Abstract: A superconducting multi-stage synchronous logic circuit structure includes a first clocked logic gate, a second clocked logic gate, and an unclocked logic gate. Each of the logic gates includes Josephson junctions. The first clocked logic gate has a single first clocked logic gate output; the second clocked logic gate has a single second clocked logic gate output. The unclocked logic gate has a first input connected in electrical communication with the first clocked logic gate output and has a second input connected in electrical communication with the second clocked logic gate output, and has a single output. The Josephson junctions of the unclocked logic gate are arranged such that, in a single clock cycle that drives the first clocked logic gate and the second clocked logic gate, the unclocked logic gate produces a single signal in response to the inputs of the first and second clocked logic gates.

Abstract: Systems and methods for optimizing a pipeline are described. A system can generate at least one pair of single flux quantum (SFQ) clock signals based on a stream of SFQ pulses. Each pair of SFQ clock signals can include a first SFQ clock signal and a second SFQ clock signal that is out of phase with the first SFQ clock signal. The second SFQ clock signal can have the same frequency as the first SFQ clock signal. The system can define, for each pair of SFQ clock signals, a first clock cycle and a second clock cycle based on the first SFQ clock signal and the second SFQ clock signal. The second clock cycle can be greater than the first clock cycle. The system can assign the first and second clock cycles to different stages of a pipeline based on delays by the different stages.

Abstract: A system and method for supporting an interconnection of processor cores, each core with functional state monitors for monitoring operations of each processor core, the processor cores interconnected using a resistive network connected between two-terminal regions being embedded in the resistive network such that each terminal of a region may be connected by controllable resistors to one or both fixed rails or by controllable resistors to one or more intermediate nodes. The resistor values are configurable to provide indirect control of the voltages across each two-terminal region, allowing full dynamic control of voltages of the two-terminal regions in a range up to the full voltage between the two voltage rails, and where a management unit accesses the functional state monitors and controls the resistor values. Feedback from functional state monitors allow the operating frequency to extend down to arbitrarily low values and up to the limits imposed by the technology.

Abstract: Embodiments of the invention relate to a time-division multiplexed neurosynaptic module with implicit memory addressing for implementing a neural network. One embodiment comprises maintaining neuron attributes for multiple neurons and maintaining incoming firing events for different time steps. For each time step, incoming firing events for said time step are integrated in a time-division multiplexing manner. Incoming firing events are integrated based on the neuron attributes maintained. For each time step, the neuron attributes maintained are updated in parallel based on the integrated incoming firing events for said time step.

Abstract: Systems and methods are provided for executing an instruction. The method may include loading a first vector into a first location, the first vector including a plurality of first data elements and loading a second vector into a second location, the second vector including a plurality of second data elements. The method may further include comparing the plurality of first data elements of the first vector to the plurality of data elements of the second vector and performing one or more operations on the plurality of first and second data elements based on at least one vector cross-compare instruction. The one or more operations include counting a number of data elements of the plurality of first and second data elements that satisfy at least one condition, counting a number of times specified values occur in the plurality of first and second data elements, and generating sequence counts for duplicated values.

Abstract: A reconfigurable neural network circuit is provided. The reconfigurable neural network circuit comprises an electronic synapse array including multiple synapses interconnecting a plurality of digital electronic neurons. Each neuron comprises an integrator that integrates input spikes and generates a signal when the integrated inputs exceed a threshold. The circuit further comprises a control module for reconfiguring the synapse array. The control module comprises a global final state machine that controls timing for operation of the circuit, and a priority encoder that allows spiking neurons to sequentially access the synapse array.

Abstract: A reconfigurable neural network circuit is provided. The reconfigurable neural network circuit comprises an electronic synapse array including multiple synapses interconnecting a plurality of digital electronic neurons. Each neuron comprises an integrator that integrates input spikes and generates a signal when the integrated inputs exceed a threshold. The circuit further comprises a control module for reconfiguring the synapse array. The control module comprises a global final state machine that controls timing for operation of the circuit, and a priority encoder that allows spiking neurons to sequentially access the synapse array.

Abstract: Systems and methods are provided for executing an instruction. The method may include loading a first vector into a first location, the first vector including a plurality of first data elements and loading a second vector into a second location, the second vector including a plurality of second data elements. The method may further include comparing the plurality of first data elements of the first vector to the plurality of data elements of the second vector and performing one or more operations on the plurality of first and second data elements based on at least one vector cross-compare instruction. The one or more operations include counting a number of data elements of the plurality of first and second data elements that satisfy at least one condition, counting a number of times specified values occur in the plurality of first and second data elements, and generating sequence counts for duplicated values.

Abstract: Systems and methods are provided for executing an instruction. The method may include loading a first vector into a first location, the first vector including a plurality of first data elements and loading a second vector into a second location, the second vector including a plurality of second data elements. The method may further include comparing the plurality of first data elements of the first vector to the plurality of data elements of the second vector and performing one or more operations on the plurality of first and second data elements based on at least one vector cross-compare instruction. The one or more operations include counting a number of data elements of the plurality of first and second data elements that satisfy at least one condition, counting a number of times specified values occur in the plurality of first and second data elements, and generating sequence counts for duplicated values.

Abstract: Embodiments of the invention relate to a time-division multiplexed neurosynaptic module with implicit memory addressing for implementing a neural network. One embodiment comprises maintaining neuron attributes for multiple neurons and maintaining incoming firing events for different time steps. For each time step, incoming firing events for said time step are integrated in a time-division multiplexing manner. Incoming firing events are integrated based on the neuron attributes maintained. For each time step, the neuron attributes maintained are updated in parallel based on the integrated incoming firing events for said time step.

Abstract: Embodiments of the invention relate to a time-division multiplexed neurosynaptic module with implicit memory addressing for implementing a neural network. One embodiment comprises maintaining neuron attributes for multiple neurons and maintaining incoming firing events for different time steps. For each time step, incoming firing events for said time step are integrated in a time-division multiplexing manner. Incoming firing events are integrated based on the neuron attributes maintained. For each time step, the neuron attributes maintained are updated in parallel based on the integrated incoming firing events for said time step.

Abstract: Systems and methods are provided for executing an instruction. The method may include loading a first vector into a first location, the first vector including a plurality of first data elements and loading a second vector into a second location, the second vector including a plurality of second data elements. The method may further include comparing the plurality of first data elements of the first vector to the plurality of data elements of the second vector and performing one or more operations on the plurality of first and second data elements based on at least one vector cross-compare instruction. The one or more operations include counting a number of data elements of the plurality of first and second data elements that satisfy at least one condition, counting a number of times specified values occur in the plurality of first and second data elements, and generating sequence counts for duplicated values.

Abstract: An apparatus for providing on-chip voltage-regulated power includes a switched capacitor voltage conversion circuit that receives an elevated power demand signal and operates at a base rate when the elevated power demand signal is not active and at an elevated rate when the elevated power demand signal is active. The switched capacitor voltage conversion circuit comprises an auxiliary set of transistors that are disabled, when the elevated power demand signal is not active and enabled, when the elevated power demand signal is active. The apparatus may also include a droop detection circuit that monitors a monitored power signal and activates the elevated power demand signal in response to the monitored power signal dropping below a selected voltage level. The monitored power signal may be a voltage input provided by an input power supply for the switched capacitor voltage conversion circuit. A corresponding method is also disclosed herein.

Abstract: An apparatus for storing data includes a latch circuit comprising a first set of transistors that propagate an input signal to an output signal and a second set of transistors that do not propagate the input signal of the latch circuit to the output signal wherein a gate pitch for the first set of transistors is substantially greater than a gate pitch for the second set of transistors. Also disclosed herein, a method for improving circuit performance includes receiving an electronic representation of a plurality of latching circuits associated with a design file and increasing transistor gate pitch for selected transistors of the plurality of latching circuits, wherein the selected transistors comprise transistors that propagate an input signal to an output signal. The method may also include fabricating a chip comprising the plurality of latching circuits. A computer program product corresponding to the method is also disclosed within.

Abstract: Embodiments of the invention relate to a time-division multiplexed neurosynaptic module with implicit memory addressing for implementing a universal substrate of adaptation. One embodiment comprises a neurosynaptic device including a memory device that maintains neuron attributes for multiple neurons. The module further includes multiple bit maps that maintain incoming firing events for different periods of delay and a multi-way processor. The processor includes a memory array that maintains a plurality of synaptic weights. The processor integrates incoming firing events in a time-division multiplexing manner. Incoming firing events are integrated based on the neuron attributes and the synaptic weights maintained.

Abstract: In one embodiment, a computer-implemented method includes issuing, to a DRAM with EIP, a first group of two or more load requests to load data from a hash table constructed from hashed join-key values of a dimension table for a hash-join procedure. A second group of two or more load requests is issued. First response data is received, responsive to the first group of load requests. The first response data is processed while awaiting second response data responsive to the second group. Processing the first response data includes identifying matches between the join-key values corresponding to entries in the load requests of the first group and one or more hash buckets in the first response data. The size of the second group of load requests is selected such that a time for processing the first response data is approximately equal to the latency in receiving the second response data.

Abstract: In one embodiment, a computer-implemented method includes issuing, to a DRAM with EIP, a first group of two or more load requests to load data from a hash table constructed from hashed join-key values of a dimension table for a hash-join procedure. A second group of two or more load requests is issued. First response data is received, responsive to the first group of load requests. The first response data is processed while awaiting second response data responsive to the second group. Processing the first response data includes identifying matches between the join-key values corresponding to entries in the load requests of the first group and one or more hash buckets in the first response data. The size of the second group of load requests is selected such that a time for processing the first response data is approximately equal to the latency in receiving the second response data.

Abstract: Apparatus and methods are disclosed that enable the allocation of a cache portion of a memory buffer to be utilized by an on-cache function controller (OFC) to execute processing functions on “main line” data. A particular method may include receiving, at a memory buffer, a request from a memory controller for allocation of a cache portion of the memory buffer. The method may also include acquiring, by an on-cache function controller (OFC) of the memory buffer, the requested cache portion of the memory buffer. The method may further include executing, by the OFC, a processing function on data stored at the cache portion of the memory buffer.

Abstract: An apparatus for providing on-chip voltage-regulated power includes a switched capacitor voltage conversion circuit that receives an elevated power demand signal and operates at a base rate when the elevated power demand signal is not active and at an elevated rate when the elevated power demand signal is active. The switched capacitor voltage conversion circuit comprises an auxiliary set of transistors that are disabled, when the elevated power demand signal is not active and enabled, when the elevated power demand signal is active. The apparatus may also include a droop detection circuit that monitors a monitored power signal and activates the elevated power demand signal in response to the monitored power signal dropping below a selected voltage level. The monitored power signal may be a voltage input provided by an input power supply for the switched capacitor voltage conversion circuit. A corresponding method is also disclosed herein.

Abstract: Apparatus and methods are disclosed that enable the allocation of a cache portion of a memory buffer to be utilized by an on-cache function controller (OFC) to execute processing functions on “main line” data. A particular method may include receiving, at a memory buffer, a request from a memory controller for allocation of a cache portion of the memory buffer. The method may also include acquiring, by an on-cache function controller (OFC) of the memory buffer, the requested cache portion of the memory buffer. The method may further include executing, by the OFC, a processing function on data stored at the cache portion of the memory buffer.