Disclosed herein are stacked transistors with different gate lengths in different device strata, as well as related methods and devices. In some embodiments, an integrated circuit structure may include stacked strata of transistors, with two different device strata having different gate lengths.

An apparatus and method for performing dual concurrent multiplications of packed data elements. For example one embodiment of a processor comprises: a decoder to decode a first instruction to generate a decoded instruction; a first source register to store a first plurality of packed doubleword data elements; a second source register to store a second plurality of packed doubleword data elements; and execution circuitry to execute the decoded instruction, the execution circuitry comprising: multiplier circuitry to multiply a first doubleword data element from the first source register with a second doubleword data element from the second source register to generate a first quadword product and to concurrently multiply a third doubleword data element from the first source register with a fourth doubleword data element from the second source register to generate a second quadword product; and a destination register to store the first quadword product and the second quadword product as first and second packed quadword data elements.

In a processing apparatus, a determination unit determines whether a jump destination address of a jump instruction in a process execution program being executed corresponds to a sensitive address region. When the determination unit determines that the jump destination address does not correspond to the sensitive address region, the security control unit executes control to allow the execution of the jump instruction and record a jump source address and the jump destination address of the jump instruction in jump history information as a jump execution record. When it is determined that the jump destination address corresponds to the sensitive address region, the security control unit searches for a “suspicious record” in the jump history information. The suspicious record is a jump execution record corresponding to an “unusual jump destination address”.

A device includes a vector register file, a memory, and a processor. The vector register file includes a plurality of vector registers. The memory is configured to store a permutation instruction. The processor is configured to access a periodicity parameter of the permutation instruction. The periodicity parameter indicates a count of a plurality of data sources that contain source data for the permutation instruction. The processor is also configured to execute the permutation instruction to, for each particular element of multiple elements of a first permutation result register of the plurality of vector registers, select a data source of the plurality of data sources based at least in part on the count of the plurality of data sources and populate the particular element based on a value in a corresponding element of the selected data source.

In various examples, a VPU and associated components may be optimized to improve VPU performance and throughput. For example, the VPU may include a min/max collector, automatic store predication functionality, a SIMD data path organization that allows for inter-lane sharing, a transposed load/store with stride parameter functionality, a load with permute and zero insertion functionality, hardware, logic, and memory layout functionality to allow for two point and two by two point lookups, and per memory bank load caching capabilities. In addition, decoupled accelerators may be used to offload VPU processing tasks to increase throughput and performance, and a hardware sequencer may be included in a DMA system to reduce programming complexity of the VPU and the DMA system. The DMA and VPU may execute a VPU configuration mode that allows the VPU and DMA to operate without a processing controller for performing dynamic region based data movement operations.

An encoding device and a decoding device use linear and nonlinear codes for encoding and decoding system data for a storage device. The encoding device includes a linear encoder for encoding first data to generate encoded data and a nonlinear transformer for transforming the encoded data with second data to generate output data. The first data includes data on a physical address corresponding to a logical address. The second data includes the logical address and a timestamp value indicating a version of map data mapping between the logical address and the physical address.

An apparatus to facilitate gathering payload from arbitrary registers for send messages in a graphics environment is disclosed. The apparatus includes processing resources comprising execution circuitry to receive a send gather message instruction identifying a number of registers to access for a send message and identifying IDs of a plurality of individual registers corresponding to the number of registers; decode a first phase of the send gather message instruction; based on decoding the first phase, cause a second phase of the send gather message instruction to bypass an instruction decode stage; and dispatch the first phase subsequently followed by dispatch of the second phase to a send pipeline. The apparatus can also perform an immediate move of the IDs of the plurality of individual registers to an architectural register of the execution circuitry and include a pointer to the architectural register in the send gather message instruction.

A method is provided that includes performing, by a processor in response to a floating point multiply instruction, multiplication of floating point numbers, wherein determination of values of implied bits of leading bit encoded mantissas of the floating point numbers is performed in parallel with multiplication of the encoded mantissas, and storing, by the processor, a result of the floating point multiply instruction in a storage location indicated by the floating point multiply instruction.

The present disclosure provides a computing method that is applied to a computing device. The computing device includes: a memory, a register unit, and a matrix computing unit. The method includes the following steps: controlling, by the computing device, the matrix computing unit to obtain a first operation instruction, where the first operation instruction includes a matrix reading instruction for a matrix required for executing the instruction; controlling, by the computing device, an operating unit to send a reading command to the memory according to the matrix reading instruction; and controlling, by the computing device, the operating unit to read a matrix corresponding to the matrix reading instruction in a batch reading manner, and executing the first operation instruction on the matrix. The technical solutions in the present disclosure have the advantages of fast computing speed and high efficiency.

One embodiment provides for a compute apparatus to perform machine learning operations, the compute apparatus comprising instruction decode logic to decode a single instruction including multiple operands into a single decoded instruction, the multiple operands including a first operand and a second operand, the first operand including vector of one-hot coded weights and the second operand including a vector of input data; and a general-purpose graphics compute unit including a first logic unit, the general-purpose graphics compute unit to execute the single decoded instruction, wherein to execute the single decoded instruction includes to perform multiple operations on the first set of operands and the second set of operands.