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U++, formally known as Ultimate++ - is a C++ RAD framework that aims to reduce the code complexity of typical desktop applications by including all necessary toolkits into a single C++ framework. Programs created with it works on multiple Operating Systems and Hardware Architectures with performance without needing to write platform-specific code.
Conversely, some language features make certain optimizations easier. For example, in some languages, functions are not permitted to have side effects. Therefore, if a program makes several calls to the same function with the same arguments, the compiler can infer that the function's result only needs to be computed once.
Generally data structures are more difficult to change than algorithms, as a data structure assumption and its performance assumptions are used throughout the program, though this can be minimized by the use of abstract data types in function definitions, and keeping the concrete data structure definitions restricted to a few places.
Python: Python profiling includes the profile module, hotshot (which is call-graph based), and using the 'sys.setprofile' function to trap events like c_{call,return,exception}, python_{call,return,exception}. Ruby: Ruby also uses a similar interface to Python for profiling. Flat-profiler in profile.rb, module, and ruby-prof a C-extension are ...
The elementary functions are constructed by composing arithmetic operations, the exponential function (), the natural logarithm (), trigonometric functions (,), and their inverses. The complexity of an elementary function is equivalent to that of its inverse, since all elementary functions are analytic and hence invertible by means of Newton's ...
The implementation is based on spectral projection methods, e.g., methods based on the matrix sign function and the matrix disk function. Dune-RB: A module for the Dune library, which realizes C++ template classes for use in snapshot generation and RB offline phases for various discretizations. Apart from single-core algorithms, the package ...
Memoized functions are optimized for speed in exchange for a higher use of computer memory space. The time/space "cost" of algorithms has a specific name in computing: computational complexity. All functions have a computational complexity in time (i.e. they take time to execute) and in space.
Since then, a C++ API and other language interfaces have been developed, and modelling utilities and other categories of solver have been added. In early‑2022, the GenX and PyPSA open energy system modelling projects endorsed a funding application for the HiGHS solver in an effort to reduce their community reliance on proprietary libraries. [ 4 ]