Description of fast matrix multiplication algorithm: ⟨3×13×14:416⟩

Algorithm type

16⁢X3⁢Y3⁢Z2+64⁢X2⁢Y3⁢Z3+24⁢X3⁢Y3⁢Z+2⁢X2⁢Y3⁢Z2+96⁢X⁢Y3⁢Z3+2⁢X3⁢Y2⁢Z+58⁢X2⁢Y2⁢Z2+4⁢X⁢Y4⁢Z+2⁢X⁢Y2⁢Z3+12⁢X3⁢Y⁢Z+6⁢X2⁢Y2⁢Z+4⁢X⁢Y3⁢Z+4⁢X⁢Y2⁢Z2+11⁢X⁢Y⁢Z3+12⁢X2⁢Y⁢Z+36⁢X⁢Y2⁢Z+16⁢X⁢Y⁢Z2+47⁢X⁢Y⁢Z16X3Y3Z264X2Y3Z324X3Y3Z2X2Y3Z296XY3Z32X3Y2Z58X2Y2Z24XY4Z2XY2Z312X3YZ6X2Y2Z4XY3Z4XY2Z211XYZ312X2YZ36XY2Z16XYZ247XYZ16*X^3*Y^3*Z^2+64*X^2*Y^3*Z^3+24*X^3*Y^3*Z+2*X^2*Y^3*Z^2+96*X*Y^3*Z^3+2*X^3*Y^2*Z+58*X^2*Y^2*Z^2+4*X*Y^4*Z+2*X*Y^2*Z^3+12*X^3*Y*Z+6*X^2*Y^2*Z+4*X*Y^3*Z+4*X*Y^2*Z^2+11*X*Y*Z^3+12*X^2*Y*Z+36*X*Y^2*Z+16*X*Y*Z^2+47*X*Y*Z

Algorithm definition

The algorithm ⟨3×13×14:416⟩ could be constructed using the following decomposition:

⟨3×13×14:416⟩ = ⟨3×13×6:176⟩ + ⟨3×13×8:240⟩.

This decomposition is defined by the following equality:

Trace⁡Mul⁡A_1_1A_1_2A_1_3A_1_4A_1_5A_1_6A_1_7A_1_8A_1_9A_1_10A_1_11A_1_12A_1_13A_2_1A_2_2A_2_3A_2_4A_2_5A_2_6A_2_7A_2_8A_2_9A_2_10A_2_11A_2_12A_2_13A_3_1A_3_2A_3_3A_3_4A_3_5A_3_6A_3_7A_3_8A_3_9A_3_10A_3_11A_3_12A_3_13B_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_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_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_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_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_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_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_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_8_14B_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_9_14B_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_10_14B_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_11_14B_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_13B_12_14B_13_1B_13_2B_13_3B_13_4B_13_5B_13_6B_13_7B_13_8B_13_9B_13_10B_13_11B_13_12B_13_13B_13_14C_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_3C_10_1C_10_2C_10_3C_11_1C_11_2C_11_3C_12_1C_12_2C_12_3C_13_1C_13_2C_13_3C_14_1C_14_2C_14_3=Trace⁡Mul⁡A_1_1A_1_2A_1_3A_1_4A_1_5A_1_6A_1_7A_1_8A_1_9A_1_10A_1_11A_1_12A_1_13A_2_1A_2_2A_2_3A_2_4A_2_5A_2_6A_2_7A_2_8A_2_9A_2_10A_2_11A_2_12A_2_13A_3_1A_3_2A_3_3A_3_4A_3_5A_3_6A_3_7A_3_8A_3_9A_3_10A_3_11A_3_12A_3_13B_1_1B_1_2B_1_3B_1_4B_1_5B_1_6B_2_1B_2_2B_2_3B_2_4B_2_5B_2_6B_3_1B_3_2B_3_3B_3_4B_3_5B_3_6B_4_1B_4_2B_4_3B_4_4B_4_5B_4_6B_5_1B_5_2B_5_3B_5_4B_5_5B_5_6B_6_1B_6_2B_6_3B_6_4B_6_5B_6_6B_7_1B_7_2B_7_3B_7_4B_7_5B_7_6B_8_1B_8_2B_8_3B_8_4B_8_5B_8_6B_9_1B_9_2B_9_3B_9_4B_9_5B_9_6B_10_1B_10_2B_10_3B_10_4B_10_5B_10_6B_11_1B_11_2B_11_3B_11_4B_11_5B_11_6B_12_1B_12_2B_12_3B_12_4B_12_5B_12_6B_13_1B_13_2B_13_3B_13_4B_13_5B_13_6C_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_3+Trace⁡Mul⁡A_1_1A_1_2A_1_3A_1_4A_1_5A_1_6A_1_7A_1_8A_1_9A_1_10A_1_11A_1_12A_1_13A_2_1A_2_2A_2_3A_2_4A_2_5A_2_6A_2_7A_2_8A_2_9A_2_10A_2_11A_2_12A_2_13A_3_1A_3_2A_3_3A_3_4A_3_5A_3_6A_3_7A_3_8A_3_9A_3_10A_3_11A_3_12A_3_13B_1_7B_1_8B_1_9B_1_10B_1_11B_1_12B_1_13B_1_14B_2_7B_2_8B_2_9B_2_10B_2_11B_2_12B_2_13B_2_14B_3_7B_3_8B_3_9B_3_10B_3_11B_3_12B_3_13B_3_14B_4_7B_4_8B_4_9B_4_10B_4_11B_4_12B_4_13B_4_14B_5_7B_5_8B_5_9B_5_10B_5_11B_5_12B_5_13B_5_14B_6_7B_6_8B_6_9B_6_10B_6_11B_6_12B_6_13B_6_14B_7_7B_7_8B_7_9B_7_10B_7_11B_7_12B_7_13B_7_14B_8_7B_8_8B_8_9B_8_10B_8_11B_8_12B_8_13B_8_14B_9_7B_9_8B_9_9B_9_10B_9_11B_9_12B_9_13B_9_14B_10_7B_10_8B_10_9B_10_10B_10_11B_10_12B_10_13B_10_14B_11_7B_11_8B_11_9B_11_10B_11_11B_11_12B_11_13B_11_14B_12_7B_12_8B_12_9B_12_10B_12_11B_12_12B_12_13B_12_14B_13_7B_13_8B_13_9B_13_10B_13_11B_13_12B_13_13B_13_14C_7_1C_7_2C_7_3C_8_1C_8_2C_8_3C_9_1C_9_2C_9_3C_10_1C_10_2C_10_3C_11_1C_11_2C_11_3C_12_1C_12_2C_12_3C_13_1C_13_2C_13_3C_14_1C_14_2C_14_3TraceMulA_1_1A_1_2A_1_3A_1_4A_1_5A_1_6A_1_7A_1_8A_1_9A_1_10A_1_11A_1_12A_1_13A_2_1A_2_2A_2_3A_2_4A_2_5A_2_6A_2_7A_2_8A_2_9A_2_10A_2_11A_2_12A_2_13A_3_1A_3_2A_3_3A_3_4A_3_5A_3_6A_3_7A_3_8A_3_9A_3_10A_3_11A_3_12A_3_13B_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_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_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_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_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_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_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_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_8_14B_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_9_14B_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_10_14B_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_11_14B_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_13B_12_14B_13_1B_13_2B_13_3B_13_4B_13_5B_13_6B_13_7B_13_8B_13_9B_13_10B_13_11B_13_12B_13_13B_13_14C_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_3C_10_1C_10_2C_10_3C_11_1C_11_2C_11_3C_12_1C_12_2C_12_3C_13_1C_13_2C_13_3C_14_1C_14_2C_14_3TraceMulA_1_1A_1_2A_1_3A_1_4A_1_5A_1_6A_1_7A_1_8A_1_9A_1_10A_1_11A_1_12A_1_13A_2_1A_2_2A_2_3A_2_4A_2_5A_2_6A_2_7A_2_8A_2_9A_2_10A_2_11A_2_12A_2_13A_3_1A_3_2A_3_3A_3_4A_3_5A_3_6A_3_7A_3_8A_3_9A_3_10A_3_11A_3_12A_3_13B_1_1B_1_2B_1_3B_1_4B_1_5B_1_6B_2_1B_2_2B_2_3B_2_4B_2_5B_2_6B_3_1B_3_2B_3_3B_3_4B_3_5B_3_6B_4_1B_4_2B_4_3B_4_4B_4_5B_4_6B_5_1B_5_2B_5_3B_5_4B_5_5B_5_6B_6_1B_6_2B_6_3B_6_4B_6_5B_6_6B_7_1B_7_2B_7_3B_7_4B_7_5B_7_6B_8_1B_8_2B_8_3B_8_4B_8_5B_8_6B_9_1B_9_2B_9_3B_9_4B_9_5B_9_6B_10_1B_10_2B_10_3B_10_4B_10_5B_10_6B_11_1B_11_2B_11_3B_11_4B_11_5B_11_6B_12_1B_12_2B_12_3B_12_4B_12_5B_12_6B_13_1B_13_2B_13_3B_13_4B_13_5B_13_6C_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_3TraceMulA_1_1A_1_2A_1_3A_1_4A_1_5A_1_6A_1_7A_1_8A_1_9A_1_10A_1_11A_1_12A_1_13A_2_1A_2_2A_2_3A_2_4A_2_5A_2_6A_2_7A_2_8A_2_9A_2_10A_2_11A_2_12A_2_13A_3_1A_3_2A_3_3A_3_4A_3_5A_3_6A_3_7A_3_8A_3_9A_3_10A_3_11A_3_12A_3_13B_1_7B_1_8B_1_9B_1_10B_1_11B_1_12B_1_13B_1_14B_2_7B_2_8B_2_9B_2_10B_2_11B_2_12B_2_13B_2_14B_3_7B_3_8B_3_9B_3_10B_3_11B_3_12B_3_13B_3_14B_4_7B_4_8B_4_9B_4_10B_4_11B_4_12B_4_13B_4_14B_5_7B_5_8B_5_9B_5_10B_5_11B_5_12B_5_13B_5_14B_6_7B_6_8B_6_9B_6_10B_6_11B_6_12B_6_13B_6_14B_7_7B_7_8B_7_9B_7_10B_7_11B_7_12B_7_13B_7_14B_8_7B_8_8B_8_9B_8_10B_8_11B_8_12B_8_13B_8_14B_9_7B_9_8B_9_9B_9_10B_9_11B_9_12B_9_13B_9_14B_10_7B_10_8B_10_9B_10_10B_10_11B_10_12B_10_13B_10_14B_11_7B_11_8B_11_9B_11_10B_11_11B_11_12B_11_13B_11_14B_12_7B_12_8B_12_9B_12_10B_12_11B_12_12B_12_13B_12_14B_13_7B_13_8B_13_9B_13_10B_13_11B_13_12B_13_13B_13_14C_7_1C_7_2C_7_3C_8_1C_8_2C_8_3C_9_1C_9_2C_9_3C_10_1C_10_2C_10_3C_11_1C_11_2C_11_3C_12_1C_12_2C_12_3C_13_1C_13_2C_13_3C_14_1C_14_2C_14_3Trace(Mul(Matrix(3, 13, [[A_1_1,A_1_2,A_1_3,A_1_4,A_1_5,A_1_6,A_1_7,A_1_8,A_1_9,A_1_10,A_1_11,A_1_12,A_1_13],[A_2_1,A_2_2,A_2_3,A_2_4,A_2_5,A_2_6,A_2_7,A_2_8,A_2_9,A_2_10,A_2_11,A_2_12,A_2_13],[A_3_1,A_3_2,A_3_3,A_3_4,A_3_5,A_3_6,A_3_7,A_3_8,A_3_9,A_3_10,A_3_11,A_3_12,A_3_13]]),Matrix(13, 14, [[B_1_1,B_1_2,B_1_3,B_1_4,B_1_5,B_1_6,B_1_7,B_1_8,B_1_9,B_1_10,B_1_11,B_1_12,B_1_13,B_1_14],[B_2_1,B_2_2,B_2_3,B_2_4,B_2_5,B_2_6,B_2_7,B_2_8,B_2_9,B_2_10,B_2_11,B_2_12,B_2_13,B_2_14],[B_3_1,B_3_2,B_3_3,B_3_4,B_3_5,B_3_6,B_3_7,B_3_8,B_3_9,B_3_10,B_3_11,B_3_12,B_3_13,B_3_14],[B_4_1,B_4_2,B_4_3,B_4_4,B_4_5,B_4_6,B_4_7,B_4_8,B_4_9,B_4_10,B_4_11,B_4_12,B_4_13,B_4_14],[B_5_1,B_5_2,B_5_3,B_5_4,B_5_5,B_5_6,B_5_7,B_5_8,B_5_9,B_5_10,B_5_11,B_5_12,B_5_13,B_5_14],[B_6_1,B_6_2,B_6_3,B_6_4,B_6_5,B_6_6,B_6_7,B_6_8,B_6_9,B_6_10,B_6_11,B_6_12,B_6_13,B_6_14],[B_7_1,B_7_2,B_7_3,B_7_4,B_7_5,B_7_6,B_7_7,B_7_8,B_7_9,B_7_10,B_7_11,B_7_12,B_7_13,B_7_14],[B_8_1,B_8_2,B_8_3,B_8_4,B_8_5,B_8_6,B_8_7,B_8_8,B_8_9,B_8_10,B_8_11,B_8_12,B_8_13,B_8_14],[B_9_1,B_9_2,B_9_3,B_9_4,B_9_5,B_9_6,B_9_7,B_9_8,B_9_9,B_9_10,B_9_11,B_9_12,B_9_13,B_9_14],[B_10_1,B_10_2,B_10_3,B_10_4,B_10_5,B_10_6,B_10_7,B_10_8,B_10_9,B_10_10,B_10_11,B_10_12,B_10_13,B_10_14],[B_11_1,B_11_2,B_11_3,B_11_4,B_11_5,B_11_6,B_11_7,B_11_8,B_11_9,B_11_10,B_11_11,B_11_12,B_11_13,B_11_14],[B_12_1,B_12_2,B_12_3,B_12_4,B_12_5,B_12_6,B_12_7,B_12_8,B_12_9,B_12_10,B_12_11,B_12_12,B_12_13,B_12_14],[B_13_1,B_13_2,B_13_3,B_13_4,B_13_5,B_13_6,B_13_7,B_13_8,B_13_9,B_13_10,B_13_11,B_13_12,B_13_13,B_13_14]]),Matrix(14, 3, [[C_1_1,C_1_2,C_1_3],[C_2_1,C_2_2,C_2_3],[C_3_1,C_3_2,C_3_3],[C_4_1,C_4_2,C_4_3],[C_5_1,C_5_2,C_5_3],[C_6_1,C_6_2,C_6_3],[C_7_1,C_7_2,C_7_3],[C_8_1,C_8_2,C_8_3],[C_9_1,C_9_2,C_9_3],[C_10_1,C_10_2,C_10_3],[C_11_1,C_11_2,C_11_3],[C_12_1,C_12_2,C_12_3],[C_13_1,C_13_2,C_13_3],[C_14_1,C_14_2,C_14_3]]))) = Trace(Mul(Matrix(3, 13, [[A_1_1,A_1_2,A_1_3,A_1_4,A_1_5,A_1_6,A_1_7,A_1_8,A_1_9,A_1_10,A_1_11,A_1_12,A_1_13],[A_2_1,A_2_2,A_2_3,A_2_4,A_2_5,A_2_6,A_2_7,A_2_8,A_2_9,A_2_10,A_2_11,A_2_12,A_2_13],[A_3_1,A_3_2,A_3_3,A_3_4,A_3_5,A_3_6,A_3_7,A_3_8,A_3_9,A_3_10,A_3_11,A_3_12,A_3_13]]),Matrix(13, 6, [[B_1_1,B_1_2,B_1_3,B_1_4,B_1_5,B_1_6],[B_2_1,B_2_2,B_2_3,B_2_4,B_2_5,B_2_6],[B_3_1,B_3_2,B_3_3,B_3_4,B_3_5,B_3_6],[B_4_1,B_4_2,B_4_3,B_4_4,B_4_5,B_4_6],[B_5_1,B_5_2,B_5_3,B_5_4,B_5_5,B_5_6],[B_6_1,B_6_2,B_6_3,B_6_4,B_6_5,B_6_6],[B_7_1,B_7_2,B_7_3,B_7_4,B_7_5,B_7_6],[B_8_1,B_8_2,B_8_3,B_8_4,B_8_5,B_8_6],[B_9_1,B_9_2,B_9_3,B_9_4,B_9_5,B_9_6],[B_10_1,B_10_2,B_10_3,B_10_4,B_10_5,B_10_6],[B_11_1,B_11_2,B_11_3,B_11_4,B_11_5,B_11_6],[B_12_1,B_12_2,B_12_3,B_12_4,B_12_5,B_12_6],[B_13_1,B_13_2,B_13_3,B_13_4,B_13_5,B_13_6]]),Matrix(6, 3, [[C_1_1,C_1_2,C_1_3],[C_2_1,C_2_2,C_2_3],[C_3_1,C_3_2,C_3_3],[C_4_1,C_4_2,C_4_3],[C_5_1,C_5_2,C_5_3],[C_6_1,C_6_2,C_6_3]])))+Trace(Mul(Matrix(3, 13, [[A_1_1,A_1_2,A_1_3,A_1_4,A_1_5,A_1_6,A_1_7,A_1_8,A_1_9,A_1_10,A_1_11,A_1_12,A_1_13],[A_2_1,A_2_2,A_2_3,A_2_4,A_2_5,A_2_6,A_2_7,A_2_8,A_2_9,A_2_10,A_2_11,A_2_12,A_2_13],[A_3_1,A_3_2,A_3_3,A_3_4,A_3_5,A_3_6,A_3_7,A_3_8,A_3_9,A_3_10,A_3_11,A_3_12,A_3_13]]),Matrix(13, 8, [[B_1_7,B_1_8,B_1_9,B_1_10,B_1_11,B_1_12,B_1_13,B_1_14],[B_2_7,B_2_8,B_2_9,B_2_10,B_2_11,B_2_12,B_2_13,B_2_14],[B_3_7,B_3_8,B_3_9,B_3_10,B_3_11,B_3_12,B_3_13,B_3_14],[B_4_7,B_4_8,B_4_9,B_4_10,B_4_11,B_4_12,B_4_13,B_4_14],[B_5_7,B_5_8,B_5_9,B_5_10,B_5_11,B_5_12,B_5_13,B_5_14],[B_6_7,B_6_8,B_6_9,B_6_10,B_6_11,B_6_12,B_6_13,B_6_14],[B_7_7,B_7_8,B_7_9,B_7_10,B_7_11,B_7_12,B_7_13,B_7_14],[B_8_7,B_8_8,B_8_9,B_8_10,B_8_11,B_8_12,B_8_13,B_8_14],[B_9_7,B_9_8,B_9_9,B_9_10,B_9_11,B_9_12,B_9_13,B_9_14],[B_10_7,B_10_8,B_10_9,B_10_10,B_10_11,B_10_12,B_10_13,B_10_14],[B_11_7,B_11_8,B_11_9,B_11_10,B_11_11,B_11_12,B_11_13,B_11_14],[B_12_7,B_12_8,B_12_9,B_12_10,B_12_11,B_12_12,B_12_13,B_12_14],[B_13_7,B_13_8,B_13_9,B_13_10,B_13_11,B_13_12,B_13_13,B_13_14]]),Matrix(8, 3, [[C_7_1,C_7_2,C_7_3],[C_8_1,C_8_2,C_8_3],[C_9_1,C_9_2,C_9_3],[C_10_1,C_10_2,C_10_3],[C_11_1,C_11_2,C_11_3],[C_12_1,C_12_2,C_12_3],[C_13_1,C_13_2,C_13_3],[C_14_1,C_14_2,C_14_3]])))

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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