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Sequential access is a term describing a group of elements (such as data in a memory array or a disk file or on magnetic-tape data storage) being accessed in a predetermined, ordered sequence. It is the opposite of random access , the ability to access an arbitrary element of a sequence as easily and efficiently as any other at any time.
In computing, sequential access memory (SAM) is a class of data storage devices that read stored data in a sequence. This is in contrast to random access memory (RAM) where data can be accessed in any order. Sequential access devices are usually a form of magnetic storage or optical storage. [1] [2]
[1] [4] Conversely, the memory order is called weak or relaxed when one thread cannot predict the order of operations arising from another thread. [1] [4] Many naïvely written parallel algorithms fail when compiled or executed with a weak memory order. [5] [6] The problem is most often solved by inserting memory barrier instructions into the ...
In computer science, a B-tree is a self-balancing tree data structure that maintains sorted data and allows searches, sequential access, insertions, and deletions in logarithmic time. The B-tree generalizes the binary search tree , allowing for nodes with more than two children. [ 2 ]
Note how the use of A[i][j] with multi-step indexing as in C, as opposed to a neutral notation like A(i,j) as in Fortran, almost inevitably implies row-major order for syntactic reasons, so to speak, because it can be rewritten as (A[i])[j], and the A[i] row part can even be assigned to an intermediate variable that is then indexed in a separate expression.
Using a general memory pool leaves more memory for other data if the list is smaller than expected or if many nodes are freed. For these reasons, this approach is mainly used for languages that do not support dynamic memory allocation. These disadvantages are also mitigated if the maximum size of the list is known at the time the array is created.
In Python, a generator can be thought of as an iterator that contains a frozen stack frame. Whenever next() is called on the iterator, Python resumes the frozen frame, which executes normally until the next yield statement is reached. The generator's frame is then frozen again, and the yielded value is returned to the caller.
[1] [2] [3] This introduces write-after-write (WAW) hazards because the second instruction to write the value to a memory location needs to wait until the first instruction finishes writing data to the same memory location or else when the memory location is read at a later time it will contain the wrong value. [2]