تحسيب عكسي

التحسيب العكسي هو عبارة عن نموذج تحسيب حيث تكون العمليات التحسيبية عكسية إلى حد ما.

قالب:Longintro Reversible computing is a model of computing where the computational process to some extent is reversible, i.e., time-invertible. A necessary condition for reversibility of a computational model is that the transition function mapping states to their successors at a given later time should be one-to-one. Reversible computing is generally considered an unconventional form of computing.

There are two major, closely-related, types of reversibility that are of particular interest for this purpose: physical reversibility and logical reversibility.

A process is said to be physically reversible if it results in no increase in physical entropy; it is isentropic. These circuits are also referred to as charge recovery logic or adiabatic computing. Although in practice no nonstationary physical process can be exactly physically reversible or isentropic, there is no known limit to the closeness with which we can approach perfect reversibility, in systems that are sufficiently well-isolated from interactions with unknown external environments, when the laws of physics describing the system's evolution are precisely known.

Probably the largest motivation for the study of technologies aimed at actually implementing reversible computing is that they offer what is predicted to be the only potential way to improve the energy efficiency of computers beyond the fundamental von Neumann-Landauer limit of kT ln(2) energy dissipated per irreversible bit operation.

As was first argued by Rolf Landauer of IBM, in order for a computational process to be physically reversible, it must also be logically reversible. Landauer's principle is the loosely formulated notion that the erasure of n bits of information must always incur a cost of nTk ln(2) in thermodynamic entropy. A discrete, deterministic computational process is said to be logically reversible if the transition function that maps old computational states to new ones is a one-to-one function; i.e. the output logical states uniquely defines the input logical states of the computational operation.

For computational processes that are nondeterministic (in the sense of being probabilistic or random), the relation between old and new states is not a single-valued function, and the requirement needed to obtain physical reversibility becomes a slightly weaker condition, namely that the size of a given ensemble of possible initial computational states does not decrease, on average, as the computation proceeds forwards.

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

 The reversibility of physics and reversible computing

Landauer's principle (and indeed, the second law of thermodynamics itself) can also be understood to be a direct logical consequence of the underlying reversibility of physics, as is reflected in the general Hamiltonian formulation of mechanics, and in the unitary time-evolution operator of quantum mechanics more specifically.

In the context of reversible physics, the phenomenon of entropy increase (and the observed arrow of time) can be understood to be consequences of the fact that our evolved predictive capabilities are rather limited, and cannot keep perfect track of the exact reversible evolution of complex physical systems, especially since these systems are never perfectly isolated from an unknown external environment, and even the laws of physics themselves are still not known with complete precision. Thus, we (and physical observers generally) always accumulate some uncertainty about the state of physical systems, even if the system's true underlying dynamics is a perfectly reversible one that is subject to no entropy increase if viewed from a hypothetical omniscient perspective in which the dynamical laws are precisely known.

The implementation of reversible computing thus amounts to learning how to characterize and control the physical dynamics of mechanisms to carry out desired computational operations so precisely that we can accumulate a negligible total amount of uncertainty regarding the complete physical state of the mechanism, per each logic operation that is performed. In other words, we would need to precisely track the state of the active energy that is involved in carrying out computational operations within the machine, and design the machine in such a way that the majority of this energy is recovered in an organized form that can be reused for subsequent operations, rather than being permitted to dissipate into the form of heat.

Although achieving this goal presents a significant challenge for the design, manufacturing, and characterization of ultra-precise new physical mechanisms for computing, there is at present no fundamental reason to think that this goal cannot eventually be accomplished, allowing us to someday build computers that generate much less than 1 bit's worth of physical entropy (and dissipate much less than kT ln 2 energy to heat) for each useful logical operation that they carry out internally.

The motivation behind much of the research that has been done in reversible computing was the first seminal paper on the topic , which was published by Charles H. Bennett of IBM research in 1973. Today, the field has a substantial body of academic literature behind it. A wide variety of reversible device concepts, logic gates, electronic circuits, processor architectures, programming languages, and application algorithms have been designed and analyzed by physicists, electrical engineers, and computer scientists.

This field of research awaits the detailed development of a high-quality, cost-effective, nearly reversible logic device technology, one that includes highly energy-efficient clocking and synchronization mechanisms. This sort of solid engineering progress will be needed before the large body of theoretical research on reversible computing can find practical application in enabling real computer technology to circumvent the various near-term barriers to its energy efficiency, including the von Neumann-Landauer bound. This may only be circumvented by the use of logically reversible computing, due to the Second Law of Thermodynamics.

 Practical logical reversibility

قالب:Relevance Any computational algorithm may be made logically reversible for as long as a complete history of each nonreversible operation can be maintained. (This is seen in every software application which offers a multi-level "Undo" feature.) The history will grow ever larger, so it is limited by available memory. To partially circumvent that limitation, snapshots of the complete computational state can be saved at various intervals, to provide the ability to jump further backwards in time, although not smoothly. (This approach is adopted by archival "backup" systems.)

Reversible computing of this kind is usually not symmetrical in time. (Reversing an operation may take more time, or less, because the underlying mechanism is different.)

 انظر أيضاً

• Reversible dynamics
• Maximum entropy thermodynamics, on the uncertainty interpretation of the second law of thermodynamics
• Reversible process
• Toffoli gate
• Fredkin gate
• حوسبة كمومية
• Billiard-ball computer
• Three-input universal logic gate
• Undo
• Reversible cellular automaton

 مراجع

Review of later theoretical work: P.M.B. Vitanyi, Time, space, and energy in reversible computing, Proceedings of the 2nd ACM conference on Computing frontiers, 2005, 435–444.

 روابط خارجية

• Introductory article on reversible computing
• First International Workshop on reversible computing
• Recent publications of Michael P. Frank
• Internet Archive backup of the "Reversible computing community Wiki" that was administered by Dr. Frank