The reverse mode of automatic differentiation is widely used in science and engineering. A severe bottleneck for the performance of the reverse mode, however, is the necessity to recover certain intermediate values of the program in reverse order. Among these values are computed addresses, which traditionally are recovered through forward recomputation and storage in memory. We propose an alter...

While computing power and memory size have been steadily increasing as predicted by Moore’s Law, they are still dwarfed by the size of massive data sets resultant from a number of applications. Many problems arising from astrophysics, computational biology, telecommunications, and the Internet often have an amount of accompanying data in the terabyte range. The analysis of this data by classica...