2188results about "Instruction analysis" patented technology

An artificial neural network calculating device for sparse connection comprises a mapping unit used for converting input data into the storage mode that input nerve cells and weight values correspond one by one, a storage unit used for storing data and instructions, and an operation unit used for executing corresponding operation on the data according to the instructions. The operation unit mainly executes three steps of operation, wherein in the first step, the input nerve cells and weight value data are multiplied; in the second step, addition tree operation is executed, the weighted output nerve cells processed in the first step are added level by level through an addition tree, or the output nerve cells are added with offset to obtain offset-added output nerve cells; in the third step, activation function operation is executed, and the final output nerve cells are obtained. By means of the device, the problems that the operation performance of a CPU and a GPU is insufficient, and the expenditure of front end coding is large are solved, support to a multi-layer artificial neural network operation algorithm is effectively improved, and the problem that memory bandwidth becomes a bottleneck of multi-layer artificial neural network operation and the performance of a training algorithm of the multi-layer artificial neural network operation is solved.

A new general method for building hybrid processors achieves higher performance in applications by allowing more powerful, tightly-coupled instruction set extensions to be implemented in reconfigurable logic. New instructions set configurations can be discovered and designed by automatic and semi-automatic methods. Improved reconfigurable execution units support deep pipelining, addition of additional registers and register files, compound instructions with many source and destination registers and wide data paths. New interface methods allow lower latency, higher bandwidth connections between hybrid processors and other logic.

The present invention relates to a general-purpose programmable packet-processing platform for accelerating network infrastructure applications which have been structured so as to separate the stages of classification and action. Network packet classification, execution of actions upon those packets, management of buffer flow, encryption services, and management of Network Interface Controllers are accelerated through the use of a multiplicity of specialized modules. A language interface is defined for specifying both stateless and stateful classification of packets and to associate actions with classification results in order to efficiently utilize these specialized modules.

A unified architecture for dynamic generation, execution, synchronization and parallelization of complex instructions formats includes a virtual register file, register cache and register file hierarchy. A self-generating and synchronizing dynamic and static threading architecture provides efficient context switching.

A microprocessor integrated circuit including a processing unit disposed upon an integrated circuit substrate is disclosed herein. The processing unit is designed to operate in accordance with a predefined sequence of program instructions stored within an instruction register. A memory, capable of storing information provided by the processing unit and occupying a larger area of the integrated circuit substrate than the processing unit, is also provided within the microprocessor integrated circuit. The memory may be implemented using, for example dynamic or static random-access memory. A variable output frequency system clock, such as generated by a ring oscillator, is also disposed on the integrated circuit substrate.

A data processing system having a data processing core and integrated pipelined array data processor and a buffer for storing list of algorithms for processing by the pipelined array data processor.

A data processing apparatus and method are provided for performing rearrangement operations. The data processing apparatus has a register data store with a plurality of registers, each register storing a plurality of data elements. Processing circuitry is responsive to control signals to perform processing operations on the data elements. An instruction decoder is responsive to at least one but no more than N rearrangement instructions, where N is an odd plural number, to generate control signals to control the processing circuitry to perform a rearrangement process at least equivalent to: obtaining as source data elements the data elements stored in N registers of said register data store as identified by the at least one re-arrangement instruction; performing a rearrangement operation to rearrange the source data elements between a regular N-way interleaved order and a de-interleaved order in order to produce a sequence of result data elements; and outputting the sequence of result data elements for storing in the register data store. This provides a particularly efficient technique for performing N-way interleave and de-interleave operations, where N is an odd number, resulting in high performance, low energy consumption, and reduced register use when compared with known prior art techniques.

An apparatus, method, and system are described herein for providing programmable control of performance/event counters. An event counter is programmable to track different events, as well as to be checkpointed when speculative code regions are encountered. So when a speculative code region is aborted, the event counter is able to be restored to it pre-speculation value. Moreover, the difference between a cumulative event count of committed and uncommitted execution and the committed execution, represents an event count/contribution for uncommitted execution. From information on the uncommitted execution, hardware/software may be tuned to enhance future execution to avoid wasted execution cycles.

A microprocessor configured to cache basic blocks of instructions is disclosed. The microprocessor may comprise decoding logic, a basic block cache, and a branch prediction unit. The decoding logic is coupled to receive and decode variable-length instructions into padded instructions that have one of a predetermined number of predetermined lengths. The decoding logic is further configured to form basic blocks of instructions from the padded and decoded instructions. Basic blocks are natural divisions in instruction streams resulting from branch instructions. The start of a basic block is a target of a branch, and the end is another branch instruction. The basic block cache is configured to store the basic blocks in a plurality of storage locations, wherein each storage location is configured to store an address tag, a link bit, and at least a portion of one basic block. The link bit indicates whether the basic block stored in said storage location extends into another storage location. The branch prediction unit has a branch prediction array storing branch prediction information corresponding to each storage location within the basic block cache. A computer system and method for operating are also disclosed.

A processor can achieve high code density while allowing higher performance than existing architectures, particularly for Digital Signal Processing (DSP) applications. In accordance with one aspect, the processor supports three possible instruction sizes while maintaining the simplicity of programming and allowing efficient physical implementation. Most of the application code can be encoded using two sets of narrow size instructions to achieve high code density. Adding a third (and larger, i.e. VLIW) instruction size allows the architecture to encode multiple operations per instruction for the performance critical section of the code. Further, each operation of the VLIW format instruction can optionally be a SIMD operation that operates upon vector data. A scheme for the optimal utilization (highest achievable performance for the given amount of hardware) of multiply-accumulate (MAC) hardware is also provided.

A matrix of execution blocks form a set of rows and columns. The rows support parallel execution of instructions and the columns support execution of dependent instructions. The matrix of execution blocks process a single block of instructions specifying parallel and dependent instructions.

A method and circuit arrangement provide support for a hybrid pipeline that dynamically switches between out-of-order and in-order modes. The hybrid pipeline may selectively execute instructions from at least one instruction stream that require the high performance capabilities provided by out-of-order processing in the out-of-order mode. The hybrid pipeline may also execute instructions that have strict power requirements in the in-order mode where the in-order mode conserves more power compared to the out-of-order mode. Each stage in the hybrid pipeline may be activated and fully functional when the hybrid pipeline is in the out-of-order mode. However, stages in the hybrid pipeline not used for the in-order mode may be deactivated and bypassed by the instructions when the hybrid pipeline dynamically switches from the out-of-order mode to the in-order mode. The deactivated stages may then be reactivated when the hybrid pipeline dynamically switches from the in-order mode to the out-of-order mode.

A group of bit set and bit clear instructions are provided for a microprocessor to allow atomic modification of privileged architecture control registers. The bit set and bit clear instructions include an opcode that designates to the microprocessor that the instructions are to execute in privileged (kernel) state only, and that the instructions are to communicate with privileged control registers. Two operands are provided for the instructions, the first designating which of the privileged control registers is to be modified, the second designating a general purpose register that contains a bit mask. The bit set instructions set bits in the designated control register according to bits set in the bit mask. The bit clear instructions clear bits in the designated control register according to bits set in the bit mask. By atomically modifying privileged control registers, a requirement for strict nesting of interrupt routines is eliminated.

A method for emulating a nexthop instruction in microcode with the assistance of dedicated hardware to extract read and write addressing from the nexthop instruction instead of performing this operation in microcode. A method for emulating a nexthop instruction in microcode with the assistance of dedicated hardware to compare a nexthop read address to a special value and to indicate whether the nexthop read address matches the special value, instead of performing this operation in microcode. A method for determining a network address by performing a single extraction of bit fields of a tree instruction to allow multiple tree search processes to be performed.

A processing system and method includes a predecoder configured to identify instructions that are combinable. Instruction storage is configured to merge instructions that are combinable by replacing the combinable instructions with a wide data internal instruction for execution. An instruction execution unit is configured to execute the internal instruction on a wide datapath.

The invention relates to a convolutional neural network hardware acceleration device, a convolution calculation method, and a storage medium. The device comprises an instruction processing unit, a hardware acceleration module and an external data memory unit, wherein the instruction processing unit decodes an instruction set to execute a corresponding operation so as to control the hardware acceleration module; the hardware acceleration module comprises an input caching unit, a data operation unit and an output caching unit, wherein the input caching unit executes the memory access operation of the instruction processing unit, and stores data read from the external data memory unit; the data operation unit executes the operation execution operation of the instruction processing unit, processes the data operation of the convolutional neural network, and controls a data operation process and a data flow direction according to an operation instruction set; the output caching unit executesthe memory access operation of the instruction processing unit, and stores a calculation result which is output by the data operation unit and needs to be written into the external data memory unit;and the external data memory unit stores a calculation result output by the output caching unit and transmits data to the input caching unit according to the reading of the input caching unit.

A programmable processor and method for improving the performance of processors by incorporating an execution unit operable to decode and execute single instructions specifying a data selection operand and a first and a second register providing a plurality of data elements, the data selection operand comprising a plurality of fields each selecting one of the plurality of data elements, the execution unit operable to provide the data element selected by each field of the data selection operand to a predetermined position in a catenated result.