DPU（数据处理器）能做什么？

了解DPU数据处理器的基础知识：它们是什么、它们做什么、谁在制造它们以及谁在采用它们。然后决定您的数据中心是否有朝一日会使用。

数据处理器是针对数据处理和以数据为中心的计算的硬件加速器。 不同于CPU和GPU及其他硬件加速器，DPU具有更高的并行度和MIMD架构。

A data processing unit is a hardware accelerator specifically geared toward data processing and data-centric computing. It differs from other hardware accelerators such as the CPU and GPU in that it has an increased degree of parallelism and MIMD architecture.

许多组织使用DPU来完成人工智能和大数据等超级计算任务。 贵司的数据中心在决定是否使用DPU前，请先了解DPU的使用案例和优缺点。

Many organizations use the DPU for supercomputing tasks such as AI and big data. To decide whether your organization requires a DPU in its data center, understand its use cases and drawbacks.

DPU（数据处理器）能做什么？

What does a DPU do?

DPU减轻了CPU的网络和通信工作负载，这使CPU能够转而处理应用程序支持任务。DPU专注于以数据为中心的工作负载，如数据传输、数据简化、数据安全和分析。DPU的芯片采用了专门的设计，将处理器核心与硬件加速块结合在一起。 这种设计使DPU成为比GPU具有更多功能、更通用的芯片。DPU拥有自己的专用操作系统，这意味着您可以将其资源与主操作系统的资源相结合，并且它可以执行加密、擦除编码、压缩或解压缩等功能。

A DPU offloads networking and communication workloads from the CPU, which enables the CPU to then tackle application support tasks instead. It focuses on data-centric workloads such as data transfer, data reduction, data security and analytics. The chip features a specialized design that combines processor cores with hardware accelerator blocks. This design makes the DPU a more versatile, general-purpose chip than the GPU. The DPU possesses its own dedicated OS, which means you can combine its resources with your primary OS's resources, and it can perform functions such as encryption, erasure coding, and compression or decompression.

云计算和超大规模计算的提供商是最早采用这种技术的。 然而，像VMware这样的供应商已经开始在他们的产品中添加对DPU的支持，这使得他们更具有吸引力。

Cloud and hyperscale providers have been the earliest adopters of this technology. However, vendors like VMware have started to add support for DPUs into their offerings, which gives them a broader appeal for other organizations.

使用DPU支持存储系统

Support storage with a DPU

由于DPU作为处理单元的多功能性，您可以使用DPU来支持数据中心中的存储。 例如，通过将NVMe存储设备连接到DPU的PCIe总线，可以加快对NVMe存储设备的访问。

Because of DPUs' versatility as a processing unit, you can use DPUs to support storage in your data center. For example, you can accelerate access to NVMe storage devices by connecting them to the DPU's PCIe bus.

DPU还可以更好地访问依赖于NVMe-oF的远程存储设备。DPU将这些远程存储设备作为标准NVMe设备呈现给系统。 这些特性将优化与远程存储的连接，因为这意味着您不再需要特殊的驱动程序来连接到这些远程存储设备。

DPU also gives you better access to remote storage devices that rely on NVMe-oF. The DPU presents these remote storage devices to the system as standard NVMe devices. This optimizes your connectivity to the remote storage because it means you no longer require special drivers to connect to these remote storage devices.

DPU和数据中心架构

DPUs and data-centric architecture

DPU只是数据中心架构的一部分。 该范例要求您围绕数据需求构建基础设施，而不是反过来让数据适应基础设施。 它使数据成为应用程序开发、业务决策和基础设施部署的主要考虑因素。 以数据为中心的组织将数据视为其核心资产，通过为多个应用程序实现单一数据策略，消除竖井，并减少无序扩展。

The DPU represents just one part of a data-centric architecture. This paradigm requires you to build infrastructure around data requirements, as opposed to forcing data to fit infrastructure. It makes data the primary consideration for application development, business decisions and infrastructure deployment. A data-centric organization treats data as its central asset, eliminates silos and mitigates sprawl by implementing a single data strategy for multiple applications.

以数据为中心的硬件(如DPU)简化了数据的移动和交付。 它应该提供高可用性和可靠性，并且应该使整个组织能够实时访问共享数据。 它的性能、容量、可伸缩性和安全性应该随需求和新技术发生变化，以满足新的工作负载需求并适应新技术。

Data-centric hardware -- such as the DPU -- eases the movement and delivery of data. It should deliver high availability and reliability, and should enable the entire organization to access that shared data in real time. Its performance, capacity, scalability and security should change to meet new workload requirements and adapt to new technologies.

在以数据为中心的架构的语境中，DPU解决了服务器节点在进行以数据为中心的计算时效率低下的问题，它还解决了服务器节点之间传输或共享数据时速度缓慢或效率低下的问题。

Within the context of a data-centric architecture, the DPU addresses server nodes' inefficiency when it comes to data-centric computation, and it also addresses slow or inefficient transfer or sharing of data between server nodes.

DPU的日益普及

The increased popularity of the DPU

2020年，新兴的Fundable公司发布了第的一个版本DPU。 它创建了两种DPU:一种用于存储，一种用于网络。Fundable公司DPU的两个版本都包含用于存储、安全、网络和虚拟化等任务的内存和片上处理。Fundable公司设计它们的目的是赋予超融合基础设施的好处，但更大程度上共享存储和网络资源。

In 2020, the startup Fungible released the first version of the DPU. It created two separate versions of the processing unit: one for storage and one for networking. Both versions of the Fungible DPU included memory and on-chip processing intended for tasks such as storage, security, networking and virtualization. Fungible designed them to confer the benefits of hyper-converged infrastructure but with greater sharing of storage and networking resources.

自从Fungible公司的DPU发布以来，诸如英伟达和英特尔等厂商已经发布了他们自己的该技术版本。 英特尔于2021年6月推出了与DPU功能相同的基础处理器芯片。 紧随英特尔之后，英伟达于2021年7月发布了自己的DPU。 这些DPU——以及来自其他竞争对手(如Marvell和AWS)的产品——都将任务从主机处理器中剥离出来，以加速和简化数据计算工作负载。 英伟达希望电信公司和云服务提供商首先采用它们的技术，但主要供应商提供的DPU产品的蓬勃发展意味着，其他数据中心可能很快也会采用它。

Since the release of Fungible's DPU, vendors such as Nvidia and Intel have released their own versions of this technology. In June 2021, Intel released its infrastructure processing unit chip, which does the same job as a DPU. On Intel's heels, in July 2021, Nvidia unveiled its own DPU. These processing units -- as well as those from additional competitors such as Marvell and AWS -- all offload tasks from the host processor to accelerate and streamline data computing workloads. Nvidia expects telecommunications companies and cloud providers to adopt its technology first, but the boom in DPU offerings from major vendors means you might see it in other data centers soon as well.