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The primary difference between a computer algebra system and a traditional calculator is the ability to deal with equations symbolically rather than numerically. The precise uses and capabilities of these systems differ greatly from one system to another, yet their purpose remains the same: manipulation of symbolic equations.
This list is incomplete; you can help by adding missing items. ... Related to NumPy, and thus connected to prior Numeric and Numarray packages for Python
dc: "Desktop Calculator" arbitrary-precision RPN calculator that comes standard on most Unix-like systems. KCalc, Linux based scientific calculator; Maxima: a computer algebra system which bignum integers are directly inherited from its implementation language Common Lisp. In addition, it supports arbitrary-precision floating-point numbers ...
The inclusion of certain items in this list is currently being disputed. ... Python, NumPy, SciPy: Python SAS: SAS Institute: 9.4M7 (August 2020 ()),
NumPy (pronounced / ˈ n ʌ m p aɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [3]
CuPy is a part of the NumPy ecosystem array libraries [7] and is widely adopted to utilize GPU with Python, [8] especially in high-performance computing environments such as Summit, [9] Perlmutter, [10] EULER, [11] and ABCI.
simdjson, a JSON parsing library, uses AVX2 and AVX-512 to achieve improved decoding speed. [62] [63] x86-simd-sort, a library with sorting algorithms for 16, 32 and 64-bit numeric data types, uses AVX2 and AVX-512. The library is used in NumPy and OpenJDK to accelerate sorting algorithms. [64]
Numba is an open-source JIT compiler that translates a subset of Python and NumPy into fast machine code using LLVM, via the llvmlite Python package.It offers a range of options for parallelising Python code for CPUs and GPUs, often with only minor code changes.