Abstract: Segment load operations are performed by processing data through an anything-to-anything mux, and sections writing elements to respective storage locations based on corresponding indices of the elements and the storage locations. Once all of the elements are loaded into the correct storage location, each location is read again with the elements of that storage location being sent through the mux, arranged) into the correct order, and written back to the same register.

Abstract: Disclosed are techniques for runtime adaptive prefetching in a many-core system. In an aspect, a method for runtime adaptive prefetching in a many-core system may include periodically performing the following steps: determining, for a first processor core in a many-core system, a workload classification based on at least one performance indicator of the first processor core; determining a first prefetching configuration from a plurality of prefetching configurations based on the workload classification; and configuring at least the first processor core according to the first prefetching configuration.

Abstract: Embodiments of systems, apparatuses, and methods for chained fused multiply add. In some embodiments, an apparatus includes a decoder to decode a single instruction having an opcode, a destination field representing a destination operand, a first source field representing a plurality of packed data source operands of a first type that have packed data elements of a first size, a second source field representing a plurality of packed data source operands that have packed data elements of a second size, and a field for a memory location that stores a scalar value. A register file having a plurality of packed data registers includes registers for the plurality of packed data source operands that have packed data elements of a first size, the source operands that have packed data elements of a second size, and the destination operand.

Abstract: Techniques are disclosed involving selection circuitry for stored operands. An embodiment of an apparatus includes a random-access storage element array and a permute network. The storage element array is configured to store a set of input data to an operation in a set of entries allocated among one or more execution lanes. The permute network is connected to each entry of the set of entries and is configured to select from among the set of entries to provide operands to one or more source inputs of execution circuitry configured to perform the operation. For a given source input, the permute network provides connection to only a subset of the entries that are allocated to a given execution lane. In a further embodiment, the permute network is configured to support multiple modes of the operation.

Abstract: Disclosed is a method for resetting configurable units in a reconfigurable processor with an array of configurable units and a force-quit controller on an integrated circuit substrate. The array includes multiple sub-arrays of configurable units. The method involves receiving a force-quit command at the force-quit controller and generating force-quit control signals to reset configurable units in a specific sub-array of the plurality of sub-arrays. The specific sub-array contains the force-quit controller. This method enhances the efficiency and reliability of reconfigurable processors by enabling targeted and controlled resets of configurable units within the reconfigurable processor architecture.

Abstract: A hardware accelerator is disclosed that can flexibly be configured to support differing data types and differing operation flows. The hardware accelerator includes a plurality of fixed tensor operation logic units, tensor operation pipeline logic configured to receive from the processor a pipeline command including a software-defined tensor operation pipeline definition defining a plurality of tensor operation stages in a tensor operation pipeline and associated predetermined tensor operations to be performed at each of the defined tensor operation stages. The hardware accelerator is further configured to receive tensor data to be computed by the tensor operation pipeline, and implement the tensor operation pipeline to perform the tensor operations in each of the tensor operation stages on the tensor data, to thereby produce a tensor operation pipeline result for the tensor data, and output the tensor operation pipeline result to the processor.

Abstract: At least one instruction storage coupled with a fetch unit including sets of fetch circuitry each having a same plurality of pipeline stages. The sets of fetch circuitry perform fetch operations to fetch blocks of instructions from the at least one instruction storage. Stall circuitry, in response to an indication of a hazard for a given pipeline stage of a first set of fetch circuitry, retains a fetch operation for a first block of instructions at the given pipeline stage, and zero or more fetch operations for zero or more corresponding blocks of instructions at zero or more preceding pipeline stages of the first set of fetch circuitry, until the hazard has been removed. The stall circuitry advances a fetch operation for a second block of instructions from the given pipeline stage of a second set of fetch circuitry, during an initial cycle of the one or more cycles.

Abstract: Systems, methods, and apparatuses for implementing capability informed prefetches are described.

Abstract: Techniques for shared data prefetch are described. An exemplary instruction for shared data prefetch includes at least one field for an opcode, at least one field for a source operand to provide a memory address at least a byte of data, wherein the opcode is to indicate that circuitry is to fetch of a line of data from memory at the provided address that contains the byte specified with the source operand and store that byte in at least a cache local to a requester, wherein the byte of data is to be stored in a shared state.

Abstract: Embodiments herein describe a hardware accelerator with an array of data processing engines (DPEs) which includes a controller (e.g., a microcontroller) for multiple columns of the array. The controllers can be hardened circuitry that executes software code (or firmware) that controls the hardware accelerator. In one embodiment, the task of the controller is to control and orchestrate the functions performed by the hardware accelerator.

Abstract: Techniques for using soft-barrier hints are described. An example includes a synchronous microthreading (SyMT) co-processor coupled to a logical processor to execute a plurality of microthreads, with each microthread having an independent register state, upon an execution of an instruction to enter into SyMT mode, wherein the SyMT co-processor is further to support a soft-barrier hint instruction in code which when processed by a microthread is to pause execution of the microthread to be resumed based at least in part on a data structure having at least one entry, the entry to include an instruction pointer of the soft-barrier hint instruction and a count of microthreads that have encountered the soft-barrier hint instruction at the instruction pointer.

Abstract: Embodiments of this application disclose an instruction translation method. The method includes: obtaining a return instruction of a function call instruction; obtaining a first address mapping result based on a second address indicated in the return instruction; storing the first address mapping result in a running stack space; and obtaining a first translation result of the return instruction, where the first translation result is a binary translation result of the return instruction, and the second translation result indicates to obtain, from a target location, an instruction indicated by the first address mapping result and execute the instruction. In this application, a running stack space of a source program is reused, thereby saving a storage space. In addition, an address of a return instruction does not need to be checked each time the return instruction is translated, thereby reducing overheads during translation and increasing program running efficiency.

Abstract: A system for Multi-Party Computation (MPC) includes a general-purpose programming language, an MPC processor, an MPC Instruction Set Architecture (ISA), and a compiler. The general-purpose programming language is used for writing an MPC application. The MPC processor executes the MPC application. The MPC ISA corresponds to the MPC processor. The compiler generates an intermediate representation for the MPC application and generates machine code for the intermediate representation by mapping and assembling MPC ISA instructions.

Abstract: Detailed herein are examples of instructions and their hardware support for floating-point comparison that makes use of the distinction between signed integer comparison and unsigned integer comparison to make an analogous distinction between floating-point relationships including unordered and those that do not. These instructions may reduce the number of instructions required to compare and conditionally execute operations in a program, including instructions to load values and instructions to explicitly test for the unordered condition.

Abstract: A system for efficient element-wise and cross-vector maximum operations. One example system includes an input bus, an output bus, and a memory configured to store N/K elements of an N-element vector in a corresponding row of the memory. A K-wide FMAX( ) comparator has a first set of K-wide inputs of the K-wide FMAX( ) comparator coupled to a read port of the memory and a second set of K-wide inputs of the K-wide FMAX( ) comparator coupled to the input bus, and a set of K-wide outputs of the K-wide FMAX( ) comparator coupled to a write port of the memory. A tree of FMAX( ) comparators comprises an input and an output, the input of the tree coupled to the set of K-wide outputs of the K-wide FMAX( ) comparator and the output of the tree coupled to the output bus.

Abstract: A system receives, by a network interface card (NIC), inputs including an instruction to read or write a payload of a message, a tracker state indicating a round of processing, and a datatype descriptor defining organization of the message payload. The system identifies a current context and a processing state for the instruction. If the datatype descriptor indicates a first type, the system: obtains the current context associated with the first type from a host memory or a cache of the NIC; and creates direct memory access (DMA) instructions corresponding to the received instruction by executing operations in a nested loop. If the datatype descriptor indicates a second type, the system: obtains the current context associated with the second type by fetching vector entries from a buffer of the NIC; and creates the DMA instructions corresponding to the received instruction based on addresses and lengths in the vector entries.

Abstract: Systems, apparatuses, and methods for implementing a hierarchical scheduler. In various implementations, a processor includes a global scheduler, and a plurality of independent local schedulers with each of the local schedulers coupled to a plurality of processors. In one implementation, the processor is a graphics processing unit and the processors are computation units. The processor further includes a shared cache that is shared by the plurality of local schedulers. Each of the local schedulers also includes a local cache used by the local scheduler and processors coupled to the local scheduler. To schedule work items for execution, the global scheduler is configured to store one or more work items in the shared cache and convey an indication to a first local scheduler of the plurality of local schedulers which causes the first local scheduler to retrieve the one or more work items from the shared cache.

Abstract: An electronic, digital data processor is adapted dynamically to develop for selected instructions received for execution in a pipelined execution unit a predetermined transform of the selected instructions. Depending on predetermined static or dynamic conditions that may exist in the pipelined execution unit, execution of the transform may be allowed or suppressed. The transform may be a fusion, a fracture or a binary transformation. A method is also disclosed for implementing this selective suppression of developed transforms.

Abstract: Embodiments are directed to a deterministic streaming system with one or more deterministic streaming processors each having an array of processing elements and a first deterministic memory coupled to the processing elements. The deterministic streaming system further includes a second deterministic memory with multiple data banks having a global memory address space, and a controller. The controller initiates retrieval of first data from the data banks of the second deterministic memory as a first plurality of streams, each stream of the first plurality of streams streaming toward a respective group of processing elements of the array of processing elements. The controller further initiates writing of second data to the data banks of the second deterministic memory as a second plurality of streams, each stream of the second plurality of streams streaming from the respective group of processing elements toward a respective data bank of the second deterministic memory.

Abstract: An apparatus comprises decoding circuitry configured to decode instructions; processing circuitry configured to perform data processing operations in response to the instructions decoded by the decoding circuitry; extension processing circuitry configured to perform a low-precision computation extension task asynchronously with respect to other data processing operations performed by the processing circuitry, the low-precision computation extension task comprising processing one or more sets of data elements for which at least one of the sets of data elements comprises low-precision data represented in a low-precision number format with lower precision than a single-precision floating-point format; and an extension task offload interface separate from an interface by which the processing circuitry issues a memory system request to a memory system, wherein the extension task offload interface is responsive to at least one task offloading instruction decoded by the decoding circuitry to offload the low-precisio