… By interchanging rows and columns of a matrix A, we obtain a matrix which is … we use the
same letter P to denote a matrix which represents the subspace P. We call the matrix P a matrix …

… Parallelizing dense matrix computations to distributed memory architectures is a well-studied
subject and generally considered to be among the best understood domains of parallel …

… to improve future memory and computing performance. By … in-memory matrix operations,
where same devices are used … systems can be used to perform vector–matrix multiplication …

… matrix A in random access memory (RAM), provided it can make two passes over the matrix
stored in external memory and use … matrix C by randomly sampling r rows of C to form a r × c …

… the matrices A and B in RAM, provided it can make two passes over the matrices stored in
external memory and use O(… We then present a second matrix multiplication algorithm which is …

… format used to store the sparse matrix in memory. Compressed sparse row (CSR) has historically
been a frequently used … compresses both structured and unstructured matrices, and it is …

… known matrix memories are \Willshaw" networks Willshaw, 1981] and Hop eld networks Hop
eld, 1982]. Matrix memories can be used … associated with the cue, or a noisy version thereof. …

… external memory matrix, analogous to the random-access memory in a conventional computer.
Like a conventional computer, it can use its memory … without external read–write memory. …

… This algorithm may be implemented without storing the matrix A in RAM, provided it can
make two passes over the matrix stored in external memory and use O(m + n) additional RAM (…

… (sometimes referred to as holographic-like memories) and matrix memories have been …
produces the item that was originally associated with the cue, or a noisy version thereof. …