Provided is a computation method of a memory processor configured to perform an operation between a first vector including first elements and a second vector including second elements, the first elements including respective first bits and the second elements including respective second bits, the method performed by the memory processor including: applying, to single-bit operation gates, the respective first bits and the respective second bits; obtaining bit operation result sum values for the respective first and second elements based on bit operation results obtained using the single-bit operation gates; and obtaining an operation result of the first vector and the second vector based on the bit operation result sum value.

Provided is a computation method of a memory processor configured to perform an operation between a first vector including first elements and a second vector including second elements, the first elements including respective first bits and the second elements including respective second bits, the method performed by the memory processor including: applying, to single-bit operation gates, the respective first bits and the respective second bits; obtaining bit operation result sum values for the respective first and second elements based on bit operation results obtained using the single-bit operation gates; and obtaining an operation result of the first vector and the second vector based on the bit operation result sum value.

The invention is notably directed to a computing system configured to perform linear algebraic operations. The computing system comprises a co-processing module comprising a co-processing unit. The co-processing unit comprises a parallel array of bit-serial processing units. The bit-serial processing units are adapted to perform the linear algebraic operations with variable precision. The invention further concerns a related computer implemented method and a related computer program product.

The invention is notably directed to a computing system configured to perform linear algebraic operations. The computing system comprises a co-processing module comprising a co-processing unit. The co-processing unit comprises a parallel array of bit-serial processing units. The bit-serial processing units are adapted to perform the linear algebraic operations with variable precision. The invention further concerns a related computer implemented method and a related computer program product.

A solid-state imaging device, a method for driving a solid-state imaging device, and an electronic apparatus are provided that are capable of reducing memory circuits of a column reading system, so that the column reading system can achieve a reduced layout area and eventually a reduced size. A column reading circuit includes an AD converting part and a calculating part. The AD converting part is configured to analog-to-digital convert a read-out reset signal and a read-out signal of a pixel signal read to a vertical signal line into an n-bit digital pixel signal. The calculating part includes an n-bit asynchronous counter including a retention circuit with a control logic function, which is configured to obtain a difference between an n-bit read-out reset signal and an n-bit read-out signal produced by the AD conversion performed by the AD converting part.

A four-input lookup table (LUT4) is modified to operate in a first mode as an ordinary LUT4 and in a second mode as a 1-bit adder providing a sum output and a carry output. A six-input lookup table (LUT6) is modified to operate in a first mode as an ordinary LUT6 with a single output and in a second mode as a 2-bit adder providing a sum output and a carry output. Both possible results for the two different possible carry inputs can be determined and selected between when the carry input is available, implementing a 2-bit carry-select adder when in the second mode and retaining the ability to operate as an ordinary LUT6 in the first mode. Using the novel LUT6 design in a circuit chip fabric allows a 2-bit adder slice to be built that efficiently makes use of the LUT6 without requiring additional logic blocks.

Various aspects of a system and method to process data in an adder based circuit, such as an integrated circuit, are disclosed herein. In accordance with an embodiment, a first addend is encoded as a first unary number. The first unary number comprises a token bit. A second addend is encoded as a second unary number. A first shift operation is performed on the token bit in the first unary number based on the second unary number. The first shift operation is performed to generate an output unary number. The generated output unary number is decoded to a number representation that corresponds to the number representation of the first addend and/or the second addend. The decoded number representation indicates a summation of the first addend and the second addend.

A processor and method for performing outer product and outer product accumulation operations on vector operands requiring large numbers of multiplies and accumulations is disclosed.

An example system includes a processor. The system also includes a peripheral interface that includes a controller communicatively coupled to the processor. The controller is to request information from a plurality of devices connected to the peripheral interface prior to the processor requesting the information. The controller is to provide the information to the processor.

An example system includes a processor. The system also includes a peripheral interface that includes a controller communicatively coupled to the processor. The controller is to request information from a plurality of devices connected to the peripheral interface prior to the processor requesting the information. The controller is to provide the information to the processor.