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Network Packet Processing with P4 (Programming Protocol-Independent Packet Processors) in CPU, GPU and FPGAs using OpenCL

Network Packet Processing with P4 (Programming Protocol-Independent Packet Processors) in CPU, GPU and FPGAs using OpenCL
使用 OpenCL 在 CPU、GPU 和 FPGA 中使用 P4(独立于编程协议的数据包处理器)进行网络数据包处理
批准号:
486746-2015
负责人:
Makaroff, Dwight
金额:
$1.78万
依托单位:
依托单位国家:
加拿大
项目类别:
Engage Grants Program
财政年份:
2015
资助国家:
加拿大
项目状态:
已结题
起止时间:
2015-01-01 至 2016-12-31

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英文摘要
The purpose of Network functions virtualization (NFV) is to virtualize the network services that are now being offered by dedicated hardware. NFV will decrease the amount of dedicated hardware that's needed to launch and operate network services. In other words, NFV is proposed to decouple network functions from dedicated hardware devices and allow network services that are now being carried out by routers, firewalls, load balancers and other dedicated hardware devices to be hosted on virtual machines (VMs). Consequently, the network administrators will no longer need to purchase dedicated hardware devices in order to build a service chain. As a result, server-functionality and capacity is thus dictated by the available generic hardware and the software-enforced quota of that hardware granted to an NFV; there will be no need for network administrators to over-provision their data centres with specialized single-use hardware, which will reduce both capital expenses and operating expenses. Intel CPUs are the currently available "generic hardware" being used for NFV applications; Intel CPUs are not designed for highly parallel tasks like packet processing. Bleeding edge technology investments by Intel suggest that future "generic hardware" for NFVs will have FPGA (Field Programmable Gate Arrays) or GPU (Graphics Processing Units) based co-processors for offloading highly parallel tasks. An important consequence of the availability of this class of hardware is that designers could configure functionality after manufacture and even after deployment should this be desired by the customer. Emerging technologies for heterogeneous computing (OpenCL) will be investigated as potential technology investments to target current generation hardware and next generation hardware with the same code-base.
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Distributed Systems Support for Processing Big Data from Sensor Networks
  • 批准号:
    RGPIN-2019-06776
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.04万
  • 财政年份:
    2022
  • 负责人:
    Makaroff, Dwight
  • 依托单位:
Distributed Systems Support for Processing Big Data from Sensor Networks
  • 批准号:
    RGPIN-2019-06776
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.04万
  • 财政年份:
    2021
  • 负责人:
    Makaroff, Dwight
  • 依托单位:
Distributed Systems Support for Processing Big Data from Sensor Networks
  • 批准号:
    RGPIN-2019-06776
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.04万
  • 财政年份:
    2020
  • 负责人:
    Makaroff, Dwight
  • 依托单位:
Distributed Systems Support for Processing Big Data from Sensor Networks
  • 批准号:
    RGPIN-2019-06776
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.04万
  • 财政年份:
    2019
  • 负责人:
    Makaroff, Dwight
  • 依托单位:
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