Certain aspects of the present disclosure provide techniques for performing machine learning computations in a compute in memory (CIM) array comprising a plurality of bit cells, including: determining that a sparsity of input data to a machine learning model exceeds an input data sparsity threshold; disabling one or more bit cells in the CIM array based on the sparsity of the input data prior to processing the input data; processing the input data with bit cells not disabled in the CIM array to generate an output value; applying a compensation to the output value based on the sparsity to generate a compensated output value; and outputting the compensated output value.

A MAC operator includes a plurality of multipliers, a plurality of floating-point to fixed-point converters, an adder tree, an accumulator, and a fixed-point to floating-point converter. Each of the plurality of multipliers may perform a multiplication operation on first data and second data of a single-precision floating-point (FP32) format to output multiplication result data of the FP 32 format. Each of the plurality of floating-point to fixed-point converters may convert the FP 32 format into a fixed-point format. The adder tree may perform a first addition operation on the data of the fixed-point format. The accumulator may perform an accumulation operation on the data output from the adder tree. And the fixed-point to floating-point converter may convert the data of the fixed-point format into data of the FP32 format.

A discrete three-dimensional (3-D) processor comprises first and second dice. The first die comprises 3-D memory (3D-M) arrays, whereas the second die comprises logic circuits and at least an off-die peripheral-circuit component of the 3D-M array(s). Typical off-die peripheral-circuit component could be an address decoder, a sense amplifier, a programming circuit, a read-voltage generator, a write-voltage generator, a data buffer, or a portion thereof.

A discrete three-dimensional (3-D) processor comprises stacked first and second dice. The first die comprises three-dimensional memory (3D-M) arrays, whereas the second die comprises at least a portion of a logic/processing circuit and an off-die peripheral-circuit component of the 3D-M array(s). The preferred 3-D processor can be used to compute non-arithmetic function/model. In other applications, the preferred 3-D processor may also be a 3-D configurable computing array, a 3-D pattern processor, or a 3-D neuro-processor.

Provided are systems, methods, and apparatuses for managing storage device memory. A method can include receiving, from a host, a command for managing the memory; performing, by the storage device, the command on first data stored on the memory via at least one processing element in the storage device to generate second data; and transmitting, by the storage device, third data based on the second data to the host.

The present disclosure includes apparatuses and methods for in data path compute operations. An example apparatus includes an array of memory cells. Sensing circuitry is selectably coupled to the array. A plurality of shared input/output (I/O) lines provides a data path. The plurality of shared I/O lines selectably couples a first subrow of a row of the array via the sensing circuitry to a first compute component in the data path to move a first data value from the first subrow to the first compute component and a second subrow of the respective row via the sensing circuitry to a second compute component to move a second data value from the second subrow to the second compute component. An operation is performed on the first data value from the first subrow using the first compute component substantially simultaneously with movement of the second data value from the second subrow to the second compute component.

A memory device includes a memory having a memory bank, a processor in memory (PIM) circuit, and control logic. The PIM circuit includes instruction memory storing at least one instruction provided from a host. The PIM circuit is configured to process an operation using data provided by the host or data read from the memory bank and to store at least one instruction provided by the host. The control logic is configured to decode a command/address received from the host to generate a decoding result and to perform a control operation so that one of i) a memory operation on the memory bank is performed and ii) the PIM circuit performs a processing operation, based on the decoding result. A counting value of a program counter instructing a position of the instruction memory is controlled in response to the command/address instructing the processing operation be performed.

A computing device includes an array of processing elements mutually connected to perform single instruction multiple data (SIMD) operations, memory cells connected to each processing element to store data related to the SIMD operations, and a cache connected to each processing element to cache data related to the SIMD operations. Caches of adjacent processing elements are connected. The same or another computing device includes rows of mutually connected processing elements to share data. The computing device further includes a row arithmetic logic unit (ALU) at each row of processing elements. The row ALU of a respective row is configured to perform an operation with processing elements of the respective row.

A data processing apparatus and method are disclosed. The data processing apparatus may include a host core configured to generate a control message to control a direct memory access (DMA), the DMA configured to generate a memory request based on the control message, a memory controller configured to generate a memory command based on the memory request, and a processor configured to perform an operation in a memory based on the memory command.

Disclosed is a memory device including a plurality of memory banks, each of which performs an operation based on first operand data including pieces of first unit data and second operand data including pieces of second unit data and a processing in-memory interface unit (PIM IU) that delivers signals for an operation request to the plurality of memory banks. Each of the plurality of memory banks includes a memory cell array configured to store one of the pieces of first unit data and a PIM engine that reads the one of the pieces of first unit data from the memory cell array, reads the pieces of second unit data broadcast to the plurality of memory banks, and generates an operation result by performing an operation based on the one of the pieces of first unit data and the pieces of second unit data.