Intel Corporation

Tomasz Kantecki

John Joseph Browne

Chris MacNamara

Niall D McDonnell

Pierre Laurent

Liang J Ma

David Hunt

Patrick L Connor

Timothy Verrall

Andrey Chilikin

Patrick Fleming

Bruce Richardson

Stephen Doyle

Brendan Ryan

Eoin Walsh

Sean Harte

Ciara Loftus

Marcel Cornu

Namakkal N Venkatesan

Andrew Cunningham

Mark D Gray

Christopher MacNamara

Maryam Tahhan

Niall Power

Anthony L Kelly

Krishnamurthy Jambur Sathyanarayana

Shobhi Jain

Amruta Misra

Vinodh Gopal

Wajdi K Feghali

James D Guilford

Wei Zhang

Andrew J Herdrich

Ankush Varma

Sanjay Kumar

Ben-Zion Friedman

Vasudevan Srinivasan

Stephen T Palermo

Srihari Makineni

Nikhil Gupta

Dorit Shapira

Weigang Li

Shrikant M Shah

Ronen Chayat

Alexander J Leckey

Damien Power

Jasvinder Singh

Michael A O'Hanlon

Peter McCarthy

Fiona Trahe

Declan W Doherty

Chris Macnamara

Nemanja Marjanovic

Maksim Lukoshkov

Rory Sexton

Adrian Boczkowski

Jacqueline F Jardim

Wojciech Andralojc

Anatoly Burakov

Bryan T Butters

Mairtin O'Loingsigh

John Griffin

Seán Harte

Terence Nally

Chris M Macnamara

John Barry

Barak Hermesh

Methods, apparatus, and software for hashing data. The methods and apparatus employ novel improvements to hash algorithms, such as a SHA-2 hash algorithm to reduce computations and increase performance. In one aspect, calculation of SHA-2 message scheduling and SHA compression operations are separated under which an SHA-2 message schedule is applied to multiple rounds of SHA compression operations over multiple chunks of data for the data item being hashed. In another aspect, the SHA-2 message schedule is implemented such that message schedules for multiple message words or data blocks are performed in parallel. The approaches may be employed to reduce hash calculations for various purposes, including generating Filecoin nodes.

Methods and apparatus to hash data

Examples described herein relate to a device including circuitry to permit or deny the device to write-to or read-from kernel space memory of a virtualized execution environment by use of multiple process identifiers. In some examples, the device is communicatively coupled with the virtualized execution environment in a manner consistent with one or more of: Single Root IO Virtualization (SR-IOV), Scalable I/O Virtualization (SIOV), or PCI express (PCIe). In some examples, to control write or read operations to kernel space memory of a virtualized execution environment by the device by use of multiple process identifiers, the circuitry is to perform an address translation based on a first process identifier and second process identifier associated with the virtualized execution environment.

Technologies to provide access to kernel and user space memory regions

A performance monitor provides cache miss stall and memory bandwidth usage metric samples to a resource exhaustion detector. The detector can detect the presence of last-level cache and memory bandwidth exhaustion conditions based on the metric samples. If cache miss stalls and memory bandwidth usage are both trending up, the detector reports a memory bandwidth exhaustion condition to a resource controller. If cache miss stalls are trending up and memory bandwidth usage is trending down, the detector reports a last-level cache exhaustion condition to the resource controller. The resource controller can allocate additional last-level cache or memory bandwidth to the processor unit to remediate the resource exhaustion condition. If bandwidth-related metric samples indicate that a processor unit may be overloaded due to receiving high bandwidth traffic, the resource controller can take a traffic rebalancing remedial action.

Processor unit resource exhaustion detection and remediation

A system comprising an interface to access a network slice power consumption parameter for a network slice comprising a logical network between two endpoints through a plurality of physical computing platforms; and a controller comprising circuitry, the controller to specify operating parameters for a plurality of hardware resources of a first physical computing platform in accordance with the network slice power consumption parameter.

Energy aware network slicing

A computing device includes an appliance status table to store at least one of reliability and performance data for one or more network functions virtualization (NFV) appliances and one or more legacy network appliances. The computing device includes a load controller to configure an Internet Protocol (IP) filter rule to select a packet for which processing of the packet is to be migrated from a selected one of the one or more legacy network appliances to a selected one of the one or more NFV appliances, and to update the appliance status table with received at least one of reliability and performance data for the one or more legacy network appliances and the one or more NFV appliances. The computing device includes a packet distributor to receive the packet, to select one of the one or more NFV appliances based at least in part on the appliance status table, and to send the packet to the selected NFV appliance. Other embodiments are described herein.

Migration from a legacy network appliance to a network function virtualization (NFV) appliance

Packets are differentiated based on their traffic class. A traffic class is allocated bandwidth for transmission. One or more core or thread can be allocated to process packets of a traffic class for transmission based on allocated bandwidth for that traffic class. If multiple traffic classes are allocated bandwidth, and a traffic class underutilizes allocated bandwidth or a traffic class is allocated insufficient bandwidth, then allocated bandwidth can be adjusted for a future transmission time slot. For example, a higher priority traffic class with excess bandwidth can share the excess bandwidth with a next highest priority traffic class for use to allocate packets for transmission for the same time slot. In the same or another example, bandwidth allocated to a traffic class depends on an extent of insufficient allocation or underutilization of allocated bandwidth such that a traffic class with insufficient allocated bandwidth in one or more prior time slot can be provided more bandwidth in a current time slot and a traffic class with underutilization of allocated bandwidth can be provided with less allocated bandwidth for a current time slot.

Scalable traffic management using one or more processor cores for multiple levels of quality of service

Technologies for coordinating access to packets include a network device. The network device is to establish a ring in a memory of the network device. The ring includes a plurality of slots. The network device is also to allocate cores to each of an input stage, an output stage, and a worker stage. The worker stage is to process data in a data packet with an associated worker function. The network device is also to add, with the input stage, an entry to a slot in the ring representative of a data packet received with a network interface controller of the network device, access, with the worker stage, the entry in the ring to process at least a portion of the data packet, and provide, with the output stage, the processed data packet to the network interface controller for transmission.

Technologies for coordinating access to data packets in a memory

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

Examples herein relate to assigning, by a system agent of a central processing unit (CPU), an operating frequency to a core group based priority level of the core group while avoiding throttling of the system agent. Avoiding throttling of the system agent can include maintaining a minimum performance level of the system agent. A minimum performance level of the system agent can be based on a minimum operating frequency. Assigning, by a system agent of a central processing unit, an operating frequency to a core group based priority level of the core group while avoiding throttling of the system agent can avoid a thermal limit of the CPU. Avoiding thermal limit of the CPU can include adjusting the operating frequency to the core group to avoid performance indicators of the CPU. A performance indicator can indicate CPU utilization corresponds to Thermal Design Point (TDP).

Platform slicing of central processing unit (CPU) resources

Techniques and apparatuses for processing data unit are described. In one embodiment, for example, an apparatus for networking may include at least one memory, logic, at least a portion of the logic comprised in hardware coupled to the at least one memory, the logic to access an encrypted packet having an encrypted portion, determine at least one flow control segment of the encrypted portion, decrypt the at least one flow control segment to generate a partially-decrypted packet comprising a decrypted at least one flow control segment and an encrypted remainder portion, the remainder portion comprising a portion of the encrypted packet that does not include the decrypted at least one flow control segment, access process information in the decrypted at least one flow control segment, and process the partially-decrypted packet according to the process information. Other embodiments are described and claimed.

Techniques for flow control packet processing

A computing apparatus, including: a processor; a pointer to a counter memory location; and a lazy increment counter engine to: receive a stimulus to update the counter; and lazy increment the counter including issuing a weakly-ordered increment directive to the pointer.

Lazy increment for high frequency counters

A network interface device, including: an ingress interface; a host platform interface to communicatively couple to a host platform; and a packet preprocessor including logic to: receive via the ingress interface a data sequence including a plurality of discrete data units; identify the data sequence as data for a parallel processing operation; reorder the discrete data units into a reordered data frame, the reordered data frame configured to order the discrete data units for consumption by the parallel operation; and send the reordered data to the host platform via the host platform interface.

Reordering of data for parallel 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

Examples include techniques for coalescing doorbells in a request message. Example techniques include gathering doorbells to access a device. The gathered are combined in a cache line structure and the cache line structure is written to a cache or buffer for a central processing unit in a single write operation.

Techniques for coalescing doorbells in a request message

Growing community of inventors

Ennis, Ireland

Tomasz Kantecki