Abstract:
This disclosure provides a circuit that includes a ramp generator to apply a voltage ramp to a resistive memory cell. A sensing circuit can enable the ramp generator and monitor a current output received from the resistive memory cell in response to the applied voltage ramp, wherein the sensing circuit compares the current output to a predetermined current threshold to determine the state of the resistive memory cell.
Abstract:
Example implementations relate to performing active memory operations. In example implementations, a memory controller may be programmed such that the memory controller allocates more time for a standard memory operation than required by a timing specification of a memory communicatively coupled to the memory controller. Extra time that is allocated for the standard memory operation may be identified. An active memory operation may be performed during the extra time.
Abstract:
In an example, a method includes identifying, using at least one processor, data portions of a plurality of distinct data objects stored in at least one memory which are to be processed using the same logical operation. The method may further include identifying a representation of an operand stored in at least one memory, the operand being to provide the logical operation and providing a logical engine with the operand. The data portions may be stored in a plurality of input data buffers, wherein each of the input data buffers comprises a data portion of a different data object. The logical operation may be carried out on each of the data portions using the logical engine, and the outputs for each data portion may be stored in a plurality of output data buffers, wherein each of the outputs comprising data derived from a different data object.
Abstract:
In an example, a method includes receiving, in a memory, input data to be processed in a first and a second processing layer. A processing operation of the second layer may be carried out on an output of a processing operation of the first processing layer. The method may further include assigning the input data to be processed according to at least one processing operation of the first layer, which may comprise using a resistive memory array, and buffering output data. It may be determined whether the buffered output data exceeds a threshold data amount to carry out at least one processing operation of the second layer and when it is determined that the buffered output data exceeds the threshold data amount, at least a portion of the buffered output data may be assigned to be processed according to a processing operation of the second layer.
Abstract:
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.
Abstract:
Computer-implemented methods, systems, and devices to perform lossless compression of floating point format time-series data are disclosed. A first data value may be obtained in floating point format representative of an initial time-series parameter. For example, an output checkpoint of a computer simulation of a real-world event such as weather prediction or nuclear reaction simulation. A first predicted value may be determined representing the parameter at a first checkpoint time. A second data value may be obtained from the simulation. A prediction error may be calculated. Another predicted value may be generated for a next point in time and may be adjusted by the previously determined prediction error (e.g., to increase accuracy of the subsequent prediction). When a third data value is obtained, the adjusted prediction value may be used to generate a difference (e.g., XOR) for storing in a compressed data store to represent the third data value.
Abstract:
While scheduled checkpoints are being taken of a cluster of active compute nodes distributively executing an application in parallel, a likelihood of failure of the active compute nodes is periodically and independently predicted. Responsive to the likelihood of failure of a given active compute node exceeding a threshold, the given active compute node is proactively migrated to a spare compute node of the cluster at a next scheduled checkpoint. Another spare compute node of the cluster can perform prediction and migration. Prediction can be based on both hardware events and software events regarding the active compute nodes.
Abstract:
This disclosure provides a circuit that includes a ramp generator to apply a voltage ramp to a resistive memory cell. A sensing circuit can enable the ramp generator and monitor a current output received from the resistive memory cell in response to the applied voltage ramp, wherein the sensing circuit compares the current output to a predetermined current threshold to determine the state of the resistive memory cell.
Abstract:
According to an example, in a method for determining a resistance state of a cell in a crossbar memory array, a first read voltage may be applied across a cell to sense a first cell current. In addition, a second read voltage may be applied across the cell to sense a second cell current. A difference value between the first cell current and the second cell current may be identified and a resistance state of the cell may be determined based on the difference value.
Abstract:
A disclosed example apparatus includes a row address register (412) to store a row address corresponding to a row (608) in a memory array (602). The example apparatus also includes a row decoder (604) coupled to the row address register to assert a signal on a wordline (704) of the row after the memory receives a column address. In addition the example apparatus includes a column decoder (606) to selectively activate a portion of the raw based on the column address and the signal asserted on the wordline.