X2Y3Z24X2Y2Z33XY4Z248XY3Z3X3YZ2X2Y3Z143X2Y2Z2XY4ZXY2Z3X3YZ2X2Y2Z3X2YZ22XY3Z5XY2Z247X2YZ137XY2Z12XYZ294XYZ25*X^4*Y^4*Z^4+8*X^4*Y^4*Z^3+3*X^4*Y^3*Z^4+5*X^3*Y^4*Z^4+2*X^4*Y^3*Z^3+2*X^4*Y^2*Z^4+7*X^3*Y^4*Z^3+X^2*Y^6*Z^2+X^2*Y^4*Z^4+X^5*Y^2*Z^2+X^3*Y^3*Z^3+2*X^2*Y^4*Z^3+3*X^4*Y^2*Z^2+32*X^3*Y^3*Z^2+27*X^2*Y^4*Z^2+32*X^2*Y^3*Z^3+7*X^2*Y^2*Z^4+2*X^4*Y^2*Z+2*X^4*Y*Z^2+48*X^3*Y^3*Z+2*X^3*Y^2*Z^2+4*X^2*Y^4*Z+2*X^2*Y^3*Z^2+4*X^2*Y^2*Z^3+3*X*Y^4*Z^2+48*X*Y^3*Z^3+X^3*Y*Z^2+X^2*Y^3*Z+143*X^2*Y^2*Z^2+X*Y^4*Z+X*Y^2*Z^3+X^3*Y*Z+2*X^2*Y^2*Z+3*X^2*Y*Z^2+2*X*Y^3*Z+5*X*Y^2*Z^2+47*X^2*Y*Z+137*X*Y^2*Z+12*X*Y*Z^2+94*X*Y*Z

Algorithm definition

The algorithm ⟨7×12×13:724⟩ could be constructed using the following decomposition:

⟨7×12×13:724⟩ = ⟨4×6×7:123⟩ + ⟨3×6×6:80⟩ + ⟨4×6×7:123⟩ + ⟨3×6×7:94⟩ + ⟨3×6×7:94⟩ + ⟨4×6×6:105⟩ + ⟨4×6×6:105⟩.

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_1_10A_1_11A_1_12A_2_1A_2_2A_2_3A_2_4A_2_5A_2_6A_2_7A_2_8A_2_9A_2_10A_2_11A_2_12A_3_1A_3_2A_3_3A_3_4A_3_5A_3_6A_3_7A_3_8A_3_9A_3_10A_3_11A_3_12A_4_1A_4_2A_4_3A_4_4A_4_5A_4_6A_4_7A_4_8A_4_9A_4_10A_4_11A_4_12A_5_1A_5_2A_5_3A_5_4A_5_5A_5_6A_5_7A_5_8A_5_9A_5_10A_5_11A_5_12A_6_1A_6_2A_6_3A_6_4A_6_5A_6_6A_6_7A_6_8A_6_9A_6_10A_6_11A_6_12A_7_1A_7_2A_7_3A_7_4A_7_5A_7_6A_7_7A_7_8A_7_9A_7_10A_7_11A_7_12B_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_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_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_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_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_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_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_8_1B_8_2B_8_3B_8_4B_8_5B_8_6B_8_7B_8_8B_8_9B_8_10B_8_11B_8_12B_8_13B_9_1B_9_2B_9_3B_9_4B_9_5B_9_6B_9_7B_9_8B_9_9B_9_10B_9_11B_9_12B_9_13B_10_1B_10_2B_10_3B_10_4B_10_5B_10_6B_10_7B_10_8B_10_9B_10_10B_10_11B_10_12B_10_13B_11_1B_11_2B_11_3B_11_4B_11_5B_11_6B_11_7B_11_8B_11_9B_11_10B_11_11B_11_12B_11_13B_12_1B_12_2B_12_3B_12_4B_12_5B_12_6B_12_7B_12_8B_12_9B_12_10B_12_11B_12_12B_12_13C_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_7=TraceMulA_1_6+A_2_7A_1_1+A_2_4A_1_2+A_2_5A_1_3+A_2_10A_1_8+A_2_11A_1_9+A_2_12A_5_7A_5_4A_5_5A_5_10A_5_11A_5_12A_3_6+A_6_7A_3_1+A_6_4A_3_2+A_6_5A_3_3+A_6_10A_3_8+A_6_11A_3_9+A_6_12A_4_6+A_7_7A_4_1+A_7_4A_4_2+A_7_5A_4_3+A_7_10A_4_8+A_7_11A_4_9+A_7_12B_7_1B_6_7+B_7_8B_6_2+B_7_5B_6_3+B_7_6B_6_4+B_7_11B_6_9+B_7_12B_6_10+B_7_13B_4_1B_1_7+B_4_8B_1_2+B_4_5B_1_3+B_4_6B_1_4+B_4_11B_1_9+B_4_12B_1_10+B_4_13B_5_1B_2_7+B_5_8B_2_2+B_5_5B_2_3+B_5_6B_2_4+B_5_11B_2_9+B_5_12B_2_10+B_5_13B_10_1B_3_7+B_10_8B_3_2+B_10_5B_3_3+B_10_6B_3_4+B_10_11B_3_9+B_10_12B_3_10+B_10_13B_11_1B_8_7+B_11_8B_8_2+B_11_5B_8_3+B_11_6B_8_4+B_11_11B_8_9+B_11_12B_8_10+B_11_13B_12_1B_9_7+B_12_8B_9_2+B_12_5B_9_3+B_12_6B_9_4+B_12_11B_9_9+B_12_12B_9_10+B_12_13C_1_2C_1_5C_1_6C_1_7C_7_1+C_8_2C_8_5C_7_3+C_8_6C_7_4+C_8_7C_2_1+C_5_2C_5_5C_2_3+C_5_6C_2_4+C_5_7C_3_1+C_6_2C_6_5C_3_3+C_6_6C_3_4+C_6_7C_4_1+C_11_2C_11_5C_4_3+C_11_6C_4_4+C_11_7C_9_1+C_12_2C_12_5C_9_3+C_12_6C_9_4+C_12_7C_10_1+C_13_2C_13_5C_10_3+C_13_6C_10_4+C_13_7+TraceMulA_1_7-A_2_7A_1_4-A_2_4A_1_5-A_2_5A_1_10-A_2_10A_1_11-A_2_11A_1_12-A_2_12A_3_7-A_6_7A_3_4-A_6_4A_3_5-A_6_5A_3_10-A_6_10A_3_11-A_6_11A_3_12-A_6_12A_4_7-A_7_7A_4_4-A_7_4A_4_5-A_7_5A_4_10-A_7_10A_4_11-A_7_11A_4_12-A_7_12B_7_7+B_7_8B_7_2+B_7_5B_7_3+B_7_6B_7_4+B_7_11B_7_9+B_7_12B_7_10+B_7_13B_4_7+B_4_8B_4_2+B_4_5B_4_3+B_4_6B_4_4+B_4_11B_4_9+B_4_12B_4_10+B_4_13B_5_7+B_5_8B_5_2+B_5_5B_5_3+B_5_6B_5_4+B_5_11B_5_9+B_5_12B_5_10+B_5_13B_10_7+B_10_8B_10_2+B_10_5B_10_3+B_10_6B_10_4+B_10_11B_10_9+B_10_12B_10_10+B_10_13B_11_7+B_11_8B_11_2+B_11_5B_11_3+B_11_6B_11_4+B_11_11B_11_9+B_11_12B_11_10+B_11_13B_12_7+B_12_8B_12_2+B_12_5B_12_3+B_12_6B_12_4+B_12_11B_12_9+B_12_12B_12_10+B_12_13C_7_1C_7_3C_7_4C_2_1C_2_3C_2_4C_3_1C_3_3C_3_4C_4_1C_4_3C_4_4C_9_1C_9_3C_9_4C_10_1C_10_3C_10_4+TraceMul-A_1_6+A_2_6A_2_1-A_1_1-A_1_2+A_2_2A_2_3-A_1_3-A_1_8+A_2_8-A_1_9+A_2_9A_5_6A_5_1A_5_2A_5_3A_5_8A_5_9-A_3_6+A_6_6-A_3_1+A_6_1-A_3_2+A_6_2-A_3_3+A_6_3-A_3_8+A_6_8-A_3_9+A_6_9-A_4_6+A_7_6-A_4_1+A_7_1-A_4_2+A_7_2-A_4_3+A_7_3-A_4_8+A_7_8-A_4_9+A_7_9B_6_1B_6_7+B_6_8B_6_2+B_6_5B_6_3+B_6_6B_6_4+B_6_11B_6_9+B_6_12B_6_10+B_6_13B_1_1B_1_7+B_1_8B_1_2+B_1_5B_1_3+B_1_6B_1_4+B_1_11B_1_9+B_1_12B_1_10+B_1_13B_2_1B_2_7+B_2_8B_2_2+B_2_5B_2_3+B_2_6B_2_4+B_2_11B_2_9+B_2_12B_2_10+B_2_13B_3_1B_3_7+B_3_8B_3_2+B_3_5B_3_3+B_3_6B_3_4+B_3_11B_3_9+B_3_12B_3_10+B_3_13B_8_1B_8_7+B_8_8B_8_2+B_8_5B_8_3+B_8_6B_8_4+B_8_11B_8_9+B_8_12B_8_10+B_8_13B_9_1B_9_7+B_9_8B_9_2+B_9_5B_9_3+B_9_6B_9_4+B_9_11B_9_9+B_9_12B_9_10+B_9_13C_1_2C_1_5C_1_6C_1_7C_8_2C_8_5C_8_6C_8_7C_5_2C_5_5C_5_6C_5_7C_6_2C_6_5C_6_6C_6_7C_11_2C_11_5C_11_6C_11_7C_12_2C_12_5C_12_6C_12_7C_13_2C_13_5C_13_6C_13_7+TraceMulA_1_6+A_1_7A_1_1+A_1_4A_1_2+A_1_5A_1_3+A_1_10A_1_8+A_1_11A_1_9+A_1_12A_3_6+A_3_7A_3_1+A_3_4A_3_2+A_3_5A_3_3+A_3_10A_3_8+A_3_11A_3_9+A_3_12A_4_6+A_4_7A_4_1+A_4_4A_4_2+A_4_5A_4_3+A_4_10A_4_8+A_4_11A_4_9+A_4_12B_7_1B_7_8B_7_5B_7_6B_7_11B_7_12B_7_13B_4_1B_4_8B_4_5B_4_6B_4_11B_4_12B_4_13B_5_1B_5_8B_5_5B_5_6B_5_11B_5_12B_5_13B_10_1B_10_8B_10_5B_10_6B_10_11B_10_12B_10_13B_11_1B_11_8B_11_5B_11_6B_11_11B_11_12B_11_13B_12_1B_12_8B_12_5B_12_6B_12_11B_12_12B_12_13C_1_1C_1_3C_1_4-C_7_1+C_8_1C_8_3-C_7_3C_8_4-C_7_4-C_2_1+C_5_1-C_2_3+C_5_3-C_2_4+C_5_4-C_3_1+C_6_1-C_3_3+C_6_3-C_3_4+C_6_4-C_4_1+C_11_1-C_4_3+C_11_3-C_4_4+C_11_4-C_9_1+C_12_1-C_9_3+C_12_3-C_9_4+C_12_4-C_10_1+C_13_1-C_10_3+C_13_3-C_10_4+C_13_4+TraceMulA_1_6A_1_1A_1_2A_1_3A_1_8A_1_9A_3_6A_3_1A_3_2A_3_3A_3_8A_3_9A_4_6A_4_1A_4_2A_4_3A_4_8A_4_9B_6_1-B_7_1B_6_8-B_7_8B_6_5-B_7_5B_6_6-B_7_6B_6_11-B_7_11B_6_12-B_7_12B_6_13-B_7_13B_1_1-B_4_1B_1_8-B_4_8B_1_5-B_4_5B_1_6-B_4_6B_1_11-B_4_11B_1_12-B_4_12B_1_13-B_4_13B_2_1-B_5_1B_2_8-B_5_8B_2_5-B_5_5B_2_6-B_5_6B_2_11-B_5_11B_2_12-B_5_12B_2_13-B_5_13B_3_1-B_10_1B_3_8-B_10_8B_3_5-B_10_5B_3_6-B_10_6B_3_11-B_10_11B_3_12-B_10_12B_3_13-B_10_13B_8_1-B_11_1B_8_8-B_11_8B_8_5-B_11_5B_8_6-B_11_6B_8_11-B_11_11B_8_12-B_11_12B_8_13-B_11_13B_9_1-B_12_1B_9_8-B_12_8B_9_5-B_12_5B_9_6-B_12_6B_9_11-B_12_11B_9_12-B_12_12B_9_13-B_12_13C_1_1+C_1_2C_1_3+C_1_6C_1_4+C_1_7C_8_1+C_8_2C_8_3+C_8_6C_8_4+C_8_7C_5_1+C_5_2C_5_3+C_5_6C_5_4+C_5_7C_6_1+C_6_2C_6_3+C_6_6C_6_4+C_6_7C_11_1+C_11_2C_11_3+C_11_6C_11_4+C_11_7C_12_1+C_12_2C_12_3+C_12_6C_12_4+C_12_7C_13_1+C_13_2C_13_3+C_13_6C_13_4+C_13_7+TraceMulA_2_7A_2_4A_2_5A_2_10A_2_11A_2_12A_5_7A_5_4A_5_5A_5_10A_5_11A_5_12A_6_7A_6_4A_6_5A_6_10A_6_11A_6_12A_7_7A_7_4A_7_5A_7_10A_7_11A_7_12-B_6_7+B_7_7-B_6_2+B_7_2-B_6_3+B_7_3-B_6_4+B_7_4-B_6_9+B_7_9-B_6_10+B_7_10-B_1_7+B_4_7B_4_2-B_1_2-B_1_3+B_4_3-B_1_4+B_4_4-B_1_9+B_4_9-B_1_10+B_4_10-B_2_7+B_5_7-B_2_2+B_5_2-B_2_3+B_5_3-B_2_4+B_5_4-B_2_9+B_5_9-B_2_10+B_5_10-B_3_7+B_10_7-B_3_2+B_10_2-B_3_3+B_10_3-B_3_4+B_10_4-B_3_9+B_10_9-B_3_10+B_10_10-B_8_7+B_11_7-B_8_2+B_11_2-B_8_3+B_11_3-B_8_4+B_11_4-B_8_9+B_11_9-B_8_10+B_11_10-B_9_7+B_12_7-B_9_2+B_12_2-B_9_3+B_12_3-B_9_4+B_12_4-B_9_9+B_12_9-B_9_10+B_12_10C_7_1+C_7_2C_7_5C_7_3+C_7_6C_7_4+C_7_7C_2_1+C_2_2C_2_5C_2_3+C_2_6C_2_4+C_2_7C_3_1+C_3_2C_3_5C_3_3+C_3_6C_3_4+C_3_7C_4_1+C_4_2C_4_5C_4_3+C_4_6C_4_4+C_4_7C_9_1+C_9_2C_9_5C_9_3+C_9_6C_9_4+C_9_7C_10_1+C_10_2C_10_5C_10_3+C_10_6C_10_4+C_10_7+TraceMulA_2_6+A_2_7A_2_1+A_2_4A_2_2+A_2_5A_2_3+A_2_10A_2_8+A_2_11A_2_9+A_2_12A_5_6+A_5_7A_5_1+A_5_4A_5_2+A_5_5A_5_3+A_5_10A_5_8+A_5_11A_5_9+A_5_12A_6_6+A_6_7A_6_1+A_6_4A_6_2+A_6_5A_6_3+A_6_10A_6_8+A_6_11A_6_9+A_6_12A_7_6+A_7_7A_7_1+A_7_4A_7_2+A_7_5A_7_3+A_7_10A_7_8+A_7_11A_7_9+A_7_12B_6_7B_6_2B_6_3B_6_4B_6_9B_6_10B_1_7B_1_2B_1_3B_1_4B_1_9B_1_10B_2_7B_2_2B_2_3B_2_4B_2_9B_2_10B_3_7B_3_2B_3_3B_3_4B_3_9B_3_10B_8_7B_8_2B_8_3B_8_4B_8_9B_8_10B_9_7B_9_2B_9_3B_9_4B_9_9B_9_10C_7_2-C_8_2C_7_5-C_8_5C_7_6-C_8_6C_7_7-C_8_7C_2_2-C_5_2C_2_5-C_5_5C_2_6-C_5_6C_2_7-C_5_7C_3_2-C_6_2C_3_5-C_6_5C_3_6-C_6_6C_3_7-C_6_7C_4_2-C_11_2C_4_5-C_11_5C_4_6-C_11_6C_4_7-C_11_7C_9_2-C_12_2C_9_5-C_12_5C_9_6-C_12_6C_9_7-C_12_7C_10_2-C_13_2C_10_5-C_13_5C_10_6-C_13_6C_10_7-C_13_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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