Intel Corporation

Peter McCarthy

John Joseph Browne

Chris MacNamara

Liang J Ma

Tomasz Kantecki

Liam Day

Pierre Laurent

David Hunt

Sean Harte

Nemanja Marjanovic

Rory Sexton

Jacqueline F Jardim

Mairtin O'Loingsigh

John Griffin

Technologies for performance monitoring include a computing device having multiple processor cores. The computing device performs a training workload with a processor core by continuously polling an empty input queue. The computing device determines empty polling thresholds based on the empty polling workload. The computing device performs a packet processing workload with one or more processor cores by continuously polling input queues associated with network traffic. The computing device compares a measured number of empty polls performed by the packet processing workload against the empty polling thresholds. The computing device configures power management of one or more processor cores in response to the comparison. The computing device may determine empty polling trends and compare the measured number of empty polls and the empty polling trends to the empty polling thresholds. Other embodiments are described and claimed.

Technologies for performance monitoring and management with empty polling

Technologies for power-aware scheduling include a computing device that receives network packets. The computing device classifies the network packets by priority level and then assigns each network packet to a performance group bin. The packets are assigned based on priority level and other performance criteria. The computing device schedules the network packets assigned to each performance group for processing by a processing engine such as a processor core. Network packets assigned to performance groups having a high priority level are scheduled for processing by processing engines with a high performance level. The computing device may select performance levels for processing engines based on processing workload of the network packets. The computing device may control the performance level of the processing engines, for example by controlling the frequency of processor cores. The processing workload may include packet encryption. Other embodiments are described and claimed.

Technologies for power-aware scheduling for network packet processing

Technologies for network packet processing include a computing device that receives incoming network packets. The computing device adds the incoming network packets to an input lockless shared ring, and then classifies the network packets. After classification, the computing device adds the network packets to multiple lockless shared traffic class rings, with each ring associated with a traffic class and output port. The computing device may allocate bandwidth between network packets active during a scheduling quantum in the traffic class rings associated with an output port, schedule the network packets in the traffic class rings for transmission, and then transmit the network packets in response to scheduling. The computing device may perform traffic class separation in parallel with bandwidth allocation and traffic scheduling. In some embodiments, the computing device may perform bandwidth allocation and/or traffic scheduling on each traffic class ring in parallel. Other embodiments are described and claimed.

Technologies for scalable network packet processing with lock-free rings

Growing community of inventors

Ennis, Ireland

Peter McCarthy