Optimizing Reversible Simulation of Injective Functions

被引:0
|
作者
Yokoyama, Tetsuo [1 ]
Axelsen, Holger Bock [2 ]
Gluck, Robert [2 ]
机构
[1] Nanzan Univ, Dept Software Engn, Fac Informat Sci & Engn, Seto City, Aichi 4890863, Japan
[2] Univ Copenhagen, Dept Comp Sci, DIKU, DK-2100 Copenhagen, Denmark
关键词
Reversible computing; reversible simulation; Janus; Bennett's method; lossless data encoding; reversibilization; SPACE; INVERSION; LANGUAGE;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Bennett showed that a clean reversible simulation of injective programs is possible without returning the input of a program as additional output. His method involves two computation and two uncomputation phases. This paper proposes an optimization of Bennett's simulation that requires only half of the computation and uncomputation steps for a class of injective programs. A practical consequence is that the reversible simulation runs twice as fast as Bennett's simulation. The proposed method is demonstrated by developing lossless encoders and decoders for run-length encoding and range coding. The range-coding program is further optimized by conserving the model over the text-generation phase. This paper may thus provide a new view on developing efficient reversible simulations for a certain class of injective functions.
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页码:5 / 24
页数:20
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