公开(公告)号：US12182075B2

公开(公告)日：2024-12-31

申请号：US18092696

申请日：2023-01-03

Applicant: Mellanox Technologies, Ltd.

Inventor： Siddha Ganju ,  Itamar Frenkel ,  Elad Mentovich ,  Rotem Barzilai ,  Yaakov Gridish

IPC: G06F16/174 ,  G06N20/10

Abstract: Systems, computer program products, and methods are described herein for intelligent data compression, in accordance with an embodiment of the invention. The present invention may be configured to receive a plurality of files for storage in a database and perform a series of steps iteratively, for each file of the plurality of files, and until each file of the plurality of files is represented in the database. The series of steps may include identifying one or more data points in the respective file, where each identified data point was previously unidentified in the database and adding the identified one or more data points to the database. The series of steps may also include identifying one or more features of the respective file for storage in the database and storing the identified one or more features in the database as a surrogate for the respective file.

公开(公告)号：US20230409016A1

公开(公告)日：2023-12-21

申请号：US17807444

申请日：2022-06-17

Applicant: Mellanox Technologies, Ltd.

Inventor： Siddha Ganju ,  Elad Mentovich ,  Yaakov Gridish

IPC: G05B19/418

CPC classification number: G05B19/41875 ,  G05B19/4183 ,  G05B2219/34065

Abstract: A computing entity obtains product information corresponding to a product and defines a multi-region metric space vector based on the product information. The multi-region metric space vector is a vector within a multi-region metric space that comprises a first region corresponding to supply chain/component information, a second region corresponding to assembly/fabrication information, and a third region corresponding to usage/usage environment information. Each of the first, second, and third regions are multi-dimensional. The computing entity processes the multi-region metric space vector using a component, assembly, and usage perspicacity model configured to define fuzzy clusters within the multi-region metric space; determines a parameter corresponding to the product based on at least one fuzzy cluster to which the perspicacity model assigned the multi-region space vector; and provides or causes providing of (a) a visual/audible representation of the parameter or (b) a machine-readable representation of the parameter as input to an application/program.

公开(公告)号：US20240020401A1

公开(公告)日：2024-01-18

申请号：US17863779

申请日：2022-07-13

Applicant: Mellanox Technologies, Ltd.

Inventor： Siddha Ganju ,  Elad Mentovich ,  Andrew Russell

IPC: G06F21/62

CPC classification number: G06F21/6218

Abstract: Various embodiments of the present disclosure provide for generating and managing a digital ledger access system and its associated objects. An example method is configured for securing objects in a digital ledger of objects by identifying an object from amongst a plurality of objects in the digital ledger of objects and generating a quantum token for attachment with the object. The method includes deriving one or more classical public keys associated with the quantum token and determining an attempt to access the object. The method provides access to the object in response to a validation of the classical public key based on the quantum token, and the method precludes access to the object in response to an invalidation of the classical public key based on the quantum token.

公开(公告)号：US20240248455A1

公开(公告)日：2024-07-25

申请号：US18100296

申请日：2023-01-23

Applicant: Mellanox Technologies, Ltd.

Inventor： Tahir Cader ,  Siddha Ganju ,  Avraham Ganor ,  Ran Hasson Ruso ,  Elad Mentovich

IPC: G05B19/4155

CPC classification number: G05B19/4155 ,  G05B2219/49216

Abstract: Methods, apparatuses, and computer program products for proactive thermal management and processing core selection are provided. An example method includes receiving a job packet that is associated with a packet profile and determining one or more performance parameters associated with a performance of the job packet as defined by the packet profile. The method further includes generating a proactive thermal management procedure based upon the one or more performance parameters and associating the proactive thermal management procedure with the job packet. The method may further include determining a selected processing core from amongst a plurality of processing cores for the performance of the job packet based upon one or more operating characteristics of the processing cores and/or one or more performance parameters of the job packet.

公开(公告)号：US20240045418A1

公开(公告)日：2024-02-08

申请号：US17887642

申请日：2022-08-15

Applicant: MELLANOX TECHNOLOGIES, LTD.

Inventor： Siddha Ganju ,  Elad Mentovich ,  Dimitrios Kalavrouziotis ,  Paraskevas Bakopoulos ,  Dimitrios Syrivelis ,  Nikolaos Argyris ,  Yoram Zer ,  Maoz Menachem Nagler ,  Holger Prüsse Orup ,  Finn Leif Kraemer

IPC: G05B23/02 ,  G01R31/08

CPC classification number: G05B23/0283 ,  G01R31/088 ,  G05B23/0254 ,  G05B23/0216 ,  G05B2223/02

Abstract: Apparatuses, systems, and techniques to monitor health data from components and predict needs for maintenance. In at least one embodiment, monitoring health data of cables having one or more known characteristics ands analyzing the health data to determine the health metrics of the one or more cable to generate profiles of the cables used to predict future health metrics of the cables and related cables sharing known characteristics.

公开(公告)号：US11836909B2

公开(公告)日：2023-12-05

申请号：US17584914

申请日：2022-01-26

Applicant: Mellanox Technologies, Ltd.

Inventor： Siddha Ganju ,  Elad Mentovich ,  David Greenlaw ,  Tony Altinis

IPC: G06T7/00 ,  G06V10/774 ,  G06V10/762 ,  G06T7/10

CPC classification number: G06T7/0004 ,  G06T7/10 ,  G06V10/762 ,  G06V10/7747 ,  G06T2207/20081 ,  G06T2207/20092

Abstract: A computing entity is described that obtains at least one inspection image of an at least partially fabricated product and causes the at least one inspection image to be processed by a product inspection engine. The product inspection engine includes a machine learning-trained model. The computing entity obtains an inspection result determined based on the processing of the at least one inspection image by the product inspection engine; identifies one or more training images stored in an image database based at least in part on the at least one inspection image; associates automatically generated labeling data with the one or more training images based at least in part on the inspection result determined by the processing of the at least one inspection image; and causes training of the product inspection engine using the one or more training images and the associated labeling data.

公开(公告)号：US12229296B2

公开(公告)日：2025-02-18

申请号：US17863779

申请日：2022-07-13

Applicant: Mellanox Technologies, Ltd.

Inventor： Siddha Ganju ,  Elad Mentovich ,  Andrew Russell

IPC: G06F21/62

Abstract: Various embodiments of the present disclosure provide for generating and managing a digital ledger access system and its associated objects. An example method is configured for securing objects in a digital ledger of objects by identifying an object from amongst a plurality of objects in the digital ledger of objects and generating a quantum token for attachment with the object. The method includes deriving one or more classical public keys associated with the quantum token and determining an attempt to access the object. The method provides access to the object in response to a validation of the classical public key based on the quantum token, and the method precludes access to the object in response to an invalidation of the classical public key based on the quantum token.

公开(公告)号：US20240220455A1

公开(公告)日：2024-07-04

申请号：US18092696

申请日：2023-01-03

Applicant: Mellanox Technologies, Ltd.

Inventor： Siddha Ganju ,  Itamar Frenkel ,  Elad Mentovich ,  Rotem Barzilai ,  Yaakov Gridish

IPC: G06F16/174

CPC classification number: G06F16/1744 ,  G06N20/10

Abstract: Systems, computer program products, and methods are described herein for intelligent data compression, in accordance with an embodiment of the invention. The present invention may be configured to receive a plurality of files for storage in a database and perform a series of steps iteratively, for each file of the plurality of files, and until each file of the plurality of files is represented in the database. The series of steps may include identifying one or more data points in the respective file, where each identified data point was previously unidentified in the database and adding the identified one or more data points to the database. The series of steps may also include identifying one or more features of the respective file for storage in the database and storing the identified one or more features in the database as a surrogate for the respective file.

公开(公告)号：US20230237635A1

公开(公告)日：2023-07-27

申请号：US17584914

申请日：2022-01-26

Applicant: Mellanox Technologies, Ltd.

Inventor： Siddha Ganju ,  Elad Mentovich ,  David Greenlaw ,  Tony Altinis

IPC: G06T7/00 ,  G06V10/774 ,  G06T7/10 ,  G06V10/762

CPC classification number: G06T7/0004 ,  G06V10/7747 ,  G06T7/10 ,  G06V10/762 ,  G06T2207/20081 ,  G06T2207/20092

Abstract: A computing entity is described that obtains at least one inspection image of an at least partially fabricated product and causes the at least one inspection image to be processed by a product inspection engine. The product inspection engine includes a machine learning-trained model. The computing entity obtains an inspection result determined based on the processing of the at least one inspection image by the product inspection engine; identifies one or more training images stored in an image database based at least in part on the at least one inspection image; associates automatically generated labeling data with the one or more training images based at least in part on the inspection result determined by the processing of the at least one inspection image; and causes training of the product inspection engine using the one or more training images and the associated labeling data.