Abstract:
A new processing architecture is described in which a data processing unit (DPU) is utilized within a device. Unlike conventional compute models that are centered around a central processing unit (CPU), example implementations described herein leverage a DPU that is specially designed and optimized for a data-centric computing model in which the data processing tasks are centered around, and the primary responsibility of, the DPU. For example, various data processing tasks, such as networking, security, and storage, as well as related work acceleration, distribution and scheduling, and other such tasks are the domain of the DPU. The DPU may be viewed as a highly programmable, high-performance input/output (I/O) and data-processing hub designed to aggregate and process network and storage I/O to and from multiple other components and/or devices. This frees resources of the CPU, if present, for computing-intensive tasks.
Abstract:
One embodiment provides an apparatus. The apparatus includes client traffic management (CTM) logic. The CTM logic is to trigger implementation of a selected network traffic flow related to the client device, the triggering based, at least in part, on a network traffic flow related to the client device. The network traffic flow is associated with a connection and includes at least one subflow. Each subflow is carried by a respective path associated with the connection. The triggering includes at least one of constraining and/or adjusting an allowable throughput at a service provider for one or more of the at least one subflow. The selected traffic policy is to be implemented in a transport layer.
Abstract:
Technologies for low-latency data streaming include a computing device having a processor that includes a producer and a consumer. The producer generates a data item, and in a local buffer producer mode adds the data item to a local buffer, and in a remote buffer producer mode adds the data item to a remote buffer. When the local buffer is full, the producer switches to the remote buffer producer mode, and when the remote buffer is below a predetermined low threshold, the producer switches to the local buffer producer mode. The consumer reads the data item from the local buffer while operating in a local buffer consumer mode and reads the data item from the remote buffer while operating in a remote buffer consumer mode. When the local buffer is above a predetermined high threshold, the consumer may switch to a catch-up operating mode. Other embodiments are described and claimed.
Abstract:
One embodiment provides an apparatus. The apparatus includes client traffic management (CTM) logic. The CTM logic is to trigger implementation of a selected network traffic flow related to the client device, the triggering based, at least in part, on a network traffic flow related to the client device. The network traffic flow is associated with a connection and includes at least one subflow. Each subflow is carried by a respective path associated with the connection. The triggering includes at least one of constraining and/or adjusting an allowable throughput at a service provider for one or more of the at least one subflow. The selected traffic policy is to be implemented in a transport layer.
Abstract:
A system for adaptive audio video (AV) stream processing may include at least one processor and a switch device. The switch device may be configured to route AV traffic to the processor, and to receive AV traffic from the processor and provide the AV traffic to a client device via one or more channels. The processor may monitor a transcoder buffer depth and depths of buffers associated with channels over which the AV traffic is being transmitted. The processor may adaptively modify one or more attributes associated with the AV traffic based at least on the monitored buffer depths. For example, the processor may adaptively adjust a bit rate associated with transcoding the AV traffic based at least on the transcoder buffer depth. The processor may utilize the depths of the buffers associated with the channels to adaptively adjust the amount of AV traffic provided for transmission over the channels.
Abstract:
Described is an apparatus that comprises: a first sequential unit; a first queue coupled in parallel to the first sequential unit such that the first queue and first sequential unit receive a first input, the first sequential for double sampling the first input; a compare unit to receive an output from the first sequential unit; and a first selection unit controllable by a write pointer of a previous cycle, the first selection unit to receive outputs of each storage unit of the first queue, wherein the first selection unit to generate an output for comparison by the first compare unit.
Abstract:
A system for adaptive audio video (AV) stream processing may include at least one processor and a switch device. The switch device may be configured to route AV traffic to the processor, and to receive AV traffic from the processor and provide the AV traffic to a client device via one or more channels. The processor may monitor a transcoder buffer depth and depths of buffers associated with channels over which the AV traffic is being transmitted. The processor may adaptively modify one or more attributes associated with the AV traffic based at least on the monitored buffer depths. For example, the processor may adaptively adjust a bit rate associated with transcoding the AV traffic based at least on the transcoder buffer depth. The processor may utilize the depths of the buffers associated with the channels to adaptively adjust the amount of AV traffic provided for transmission over the channels.
Abstract:
Exemplary embodiments may employ techniques for dynamically dispatching requests to resources operating in a distributed computing environment, such as a computing cloud, according to one or more policies. Embodiments may further dynamically adjust resources in the computing environment using predictive models that use current loads as an input. Embodiments may still further maintain a state for a processing environment independent of the type or configuration of a device used to access the environment on behalf of a user.
Abstract:
Exemplary embodiments may employ techniques for dynamically dispatching requests to resources operating in a distributed computing environment, such as a computing cloud, according to one or more policies. Embodiments may further dynamically adjust resources in the computing environment using predictive models that use current loads as an input. Embodiments may still further maintain a state for a processing environment independent of the type or configuration of a device used to access the environment on behalf of a user.
Abstract:
A network processor for processing packet switching in a network switching system is disclosed. The network processor includes a first memory for storing a first packet among a plurality of packets; a second memory for storing a second packet among the plurality of packets; and a memory selecting unit for selecting the first memory or the second memory for storing each of the plurality of packets according to whether a traffic of the network switching system is congested; wherein attributes of the first memory and the second memory are different.