Table of Contents:
  • pt. 1. The exponent of matrix multiplication. The power of recursive algorithms for matrix multiplication
  • Bilinear algorithms for MM
  • The search for a basis algorithm and the history of the asymptotic acceleration of MM
  • the basic algorithm and the Exponent 2.67
  • The dependence of the exponent of MM on the class of constants used
  • [Leaning T]-algorithms and their application to MM. Accumulation of the accelerating power of [leaning T]-algorithms via recursion
  • Strassen's conjecture. Its extended and exponential versions
  • Recursive algorithms for MM and for disjoint MM (definitions, notation, and two basic facts)
  • Some applications of the recursive construction of bilinear algorithms
  • Trilinear versions of bilinear algorithms and of bilinear [leaning T]-algorithms. Duality. Recursive trilinear algorithms
  • Trilinear aggregating and some efficient basis designs
  • A further example of trilinear aggregating and its refinement via a linear transformation of variables
  • Aggregating the triplets of principal terms
  • Recursive application of trilinear aggregating
  • Can the exponent be further reduced?
  • The exponents below 2.5
  • How much can we reduce the exponent?
  • pt. 2. Correlation between matrix multiplication and other computational problems. Bit-time, bit-space, stability, and condition.
  • Reduction of some combinatorial computational problems to MM
  • Asymptotic arithmetical complexity of some computations in linear algebra
  • Two block-matrix algorithms for the QR-factorization and QR-type factorization of a matrix
  • Applications of the QR- and QR-type factorization to the problems MI, SLE, and Det
  • Storage space for asymptotically fast matrix operations
  • The bit-complexity of computations in linear algebra. The case of matrix multiplication
  • Matrix norms and their application to estimating the bit-complexity of matrix multiplication
  • Stability and condition of algebraic problems and of algorithms for such problems
  • Estimating the errors of the QR-factorization of a matrix
  • The bit-complexity and the condition of the problem of solving a system of linear equations
  • The bit-complexity and the condition of the problem of matrix inversion
  • The bit-complexity and the condition of the problem of the evaluation of the determinant of a matrix
  • Summary of the bounds on the bit-time of computations in linear algebra; acceleration of solving a system of linear equations where high relative precision of the output is required
  • pt. 3. The speed-up of the multiplication of matrices of a fixed size. The currently best upper bounds on the rank of the problem of MM of moderate sizes
  • commutative quadratic algorithms for MM
  • [Leaning T]-algorithms for the multiplication of matrices of small and moderate sizes
  • The classes of straight line arithmetical algorithms and [leaning T]-algorithms and their reduction to quadratic ones
  • The basic active substitution argument and lover bounds on the ranks of arithmetical algorithms for matrix multiplication
  • Lower bounds on the [leaning T]-rank and on the commutative [leaning T]-rank of matrix multiplication
  • Basic active substitution argument and lower bounds on the number of additions and subtractions
  • Nonlinear lower bounds on the complexity of arithmetical problems under additional restrictions on the computational schemes
  • A trade-off between the additive complexity and the asynchronicity of linear and bilinear algorithms
  • An attempt of practical acceleration of matrix multiplication and of some other arithmetical computations.