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公开(公告)号:US10206092B1
公开(公告)日:2019-02-12
申请号:US15721677
申请日:2017-09-29
Applicant: Hewlett Packard Enterprise Development LP
Inventor: Peter Erik Mellquist , Joao Claudio Ambrosi , Bryan Stiekes , Raul Ney da Silva Lima , Victor Hugo Rebelo Rodrigues , Alex Ferreira Ramires Trajano
Abstract: Some examples provide a system to automatically discover network devices. The system enables a network device discovery protocol with a transmit mode and a receive mode on a network device. The system enables an auxiliary communication protocol on the network device. The system broadcasts the network device discovery protocol records from the network device including local neighbors and connectivity information. The system engine processes topological information using the auxiliary communication protocol and timing cycles to update age of a set of topology information records.
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公开(公告)号:US20240202318A1
公开(公告)日:2024-06-20
申请号:US18067945
申请日:2022-12-19
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor: Joao Claudio Ambrosi , Joaquim Gomes Da Costa Eulalio De Souza , Reinaldo Cézar de Morais Gomes , Marcela Galdino , Ramon Sousa Sarmento
Abstract: In some examples, during runtime of a virtual computing environment, a system intercepts a call for an invocation of a program file that relates to a program execution in the virtual computing environment, and obtains, for the program file prior to the invocation of the program file in response to the call, context information of the virtual computing environment. The context information includes an identifier of a program code image for the virtual computing environment. The system computes a measurement value based on the program file, and provides the measurement value and the context information of the virtual computing environment to an integrity checker to perform a context-specific validation of the program file.
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公开(公告)号:US11799888B2
公开(公告)日:2023-10-24
申请号:US16434350
申请日:2019-06-07
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
IPC: H04L41/069 , H04L9/40 , H04L41/28 , H04L41/12
CPC classification number: H04L63/1425 , H04L41/069 , H04L41/12 , H04L41/28
Abstract: A network topology analysis and validation system and technique are provided. In some implementations, the system may obtain information in real-time mode or as an off-line data set. The information being representative of a defined network topology type for a computer network and communication connections for devices within the computer network. The computer network analysis may be performed on a subnet of a larger network. A communication topology of the computer network may be compared with the expected (defined) network topology using bipartite and bi-colorization techniques to classify nodes of the computer network. After classification, anomalous communication connections (not in conformance with a standard for the defined network topology) may be identified and colored for presentation to a system administrator. Anomalous communication connections may initiate an alert, event, or alarm, via a system administration monitoring system for real-time notification.
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公开(公告)号:US11200948B1
公开(公告)日:2021-12-14
申请号:US17005219
申请日:2020-08-27
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor: Joao Claudio Ambrosi , Arthur Carvalho Walraven Da Cunha , Jefferson Rodrigo Alves Cavalcante
Abstract: Systems are provided for implementing a hybrid resistor-memristor crossbar array, which allows for flexible conductance to be used in implementing the weight matrix of a neural network. The hybrid resistor-memristor crossbar array may include resistor crossbars, each resistor having a static conductance value. The hybrid resistor-memristor crossbar array may also have a memristor coupled to an output line associated with the resistor crossbar array, wherein the memristor has a variable conductance value, and further wherein the static conductance values and the variable conductance value are set to calculate a matrix-vector multiplication associated with a weight matrix of a neural network. An expected range of coefficients for a weight matrix of a neural network can be given by the Discrete Transform Cosine (DCT). Accordingly, the static conductance values of the resistors in the resistors crossbar array are set to values equal to known coefficients of the DCT.
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