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A typical vector implementation consists, internally, of a pointer to a dynamically allocated array, [1] and possibly data members holding the capacity and size of the vector. The size of the vector refers to the actual number of elements, while the capacity refers to the size of the internal array.
Adept implements automatic differentiation using an operator overloading approach, in which scalars to be differentiated are written as adouble, indicating an "active" version of the normal double, and vectors to be differentiated are written as aVector.
It is, however, preferable to use an algorithm from the C++ Standard Library for such tasks. [1] [2] [3] The member function erase can be used to delete an element from a collection, but for containers which are based on an array, such as vector, all elements after the deleted element have to be moved forward to avoid "gaps" in the collection ...
Automatic vectorization, in parallel computing, is a special case of automatic parallelization, where a computer program is converted from a scalar implementation, which processes a single pair of operands at a time, to a vector implementation, which processes one operation on multiple pairs of operands at once.
Reverse accumulation traverses the chain rule from outside to inside, or in the case of the computational graph in Figure 3, from top to bottom. The example function is scalar-valued, and thus there is only one seed for the derivative computation, and only one sweep of the computational graph is needed to calculate the (two-component) gradient.
Once the registers have been allocated for vector type arguments, the unused registers are allocated to HVA arguments from left to right. The positioning rules still apply. Resulting vector type and HVA values are returned using the first four XMM/YMM registers. [11] The Clang compiler and the Intel C++ Compiler also implement vectorcall. [12]
Using the XOR swap algorithm to exchange nibbles between variables without the use of temporary storage. In computer programming, the exclusive or swap (sometimes shortened to XOR swap) is an algorithm that uses the exclusive or bitwise operation to swap the values of two variables without using the temporary variable which is normally required.
Three similar vectors are in use that condense the inversions of a permutation into a vector that uniquely determines it. They are often called inversion vector or Lehmer code. (A list of sources is found here.) This article uses the term inversion vector like Wolfram. [13]