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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]
If an object reliably has a pointer at a certain location, the reference count can be stored in the unused bits of the pointer. For example, each object in Objective-C has a pointer to its class at the beginning of its memory; on the ARM64 architecture using iOS 7, 19 unused bits of this class pointer are used to store the object's reference count.
The use of such spatial indices is not limited to digital data; the "index" section of any global or street atlas commonly contains a list of named features (towns, streets, etc.) with associated grid square identifiers, and may be considered a perfectly acceptable example of a spatial index (in this case, typically organised by feature name ...
The final revision of the proposed memory model, C++ n2429, [6] was accepted into the C++ draft standard at the October 2007 meeting in Kona. [7] The memory model was then included in the next C++ and C standards, C++11 and C11. [8] [9] The Rust programming language inherited most of C/C++'s memory model. [10]
The g++ compiler implements the multiple inheritance of the classes B1 and B2 in class D using two virtual method tables, one for each base class. (There are other ways to implement multiple inheritance, but this is the most common.) This leads to the necessity for "pointer fixups", also called thunks, when casting. Consider the following C++ code:
However, the language also offers various alternatives to complex forms of memory management. Reference counting functionality is provided by the Rc and Arc types, which are non-atomic and atomic respectively. For example, the type Rc<T> provides shared ownership of a value of type T, allocated on the heap for multiple references to its data. [22]
Data locality is a typical memory reference feature of regular programs (though many irregular memory access patterns exist). It makes the hierarchical memory layout profitable. In computers, memory is divided into a hierarchy in order to speed up data accesses. The lower levels of the memory hierarchy tend to be slower, but larger.
In computer science, manual memory management refers to the usage of manual instructions by the programmer to identify and deallocate unused objects, or garbage.Up until the mid-1990s, the majority of programming languages used in industry supported manual memory management, though garbage collection has existed since 1959, when it was introduced with Lisp.