Implements which-like functionality for a big.matrix, with additional options for efficient comparisons (executed in C++); also works for regular numeric matrices without the memory overhead.
The big.matrix class is designed for matrices with elements of type double, integer, short, or char. A big.matrix acts much like a traditional R matrix, but helps protect the user from many inadvertant memory-consuming pitfalls of traditional R matrices and data frames. The objects are allocated to shared memory, and if file-backing is used they may exceed virtual memory in size. Sadly, 32-bit operating system contraints – largely Windows and some MacOS versions –will be a limiting factor with file-backed matrices; 64-bit operating systems are recommended.
bigmemory-package
(Package: bigmemory) :
Manage massive matrices with shared memory and memory-mapped files.
Create, store, access, and manipulate massive matrices. Matrices are, by default, allocated to shared memory and may use memory-mapped files. Packages biganalytics, synchronicity, bigalgebra, and bigtabulate provide advanced functionality. Access to and manipulation of a big.matrix object is exposed in by an S4 class whose interface is simlar to that of an matrix. Use of these packages in parallel environments can provide substantial speed and memory efficiencies. bigmemory also provides a C++ framework for the development of new tools that can work both with big.matrix and native matrix objects.
providing 
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