X86 virtualizationx86 virtualization is the use of hardware-assisted virtualization capabilities on an x86/x86-64 CPU. In the late 1990s x86 virtualization was achieved by complex software techniques, necessary to compensate for the processor's lack of hardware-assisted virtualization capabilities while attaining reasonable performance. In 2005 and 2006, both Intel (VT-x) and AMD (AMD-V) introduced limited hardware virtualization support that allowed simpler virtualization software but offered very few speed benefits.
P versus NP problemThe P versus NP problem is a major unsolved problem in theoretical computer science. In informal terms, it asks whether every problem whose solution can be quickly verified can also be quickly solved. The informal term quickly, used above, means the existence of an algorithm solving the task that runs in polynomial time, such that the time to complete the task varies as a polynomial function on the size of the input to the algorithm (as opposed to, say, exponential time).
Computer programmingComputer programming is the process of performing particular computations (or more generally, accomplishing specific computing results), usually by designing and building executable computer programs. Programming involves tasks such as analysis, generating algorithms, profiling algorithms' accuracy and resource consumption, and the implementation of algorithms (usually in a particular programming language, commonly referred to as coding).
NP-hardnessIn computational complexity theory, NP-hardness (non-deterministic polynomial-time hardness) is the defining property of a class of problems that are informally "at least as hard as the hardest problems in NP". A simple example of an NP-hard problem is the subset sum problem. A more precise specification is: a problem H is NP-hard when every problem L in NP can be reduced in polynomial time to H; that is, assuming a solution for H takes 1 unit time, Hs solution can be used to solve L in polynomial time.
Machine codeIn computer programming, machine code is computer code consisting of machine language instructions, which are used to control a computer's central processing unit (CPU). Although decimal computers were once common, the contemporary marketplace is dominated by binary computers; for those computers, machine code is "the binary representation of a computer program which is actually read and interpreted by the computer. A program in machine code consists of a sequence of machine instructions (possibly interspersed with data).
Performance engineeringPerformance engineering encompasses the techniques applied during a systems development life cycle to ensure the non-functional requirements for performance (such as throughput, latency, or memory usage) will be met. It may be alternatively referred to as systems performance engineering within systems engineering, and software performance engineering or application performance engineering within software engineering.
Limbo (programming language)Limbo is a programming language for writing distributed systems and is the language used to write applications for the Inferno operating system. It was designed at Bell Labs by Sean Dorward, Phil Winterbottom, and Rob Pike. The Limbo compiler generates architecture-independent object code which is then interpreted by the Dis virtual machine or compiled just before runtime to improve performance. Therefore all Limbo applications are completely portable across all Inferno platforms.
Parallel programming modelIn computing, a parallel programming model is an abstraction of parallel computer architecture, with which it is convenient to express algorithms and their composition in programs. The value of a programming model can be judged on its generality: how well a range of different problems can be expressed for a variety of different architectures, and its performance: how efficiently the compiled programs can execute. The implementation of a parallel programming model can take the form of a library invoked from a sequential language, as an extension to an existing language, or as an entirely new language.
Knapsack problemThe knapsack problem is the following problem in combinatorial optimization: Given a set of items, each with a weight and a value, determine which items to include in the collection so that the total weight is less than or equal to a given limit and the total value is as large as possible. It derives its name from the problem faced by someone who is constrained by a fixed-size knapsack and must fill it with the most valuable items.
Model-driven engineeringModel-driven engineering (MDE) is a software development methodology that focuses on creating and exploiting domain models, which are conceptual models of all the topics related to a specific problem. Hence, it highlights and aims at abstract representations of the knowledge and activities that govern a particular application domain, rather than the computing (i.e. algorithmic) concepts. MDE is a subfield of a software design approach referred as round-trip engineering.
Time complexityIn computer science, the time complexity is the computational complexity that describes the amount of computer time it takes to run an algorithm. Time complexity is commonly estimated by counting the number of elementary operations performed by the algorithm, supposing that each elementary operation takes a fixed amount of time to perform. Thus, the amount of time taken and the number of elementary operations performed by the algorithm are taken to be related by a constant factor.
Automatic programmingIn computer science, automatic programming is a type of computer programming in which some mechanism generates a computer program to allow human programmers to write the code at a higher abstraction level. There has been little agreement on the precise definition of automatic programming, mostly because its meaning has changed over time. David Parnas, tracing the history of "automatic programming" in published research, noted that in the 1940s it described automation of the manual process of punching paper tape.
