Abstract: In implementations of systems for cloud-based resource allocation using meters, a computing device implements a resource system to receive resource data describing an amount of cloud-based resources reserved for consumption by client devices during a period of time and a total amount of cloud-based resources consumed by the client devices during the period of time. The resource system determines a consumption distribution using each meter included in a set of meters. Each of the consumption distributions allocates a portion of the total amount of the cloud-based resources consumed to each client device of the client devices. A particular meter used to determine a particular consumption distribution is selected based on a Kendall Tau coefficient of the particular consumption distribution. An amount of cloud-based resources to allocate for a future period of time is estimated using the particular meter and an approximate Shapley value.

Abstract: Methods and apparatus to compensate impression data for misattribution and non-coverage are disclosed.

Abstract: There is disclosed an example of an artificial intelligence (AI) system, including: a first hardware platform; a fabric interface configured to communicatively couple the first hardware platform to a second hardware platform; a processor hosted on the first hardware platform and programmed to operate on an AI problem; and a first training accelerator, including: an accelerator hardware; a platform inter-chip link (ICL) configured to communicatively couple the first training accelerator to a second training accelerator on the first hardware platform without aid of the processor; a fabric ICL to communicatively couple the first training accelerator to a third training accelerator on a second hardware platform without aid of the processor; and a system decoder configured to operate the fabric ICL and platform ICL to share data of the accelerator hardware between the first training accelerator and second and third training accelerators without aid of the processor.

Abstract: A processor of an aspect includes a decode unit to decode a user-level suspend thread instruction that is to indicate a first alternate state. The processor also includes an execution unit coupled with the decode unit. The execution unit is to perform the instruction at a user privilege level. The execution unit in response to the instruction, is to: (a) suspend execution of a user-level thread, from which the instruction is to have been received; (b) transition a logical processor, on which the user-level thread was to have been running, to the indicated first alternate state; and (c) resume the execution of the user-level thread, when the logical processor is in the indicated first alternate state, with a latency that is to be less than half a latency that execution of a thread can be resumed when the logical processor is in a halt processor power state.

Abstract: An apparatus to facilitate utilizing structured sparsity in systolic arrays is disclosed. The apparatus includes a processor comprising a systolic array to receive data from a plurality of source registers, the data comprising unpacked source data, structured source data that is packed based on sparsity, and metadata corresponding to the structured source data; identify portions of the unpacked source data to multiply with the structured source data, the portions of the unpacked source data identified based on the metadata; and output, to a destination register, a result of multiplication of the portions of the unpacked source data and the structured source data.

Abstract: An embodiment of the invention is a processor including execution circuitry to calculate, in response to a decoded instruction, a result of a complex multiplication of a first complex number and a second complex number. The calculation includes a first operation to calculate a first term of a real component of the result and a first term of the imaginary component of the result. The calculation also includes a second operation to calculate a second term of the real component of the result and a second term of the imaginary component of the result. The processor also includes a decoder, a first source register, and a second source register. The decoder is to decode an instruction to generate the decoded instruction. The first source register is to provide the first complex number and the second source register is to provide the second complex number.

Abstract: Disclosed embodiments relate to instructions for fused multiply-add (FMA) operations with variable-precision inputs. In one example, a processor to execute an asymmetric FMA instruction includes fetch circuitry to fetch an FMA instruction having fields to specify an opcode, a destination, and first and second source vectors having first and second widths, respectively, decode circuitry to decode the fetched FMA instruction, and a single instruction multiple data (SIMD) execution circuit to process as many elements of the second source vector as fit into an SIMD lane width by multiplying each element by a corresponding element of the first source vector, and accumulating a resulting product with previous contents of the destination, wherein the SIMD lane width is one of 16 bits, 32 bits, and 64 bits, the first width is one of 4 bits and 8 bits, and the second width is one of 1 bit, 2 bits, and 4 bits.

Abstract: Methods, apparatuses, and systems for implementing data flows in a processor are described herein. A data flow manager may be configured to generate a configuration packet for a compute operation based on status information regarding multiple processing elements of the processor. Accordingly, multiple processing elements of a processor may concurrently process data flows based on the configuration packet. For example, the multiple processing elements may implement a mapping of processing elements to memory, while also implementing identified paths, through the processor, for the data flows. After executing the compute operation at certain processing elements of the processor, the processing results may be provided. In speech signal processing operations, the processing results may be compared to phonemes to identify such components of human speech in the processing results.

Abstract: The present disclosure provides an information processing apparatus capable of improving the accuracy of solving a problem when an annealing algorithm is executed. An information processing apparatus 1 includes a calculation unit 2 and an arithmetic unit 4. The calculation unit 2 calculates at least one eigenvector of a coupling coefficient matrix including a coupling coefficient indicating a strength of interaction between each of a plurality of binary variables that indicate states of a plurality of respective spins in an Ising model, the coupling coefficient matrix being given in advance in accordance with a problem to be solved by an annealing algorithm. The arithmetic unit 4 executes the annealing algorithm from an initial state set based on the at least one eigenvector.

Abstract: Embodiments of the present invention are directed to an instruction set of an object memory fabric. This object memory fabric instruction set can be used to define arbitrary, parallel functionality such as: direct object address manipulation and generation without the overhead of complex address translation and software layers to manage differing address space; direct object authentication with no runtime overhead that can be set based on secure 3rd party authentication software; object related memory computing in which, as objects move between nodes, the computing can move with them; and parallelism that is dynamically and transparent based on scale and activity. These instructions are divided into three conceptual classes: memory reference including load, store, and special memory fabric instructions; control flow including fork, join, and branches; and execute including arithmetic and comparison instructions.

Abstract: A digital data processor includes an instruction memory storing instructions each specifying a data processing operation and at least one data operand field, an instruction decoder coupled to the instruction memory for sequentially recalling instructions from the instruction memory and determining the data processing operation and the at least one data operand, and at least one operational unit coupled to a data register file and to an instruction decoder to perform a data processing operation upon at least one operand corresponding to an instruction decoded by the instruction decoder and storing results of the data processing operation. The operational unit is configured to increment histogram values in response to a histogram instruction by incrementing a bin entry at a specified location in a specified number of at least one histogram.

Abstract: Tile based interleaving and de-interleaving of row-column interleaved data is described. In one example, the de-interleaving is divided into two memory transfer stages, the first from an on-chip memory to a DRAM and the second from the DRAM to an on-chip memory. Each stage operates on part of a row-column interleaved block of data and re-orders the data items, such that the output of the second stage comprises de-interleaved data. In the first stage, data items are read from the on-chip memory according to a non-linear sequence of memory read addresses and written to the DRAM. In the second stage, data items are read from the DRAM according to bursts of linear address sequences which make efficient use of the DRAM interface and written back to on-chip memory according to a non-linear sequence of memory write addresses.

Abstract: Embodiments of the invention provide systems and methods to implement a hardware-based multi-node processing system of an object memory fabric. Hardware-based processing nodes operatively coupled may each include object memory modules storing and managing memory objects, each memory object being created natively within the memory module and managed by the memory module at a memory layer, and each memory object including memory object data and memory object metadata. The memory object metadata may include triggers that specify additional operations to be executed by any object memory module of the hardware-based processing nodes when the respective memory object is located at the respective object memory module and accessed as part of the respective object memory module processing requests.

Abstract: Embodiments of the invention provide systems and methods to implement an object memory fabric including hardware-based processing nodes having memory modules storing and managing memory objects created natively within the memory modules and managed by the memory modules at a memory layer, where physical address of memory and storage is managed with the memory objects based on an object address space that is allocated on a per-object basis with an object addressing scheme. Each node may utilize the object addressing scheme to couple to additional nodes to operate as a set of nodes so that all memory objects of the set are accessible based on the object addressing scheme, which defines invariant object addresses for the memory objects that are invariant with respect to physical memory storage locations and storage location changes of the memory objects within the memory module and across all modules interfacing the object memory fabric.

Abstract: A tile of an FPGA includes a multiple mode arithmetic circuit. The multiple mode arithmetic circuit is configured by control signals to operate in an integer mode, a floating-point mode, or both. In some example embodiments, multiple integer modes (e.g., unsigned, two's complement, and sign-magnitude) are selectable, multiple floating-point modes (e.g., 16-bit mantissa and 8-bit sign, 8-bit mantissa and 6-bit sign, and 6-bit mantissa and 6-bit sign) are supported, or any suitable combination thereof. The tile may also fuse a memory circuit with the arithmetic circuits. Connections directly between multiple instances of the tile are also available, allowing multiple tiles to be treated as larger memories or arithmetic circuits. By using these connections, referred to as cascade inputs and outputs, the input and output bandwidth of the arithmetic circuit is further increased.

Abstract: A method for using a distributed memory device in a memory augmented neural network system includes receiving, by a controller, an input query to access data stored in the distributed memory device, the distributed memory device comprising a plurality of memory banks. The method further includes determining, by the controller, a memory bank selector that identifies a memory bank from the distributed memory device for memory access, wherein the memory bank selector is determined based on a type of workload associated with the input query. The method further includes computing, by the controller and by using content based access, a memory address in the identified memory bank. The method further includes generating, by the controller, an output in response to the input query by accessing the memory address.

Abstract: A hybrid quantum-classical (HQC) computer prepares a quantum Boltzmann machine (QBM) in a pure state. The state is evolved in time according to a chaotic, tunable quantum Hamiltonian. The pure state locally approximates a (potentially highly correlated) quantum thermal state at a known temperature. With the chaotic quantum Hamiltonian, a quantum quench can be performed to locally sample observables in quantum thermal states. With the samples, an inverse temperature of the QBM can be approximated, as needed for determining the correct sign and magnitude of the gradient of a loss function of the QBM.

Abstract: There is disclosed an example of an artificial intelligence (AI) system, including: a first hardware platform; a fabric interface configured to communicatively couple the first hardware platform to a second hardware platform; a processor hosted on the first hardware platform and programmed to operate on an AI problem; and a first training accelerator, including: an accelerator hardware; a platform inter-chip link (ICL) configured to communicatively couple the first training accelerator to a second training accelerator on the first hardware platform without aid of the processor; a fabric ICL to communicatively couple the first training accelerator to a third training accelerator on a second hardware platform without aid of the processor; and a system decoder configured to operate the fabric ICL and platform ICL to share data of the accelerator hardware between the first training accelerator and second and third training accelerators without aid of the processor.

Abstract: Techniques for performing instruction fetch operations are provided. The techniques include determining instruction addresses for a primary branch prediction path; requesting that a level 0 translation lookaside buffer (“TLB”) caches address translations for the primary branch prediction path; determining either or both of alternate control flow path instruction addresses and lookahead control flow path instruction addresses; and requesting that either the level 0 TLB or an alternative level TLB caches address translations for either or both of the alternate control flow path instruction addresses and the lookahead control flow path instruction addresses.

Abstract: The present invention provides a technology for invoking a non-periodic-execution function module from a periodic-execution control program. A control system that comprises first and second control parts (C1, C2) and a storage device that stores control programs (210, 211) for a controller. The control programs (210, 211) include a periodic-execution function module (55B) that invokes a non-periodic-execution function module (55A). The first control part (C1) reflects the value of an input variable for the periodic-execution function module (55B) in an argument for the non-periodic-execution function module (55A) and outputs an execution start command for the function modules to the second control part (C2). The second control part (C2) outputs a return value for the non-periodic-execution function module (55A) to the first control part (C1). The first control part (C1) reflects the return value in an output variable for the periodic-execution function module (55B).

Abstract: Embodiments of the invention provide systems and methods for managing processing, memory, storage, network, and cloud computing to significantly improve the efficiency and performance of processing nodes. More specifically, embodiments of the present invention are directed to an instruction set of an object memory fabric. This object memory fabric instruction set can include trigger instructions defined in metadata for a particular memory object. Each trigger instruction can comprise a single instruction and action based on reference to a specific object to initiate or perform defined actions such as pre-fetching other objects or executing a trigger program.

Abstract: Methods and apparatus to compensate impression data for misattribution and non-coverage are disclosed.

Abstract: A method and system perform quantum-assisted finite elements-based, design optimization of an object to minimize a shape-specific quantity by manipulating the shape of the object using a processing unit, for example, a Quantum Processing Unit (QPU). As a result, a shape-specific quantity, such as an approximation of sound pressure at a specific position around an object, can be minimized by manipulating the object shape using the QPU.

Abstract: A digital data processor includes an instruction memory storing instructions specifying data processing operations and a data operand field, an instruction decoder coupled to the instruction memory for recalling instructions from the instruction memory and determining the operation and the data operand, and an operational unit coupled to a data register file and an instruction decoder to perform an operation upon an operand corresponding to an instruction decoded by the instruction decoder and storing results of the operation. The operational unit is configured to perform a table recall in response to a look up table read instruction by recalling data elements from a specified location and adjacent location to the specified location, in a specified number of at least one table and storing the recalled data elements in successive slots in a destination register. Recalled data elements include at least one interpolated data element in the adjacent location.

Abstract: The present invention provides an environment that makes it possible to incorporate a non-periodic-execution function module into a periodic-execution control program. A development support program that makes a computer execute steps that generate a periodic-execution second function module that invokes a non-periodic-execution first function module. Said steps include: a step in which a data type that is in a periodic-execution programming language and corresponds to the data type of an argument for the first function module is specified, and an input variable of said data type is established for the second function module; and a step in which a data type that is in a periodic-execution programming language and corresponds to the data type of a return value for the first function module is specified, and an output variable of said data type is established for the second function module.

Abstract: There is disclosed an example of an artificial intelligence (AI) system, including: a first hardware platform; a fabric interface configured to communicatively couple the first hardware platform to a second hardware platform; a processor hosted on the first hardware platform and programmed to operate on an AI problem; and a first training accelerator, including: an accelerator hardware; a platform inter-chip link (ICL) configured to communicatively couple the first training accelerator to a second training accelerator on the first hardware platform without aid of the processor; a fabric ICL to communicatively couple the first training accelerator to a third training accelerator on a second hardware platform without aid of the processor; and a system decoder configured to operate the fabric ICL and platform ICL to share data of the accelerator hardware between the first training accelerator and second and third training accelerators without aid of the processor.

Abstract: There is disclosed an example of an artificial intelligence (AI) system, including: a first hardware platform; a fabric interface configured to communicatively couple the first hardware platform to a second hardware platform; a processor hosted on the first hardware platform and programmed to operate on an AI problem; and a first training accelerator, including: an accelerator hardware; a platform inter-chip link (ICL) configured to communicatively couple the first training accelerator to a second training accelerator on the first hardware platform without aid of the processor; a fabric ICL to communicatively couple the first training accelerator to a third training accelerator on a second hardware platform without aid of the processor; and a system decoder configured to operate the fabric ICL and platform ICL to share data of the accelerator hardware between the first training accelerator and second and third training accelerators without aid of the processor.

Abstract: The present disclosure relates to a method for executing a computation task composed of at least one set of operations where subsets of pipelineable operations of the set of operations are determined in accordance with a pipelining scheme. A single routine may be created for enabling execution of the determined subsets of operations by a hardware accelerator. The routine has, as arguments, a value indicative of input data and values of configuration parameters of the computation task, where a call of the routine causes a scheduling of the subsets of operations on the hardware accelerator in accordance with the values of the configuration parameters. Upon receiving input data of the computation task, the routine may be called to cause the hardware accelerator to perform by the computation task in accordance with the scheduling.

Abstract: A hybrid computer generates samples for machine learning. The hybrid computer includes a processor that implements a Boltzmann machine, e.g., a quantum Boltzmann machine, which returns equilibrium samples from eigenstates of a quantum Hamiltonian. Subsets of samples are provided to training and validations modules. Operation can include: receiving a training set; preparing a model described by an Ising Hamiltonian; initializing model parameters; segmenting the training set into subsets; creating a sample set by repeatedly drawing samples until the determined number of samples has been drawn; and updating the model. Operation can include partitioning the training set into input and output data sets, and determining a conditional probability distribution that describes a probability of observing an output vector given a selected input vector, e.g.

Abstract: A processor of an aspect includes a decode unit to decode a user-level suspend thread instruction that is to indicate a first alternate state. The processor also includes an execution unit coupled with the decode unit. The execution unit is to perform the instruction at a user privilege level. The execution unit in response to the instruction, is to: (a) suspend execution of a user-level thread, from which the instruction is to have been received; (b) transition a logical processor, on which the user-level thread was to have been running, to the indicated first alternate state; and (c) resume the execution of the user-level thread, when the logical processor is in the indicated first alternate state, with a latency that is to be less than half a latency that execution of a thread can be resumed when the logical processor is in a halt processor power state.

Abstract: In some aspects, a control system interacts with a quantum system. In some instances, the quantum system includes qubits that respond to a control signal generated by the control system, and the control system is configured to generate the control signal in response to an input signal. A control sequence (which may include, for example, a sequence of values for the input signal) can be generated by a computing system based on a target operation to be applied to the qubits. The control sequence can be generated based on the target operation, a quantum system model, a distortion model and possibly other information. The quantum system model represents the quantum system and includes a control parameter representing the control signal. The distortion model represents a nonlinear relationship between the control signal and the input signal. The control sequence is applied to the quantum system by operation of the control system.

Abstract: An information processing apparatus manufactured at low cost and with ease and that is capable of making a search for a ground state of an arbitrary Ising model. An information processing unit containing a plurality of semiconductor chips, each retains a value of one spin or values of a plurality of spins and simulates interactions among the spins, inter-chip wiring between the necessary semiconductor chips, and a control unit that cause each semiconductor chip to perform interaction computation. The control unit converts data of a problem into data of a lattice-shaped Ising model, which is possibly expressed by the plurality of semiconductor chips, without causing a spin arrangement, in a ground state of an Ising model for the problem, to be changed. The data of the lattice-shaped Ising model is divided for allocation to the plurality of semiconductor chips, and causes each semiconductor chip to perform the interaction computation.

Abstract: Techniques relate to operating a quantum processing device is provided. The device includes at least two fixed-frequency quantum circuits coupled to a frequency-tunable coupler. The frequency of the coupler can be modulated so as to drive at least two selectively addressable energy transitions in the quantum processing device. The method includes modulating the frequency of the coupler so as to drive two first-order energy transitions. This is done so as to transfer (at least partly) an excitation of one of the quantum circuits to at least another one of the quantum circuits, via the tunable coupler. Related quantum processing devices are also provided.

Abstract: A semiconductor memory device includes a memory core that performs reading and writing of data, data delivery and training blocks that are connected between first pads and the memory core, and at least one data delivery, clock generation and training block that is connected between at least one second pad and the memory core. In a first training operation, the data delivery and training blocks output first training data, received through the first pads, through the first pads as second training data. In a second training operation, at least one of the data delivery and training blocks outputs third training data, received through the at least one second pad, through at least one of the first pads as fourth training data. The second training data and the fourth training data are output in synchronization with read data strobe signals output through the at least one second pad.

Abstract: A computer-implemented method includes receiving a first circuit design for an integrated circuit device, determining when multiple power-drawing events are to occur at substantially the same time via one or more circuitry components of the integrated circuit device, which would have a disruptive effect on a power distribution network of the integrated circuit device, based on the first circuit design, and generating logic that schedules the more than one event so that the more than one event do not occur simultaneously. The logic is included in an event sequencer. The method also includes inserting the event sequencer into the first circuit design during compilation to create a second circuit design and outputting the second circuit design to be implemented on the integrated circuit device.

Abstract: Display data used in display frame generation are compressed for efficient storage in a local memory within a graphics processing unit. The compression technique used is difference encoding and before performing difference encoding, display data in RGB format are converted into YCbCr format. Since the component values of adjacent pixels in YCbCr format typically vary less than the component values of the same adjacent pixels in RGB format, converting the display data to YCbCr format before performing difference encoding improves the compression efficiency.

Abstract: Provided are an application booting system and method that control a booting time and booting order of each application installed in a terminal (for example, an AVN) according to an importance of each application. The application booting system and method generate or update priority information of each application on the basis of an execution time and the number of executions of each application installed in the terminal, and when power is supplied to the terminal, the application booting system and method control an application to be booted according to the priority information while a system of the terminal is being booted. Accordingly, the application booting system and method enhance a booting speed of a whole system, and provide an execution convenience of an application having a high importance after booting of the system is completed.

Abstract: Provided are a computer program product, system, and method for concurrently processing parts of cells of a data structure with multiple processes. Information is provided to indicate a partitioning of the cells of the data structure into a plurality of parts, and having a cursor pointing to a cell in the part. Processes concurrently process different parts of the data structure by performing: determining from the cursor for the part one of the cells in the part to process; processing the cells from the cursor to determine whether to process the unit of work corresponding to the cell; and setting the cursor to identify one of the cells from which processing is to continue in a subsequent iteration in response to processing the units of work for a plurality of the processed cells.

Abstract: A system and method to evaluate a data value as an instruction is disclosed. For example, an apparatus configured to execute program code includes an execute unit configured to execute a first instruction associated with a location of a second instruction. The first instruction is identified by a program counter. The apparatus also includes a decode unit configured to receive the second instruction from the location and to decode the second instruction to generate a decoded second instruction without changing the program counter to point to the second instruction.

Abstract: Augmented processor hardware contains a microcode interpreter. When encrypted microcode is included in a message from a service, the microcode may be passed to the microcode interpreter. Based on decryption and execution of the microcode taking place at the processor hardware, extended functionality may be realized.

Abstract: A method for securing a data processing system having a processing unit is disclosed. At least a group of N1 digital words of m1 bits is selected from among the set of M1 digital words. N1 is less than M1. These words are selected in such a way that each selected digital word differs from all the other selected digital words by a number of bits at least equal to an integer p which is at least equal to 2. The group of N1 digital words of m1 bits form at least one group of N1 executable digital instructions. The processing unit is configured to make it capable of executing each instruction of the at least one group of N1 executable digital instructions.

Abstract: An apparatus and method are described for the efficient migration of architectural state between processor cores. For example, a processor according to one embodiment comprises: a first processing core having a first instruction execution pipeline including first register set for storing a first architectural state of a first thread being executed thereon; a second processing core having a second instruction execution pipeline including a second register set for storing a second architectural state of a second thread being executed thereon; and architectural state migration logic to perform a direct, simultaneous swap of the first architectural state from the first register set with the second architectural state from the second register set responsive to detecting that the execution of the first thread is to be migrated from the first core to the second core.

Abstract: A microprocessor includes a plurality of registers that holds an architectural state of the microprocessor and an indicator that indicates a boot instruction set architecture (ISA) of the microprocessor as either the x86 ISA or the Advanced RISC Machines (ARM) ISA. The microprocessor also includes a hardware instruction translator that translates x86 ISA instructions and ARM ISA instructions into microinstructions. The hardware instruction translator translates, as instructions of the boot ISA, the initial ISA instructions that the microprocessor fetches from architectural memory space after receiving a reset signal. The microprocessor also includes an execution pipeline, coupled to the hardware instruction translator. The execution pipeline executes the microinstructions to generate results defined by the x86 ISA and ARM ISA instructions.

Abstract: Quantum processor architectures employ unit cells tiled over an area. A unit cell may include first and second sets of qubits where each qubit in the first set crosses at least one qubit in the second set. Angular deviations between qubits in one set may allow qubits in the same set to cross one another. Each unit cell is positioned proximally adjacent at least one other unit cell. Communicatively coupling between qubits is realized through respective intra-cell and inter-cell coupling devices.

Abstract: Method of generating respective instruction compaction schemes for subsets of instructions to be processed by a programmable processor, comprising the steps of a) receiving at least one input code sample representative for software to be executed on the programmable processor, the input code comprising a plurality of instructions defining a first set of instructions (S1), b) initializing a set of removed instructions as empty (S3), c) determining the most compact representation of the first set of instructions (S4) d) comparing the size of said most compact representation with a threshold value (S5), e) carrying out steps e1 to e3 if the size is larger than said threshold value, e1) determining which instruction of the first set of instructions has a highest coding cost (S6), e2) removing said instruction having the highest coding cost from the first set of instructions and (S7), e3) adding said instruction to the set of removed instructions (S8), f) repeating steps b-f, wherein the first set of instructions

Abstract: Techniques for improving the performance of a quantum processor are described. Some techniques employ improving the processor topology through design and fabrication, reducing intrinsic/control errors, reducing thermally-assisted errors and methods of encoding problems in the quantum processor for error correction.

Abstract: Achieving orthogonal control of non-orthogonal qubit parameters of a logical qubit allows for increasing the length of a qubit chain thereby increasing the effective connectivity of the qubit chain. A hybrid qubit is formed by communicatively coupling a dedicated second qubit to a first qubit. By tuning a programmable parameter of the second qubit of a hybrid qubit, an effective programmable parameter of the hybrid qubit is adjusted without affecting another effective programmable parameter of the hybrid qubit thereby achieving orthogonal control of otherwise non-orthogonal qubit parameters. The length of the logical qubit may thus be increased by communicatively coupling a plurality of such hybrid qubits together.

Abstract: The present invention provides systems and methods for coupled dynamical systems for chaos computing. For example, a system for the coupled dynamical system comprises a first, second, and third circuit. The first circuit comprising a plurality of single dynamical systems forms a coupled dynamical system that reduces local noises in the plurality of single dynamical systems by diffusing the local noises across the coupled dynamical system. The second circuit, connected to the first circuit, receives the data and control inputs and builds an encoding map that translates the data and control inputs to an initial condition on an unstable manifold of the plurality of single dynamical systems in the coupled dynamical system. After the coupled dynamical system evolves, a third circuit, connected to the first circuit, samples a state of one of the plurality of single dynamical systems in the coupled dynamical system and builds a decoding map.

Abstract: A processor saves micro-architectural contexts to increase the efficiency of code execution and power management. Power management hardware during runtime monitors execution of a code block. The code block has been compiled to have a reserved space appended to one end of the code block. The reserved space includes a metadata block associated with the code block or an identifier of the metadata block. The hardware stores a micro-architectural context of the processor in the metadata block. The micro-architectural context includes performance data resulting from a first execution of the code block. The hardware reads the metadata block upon a second execution of the code block and tunes the second execution based on the performance data.

Abstract: A semiconductor memory device includes a memory core that performs reading and writing of data, data delivery and training blocks that are connected between first pads and the memory core, and at least one data delivery, clock generation and training block that is connected between at least one second pad and the memory core. In a first training operation, the data delivery and training blocks output first training data, received through the first pads, through the first pads as second training data. In a second training operation, at least one of the data delivery and training blocks outputs third training data, received through the at least one second pad, through at least one of the first pads as fourth training data. The second training data and the fourth training data are output in synchronization with read data strobe signals output through the at least one second pad.