Mellanox Technologies, Ltd.

Gary Mataev

Idan Burstein

Eitan Zahavi

Avi Urman

Shahaf Shuler

Hanan Shteingart

Michael Weiner

Jean-Francois Puget

Chen Rozenbaum

Yair Chasdai

David Daniel Pilnik

Liran Daniel

Shaul Arazi

Zachi Binshtock

Yoli Shavit

Methods, systems, and machine-readable mediums to perform a neural network to encode log data. In at least one embodiment, a processor comprising one or more circuits to encode at least one log message, at least in part, by encoding a first type of information in the at least one log message to obtain a first encoding, encoding a second type of information in the at least one log message to obtain a second encoding, and obtaining a resultant encoding at least in part by combing at least the first and second encodings.

Using neural networks to encode log data

Methods, systems, and computer program products for selecting packing processing cores are provided. An example system includes a plurality of packet processing cores and a load balancing unit communicatively connected to the plurality of packet processing cores. The load balancing unit is configured to receive a workflow packet including packet description data indicative of at least a packet structure and a packet priority and receive, from the plurality of packet processing cores, state data indicative of at least a utilization state and an operating state of each of the respective packet processing cores. The load balancing unit determines a selected packet processing core from amongst the plurality of packet processing cores based on the state data of the packet processing core and the packet description data of the workflow packet and transmits the workflow packet to the selected packet processing core.

Methods, systems, and computer program products for dynamic load balancing

In one embodiment, a data communication device includes a network interface controller to process packets received from at least one of a host device for sending over a network, and at least one remote device over the network, at least one processor to execute computer instructions to receive a configuration, and extract filtering rules from the configuration, and at least one hardware accelerator to receive the filtering rules from the at least one processor, and filter the packets based on the rules so that some of the packets are dropped and some of the packets are forwarded to the at least one processor to send data based on the forwarded packets to another device.

Efficient and flexible flow inspector

Devices and methods to identify malicious usage of a network device. In at least one embodiment, a network device comprises circuitry for performing a networking function and collecting telemetry data indicative of the performance of the networking function. The network device obtains an inference of a network traffic pattern using a machine learning model, and responds to the inference.

Network devices assisted by machine learning

Growing community of inventors

Haifa, Israel

Gary Mataev