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  2. List of open-source software for mathematics - Wikipedia

    en.wikipedia.org/wiki/List_of_open-source...

    PARI/GP is a computer algebra system that facilitates number-theory computation. Besides support of factoring, algebraic number theory, and analysis of elliptic curves, it works with mathematical objects like matrices, polynomials, power series , algebraic numbers, and transcendental functions . [ 3 ]

  3. List of numerical-analysis software - Wikipedia

    en.wikipedia.org/wiki/List_of_numerical-analysis...

    TK Solver is a mathematical modeling and problem-solving software system based on a declarative, rule-based language, commercialized by Universal Technical Systems, Inc. Torch is a deep-learning library with support for manipulation, statistical analysis and presentation of Tensors.

  4. DaveGrohl - Wikipedia

    en.wikipedia.org/wiki/DaveGrohl

    It was originally created in 2010 as a password hash extractor but has since evolved into a standalone or distributed password cracker. DaveGrohl supports all of the standard Mac OS X user password hashes ( MD4 , SHA-512 and PBKDF2 ) [ 1 ] [ 2 ] [ 3 ] used since OS X Lion and also can extract them formatted for other popular password crackers ...

  5. Gurobi Optimizer - Wikipedia

    en.wikipedia.org/wiki/Gurobi_Optimizer

    The Gurobi Optimizer (often referred to as simply, “Gurobi”) is a solver, since it uses mathematical optimization to calculate the answer to a problem. Gurobi is included in the Q1 2022 inside BIGDATA “Impact 50 List” as an honorable mention.

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  7. OR-Tools - Wikipedia

    en.wikipedia.org/wiki/OR-Tools

    OR-Tools was created by Laurent Perron in 2011. [5]In 2014, Google's open source linear programming solver, GLOP, was released as part of OR-Tools. [1]The CP-SAT solver [6] bundled with OR-Tools has been consistently winning gold medals in the MiniZinc Challenge, [7] an international constraint programming competition.

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  9. MOSEK - Wikipedia

    en.wikipedia.org/wiki/MOSEK

    The applicability of the solver varies widely and is commonly used for solving problems in areas such as engineering, finance and computer science. The emphasis in MOSEK is on solving large-scale sparse problems, in particular the interior-point optimizer for linear, conic quadratic (a.k.a. Second-order cone programming) and semi-definite (aka.