Screw threadA screw thread, often shortened to thread, is a helical structure used to convert between rotational and linear movement or force. A screw thread is a ridge wrapped around a cylinder or cone in the form of a helix, with the former being called a straight thread and the latter called a tapered thread. A screw thread is the essential feature of the screw as a simple machine and also as a threaded fastener. The mechanical advantage of a screw thread depends on its lead, which is the linear distance the screw travels in one revolution.
Lock (computer science)In computer science, a lock or mutex (from mutual exclusion) is a synchronization primitive: a mechanism that enforces limits on access to a resource when there are many threads of execution. A lock is designed to enforce a mutual exclusion concurrency control policy, and with a variety of possible methods there exists multiple unique implementations for different applications. Generally, locks are advisory locks, where each thread cooperates by acquiring the lock before accessing the corresponding data.
Scala (programming language)Scala (ˈskɑːlə ) is a strong statically typed high-level general-purpose programming language that supports both object-oriented programming and functional programming. Designed to be concise, many of Scala's design decisions are aimed to address criticisms of Java. Scala source code can be compiled to Java bytecode and run on a Java virtual machine (JVM). Scala can also be compiled to JavaScript to run in a browser, or directly to a native executable.
Atomicity (database systems)In database systems, atomicity (ˌætəˈmɪsəti; from átomos) is one of the ACID (Atomicity, Consistency, Isolation, Durability) transaction properties. An atomic transaction is an indivisible and irreducible series of database operations such that either all occurs, or nothing occurs. A guarantee of atomicity prevents updates to the database occurring only partially, which can cause greater problems than rejecting the whole series outright. As a consequence, the transaction cannot be observed to be in progress by another database client.
Trapezoidal thread formTrapezoidal thread forms are screw thread profiles with trapezoidal outlines. They are the most common forms used for leadscrews (power screws). They offer high strength and ease of manufacture. They are typically found where large loads are required, as in a vise or the leadscrew of a lathe. Standardized variations include multiple-start threads, left-hand threads, and self-centering threads (which are less likely to bind under lateral forces).
Fiber (computer science)In computer science, a fiber is a particularly lightweight thread of execution. Like threads, fibers share address space. However, fibers use cooperative multitasking while threads use preemptive multitasking. Threads often depend on the kernel's thread scheduler to preempt a busy thread and resume another thread; fibers yield themselves to run another fiber while executing. The key difference between fibers and kernel threads is that fibers use cooperative context switching, instead of preemptive time-slicing.
Peterson's algorithmPeterson's algorithm (or Peterson's solution) is a concurrent programming algorithm for mutual exclusion that allows two or more processes to share a single-use resource without conflict, using only shared memory for communication. It was formulated by Gary L. Peterson in 1981. While Peterson's original formulation worked with only two processes, the algorithm can be generalized for more than two. The algorithm uses two variables: flag and turn. A flag[n] value of true indicates that the process n wants to enter the critical section.
Read–modify–writeIn computer science, read–modify–write is a class of atomic operations (such as test-and-set, fetch-and-add, and compare-and-swap) that both read a memory location and write a new value into it simultaneously, either with a completely new value or some function of the previous value. These operations prevent race conditions in multi-threaded applications. Typically they are used to implement mutexes or semaphores. These atomic operations are also heavily used in non-blocking synchronization.
Light-weight processIn computer operating systems, a light-weight process (LWP) is a means of achieving multitasking. In the traditional meaning of the term, as used in Unix System V and Solaris, a LWP runs in user space on top of a single kernel thread and shares its address space and system resources with other LWPs within the same process. Multiple user-level threads, managed by a thread library, can be placed on top of one or many LWPs - allowing multitasking to be done at the user level, which can have some performance benefits.
Transactional memoryIn computer science and engineering, transactional memory attempts to simplify concurrent programming by allowing a group of load and store instructions to execute in an atomic way. It is a concurrency control mechanism analogous to database transactions for controlling access to shared memory in concurrent computing. Transactional memory systems provide high-level abstraction as an alternative to low-level thread synchronization. This abstraction allows for coordination between concurrent reads and writes of shared data in parallel systems.
Instruction-level parallelismInstruction-level parallelism (ILP) is the parallel or simultaneous execution of a sequence of instructions in a computer program. More specifically ILP refers to the average number of instructions run per step of this parallel execution. ILP must not be confused with concurrency. In ILP there is a single specific thread of execution of a process. On the other hand, concurrency involves the assignment of multiple threads to a CPU's core in a strict alternation, or in true parallelism if there are enough CPU cores, ideally one core for each runnable thread.
Inter-process communicationIn computer science, inter-process communication (IPC), also spelled interprocess communication, are the mechanisms provided by an operating system for processes to manage shared data. Typically, applications can use IPC, categorized as clients and servers, where the client requests data and the server responds to client requests. Many applications are both clients and servers, as commonly seen in distributed computing. IPC is very important to the design process for microkernels and nanokernels, which reduce the number of functionalities provided by the kernel.
