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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]
In computing, a memory access pattern or IO access pattern is the pattern with which a system or program reads and writes memory on secondary storage.These patterns differ in the level of locality of reference and drastically affect cache performance, [1] and also have implications for the approach to parallelism [2] [3] and distribution of workload in shared memory systems. [4]
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 ]
The language incorporates built-in data types and structures, control flow mechanisms, first-class functions, and modules for better code reusability and organization. Python also uses English keywords where other languages use punctuation, contributing to its uncluttered visual layout.
There are several memory-consistency models for SMP systems: Sequential consistency (all reads and all writes are in-order) Relaxed consistency (some types of reordering are allowed) Loads can be reordered after loads (for better working of cache coherency, better scaling) Loads can be reordered after stores; Stores can be reordered after stores
Sequential consistency can be achieved simply by hardware implementation, while release consistency is also based on an observation that most of the parallel programs are properly synchronized. In programming level, synchronization is applied to clearly schedule a certain memory access in one thread to occur after another.
Concurrent data structures are significantly more difficult to design and to verify as being correct than their sequential counterparts. The primary source of this additional difficulty is concurrency, exacerbated by the fact that threads must be thought of as being completely asynchronous: they are subject to operating system preemption, page faults, interrupts, and so on.