Abstract: Techniques facilitating voltage droop reduction and/or mitigation in a processor core are provided. In one example, a system can comprise a memory that stores, and a processor that executes, computer executable components. The computer executable components can comprise an observation component that detects one or more events at a first stage of a processor pipeline. An event of the one or more events can be a defined event determined to increase a level of power consumed during a second stage of the processor pipeline. The computer executable components can also comprise an instruction component that applies a voltage droop mitigation countermeasure prior to the increase of the level of power consumed during the second stage of the processor pipeline and a feedback component that provides a notification to the instruction component that indicates a success or a failure of a result of the voltage droop mitigation countermeasure.

Abstract: Techniques facilitating on-chip supply noise voltage reduction and/or mitigation using local detection loops in a processor core are provided. In one example, a computer-implemented method can comprise detecting, by a processor core, a voltage droop at a first area of the processor core. The computer-implemented method can also comprise transmitting, by the processor core, voltage droop information to a local controller located in the first area and to a global controller located in the processor core. Further, the computer-implemented method can comprise applying, by the processor core, a first mitigation countermeasure at the first area of the processor core in response to a local instruction received from the local controller. The local instruction can comprise an indication of the first mitigation countermeasure.

Abstract: Techniques facilitating on-chip supply noise voltage reduction and/or mitigation using local detection loops in a processor core are provided. In one example, a computer-implemented method can comprise detecting, by a processor core, a voltage droop at a first area of the processor core. The computer-implemented method can also comprise transmitting, by the processor core, voltage droop information to a local controller located in the first area and to a global controller located in the processor core. Further, the computer-implemented method can comprise applying, by the processor core, a first mitigation countermeasure at the first area of the processor core in response to a local instruction received from the local controller. The local instruction can comprise an indication of the first mitigation countermeasure.

Abstract: A random number signal generator used for performing dropout or weight initialization for a node in a neural network. The random number signal generator includes a transistor which generates a random noise signal. The transistor includes a substrate, source and drain regions formed in the substrate, a first insulating layer formed over a channel of the transistor, a first trapping layer formed over the first insulating layer, a second insulating layer formed over the first trapping layer, and a second trapping layer formed over the second insulating layer. One or more traps in the first and second trapping layers are configured to capture or release one or more carriers flowing through the channel region. The random noise signal is generated as a function of one or more carrier being captured or released by the one or more traps.

Abstract: A method, system and computer program product are disclosed that comprise capturing first image data of a person's face using at least one sensor responsive in a band of infrared wavelengths and capturing second image data of the person's face using the at least one sensor responsive in a band of visible wavelengths; extracting image features in the image data and detecting face regions; applying a similarity analysis to image feature edge maps extracted from the first and the second image data; and recognizing a presence of a live face image after regions found in the first image data pass a facial features classifier. Upon recognizing the presence of the live face image, additional operations can include verifying the identity of the person as an authorized person and granting the person access to a resource.

Abstract: A method, system and computer program product are disclosed that comprise capturing first image data of a person's face using at least one sensor responsive in a band of infrared wavelengths and capturing second image data of the person's face using the at least one sensor responsive in a band of visible wavelengths; extracting image features in the image data and detecting face regions; applying a similarity analysis to image feature edge maps extracted from the first and the second image data; and recognizing a presence of a live face image after regions found in the first image data pass a facial features classifier. Upon recognizing the presence of the live face image, additional operations can include verifying the identity of the person as an authorized person and granting the person access to a resource.