了解DPU數據處理器的基礎知識：它們是什么、它們做什么、誰在制造它們以及誰在采用它們。然后決定您的數據中心是否有朝一日會使用。

數據處理器是針對數據處理和以數據為中心的計算的硬件加速器。 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架構。

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.

許多組織使用DPU來完成人工智能和大數據等超級計算任務。 貴司的數據中心在決定是否使用DPU前，請先了解DPU的使用案例和優缺點。

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（數據處理器）能做什么？

What does a DPU do?

DPU減輕了CPU的網絡和通信工作負載，這使CPU能夠轉而處理應用程序支持任務。DPU專注于以數據為中心的工作負載，如數據傳輸、數據簡化、數據安全和分析。DPU的芯片采用了專門的設計，將處理器核心與硬件加速塊結合在一起。 這種設計使DPU成為比GPU具有更多功能、更通用的芯片。DPU擁有自己的專用操作系統，這意味著您可以將其資源與主操作系統的資源相結合，并且它可以執行加密、擦除編碼、壓縮或解壓縮等功能。

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.

云計算和超大規模計算的提供商是最早采用這種技術的。 然而，像VMware這樣的供應商已經開始在他們的產品中添加對DPU的支持，這使得他們更具有吸引力。

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支持存儲系統

Support storage with a DPU

由于DPU作為處理單元的多功能性，您可以使用DPU來支持數據中心中的存儲。 例如，通過將NVMe存儲設備連接到DPU的PCIe總線，可以加快對NVMe存儲設備的訪問。

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還可以更好地訪問依賴于NVMe-oF的遠程存儲設備。DPU將這些遠程存儲設備作為標準NVMe設備呈現給系統。 這些特性將優化與遠程存儲的連接，因為這意味著您不再需要特殊的驅動程序來連接到這些遠程存儲設備。

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和數據中心架構

DPUs and data-centric architecture

DPU只是數據中心架構的一部分。 該范例要求您圍繞數據需求構建基礎設施，而不是反過來讓數據適應基礎設施。 它使數據成為應用程序開發、業務決策和基礎設施部署的主要考慮因素。 以數據為中心的組織將數據視為其核心資產，通過為多個應用程序實現單一數據策略，消除豎井，并減少無序擴展。

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.

以數據為中心的硬件(如DPU)簡化了數據的移動和交付。 它應該提供高可用性和可靠性，并且應該使整個組織能夠實時訪問共享數據。 它的性能、容量、可伸縮性和安全性應該隨需求和新技術發生變化，以滿足新的工作負載需求并適應新技術。

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.

在以數據為中心的架構的語境中，DPU解決了服務器節點在進行以數據為中心的計算時效率低下的問題，它還解決了服務器節點之間傳輸或共享數據時速度緩慢或效率低下的問題。

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，新興的Fundable公司發布了第的一個版本DPU。 它創建了兩種DPU:一種用于存儲，一種用于網絡。Fundable公司DPU的兩個版本都包含用于存儲、安全、網絡和虛擬化等任務的內存和片上處理。Fundable公司設計它們的目的是賦予超融合基礎設施的好處，但更大程度上共享存儲和網絡資源。

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.

自從Fungible公司的DPU發布以來，諸如英偉達和英特爾等廠商已經發布了他們自己的該技術版本。 英特爾于2021年6月推出了與DPU功能相同的基礎處理器芯片。 緊隨英特爾之后，英偉達于2021年7月發布了自己的DPU。 這些DPU——以及來自其他競爭對手(如Marvell和AWS)的產品——都將任務從主機處理器中剝離出來，以加速和簡化數據計算工作負載。 英偉達希望電信公司和云服務提供商首先采用它們的技術，但主要供應商提供的DPU產品的蓬勃發展意味著，其他數據中心可能很快也會采用它。

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.