Hewlett Packard Enterprise Development LP

Benjamin Feinberg

Naveen Muralimanohar

John Paul Strachan

In some examples, memristive dot product circuit based floating point computations may include ascertaining a matrix and a vector including floating point values, and partitioning the matrix into a plurality of sub-matrices according to a size of a plurality of memristive dot product circuits. For each sub-matrix of the plurality of sub-matrices, the floating point values may be converted to fixed point values. Based on the conversion and selected ones of the plurality of memristive dot product circuits, a dot product operation may be performed with respect to a sub-matrix and the vector. Each ones of the plurality of memristive dot product circuits may include rows including word line voltages corresponding to the floating point values of the vector, conductances corresponding to the floating point values of an associated sub-matrix, and columns that include bitline currents corresponding to dot products of the voltages and conductances.

Memristive dot product circuit based floating point computations

Example implementations of the present disclosure relate to in situ transposition of the data values in a memory array. An example system may include a non-volatile memory (NVM) array, including a plurality of NVM elements, usable in performance of computations. The example system may include an input engine to input a plurality of data values for storage by a corresponding plurality of original NVM elements. The example system may further include a transposition engine to direct performance of the in situ transposition such that the plurality of data values remains stored by the original NVM elements.

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Palo Alto, CA, United States of America

Benjamin Feinberg