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What Is A DPU (Data Processing Unit)?

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What Is A DPU (Data Processing Unit)?

Data processing units, commonly known as DPUs, are a new class of reprogrammable high-performance processors combined with high-performance network interfaces that are optimized to perform and accelerate network and storage functions carried out by data center servers. DPUs plug into a server’s PCIe slot just as a GPU would, and they allow servers to offload network and storage functions from the CPU to the data centric computing, allowing the CPU to focus only on running the operating systems and system applications. DPUs often use a reprogrammable FPGA combined with a network interface card to accelerate network traffic the same way that GPUs are being used to accelerate artificial intelligence (AI) applications by offloading mathematical operations from the CPU to the GPU. In the past, GPUs were used to deliver rich, real-time graphics. This is so because they can process large amounts of data in parallel making them ideal for accelerating AI workloads, such as machine learning and deep learning, and other artificial intelligence workloads.

DPU Accelerated Servers will become extremely popular in the future thanks to their ability to offload network functions from the CPU to the DPU, freeing up precious CPU processing power, allowing the CPU to run more applications, and run the operating system as efficiently as possible without being bogged down by handling network activities. In fact, some experts claim that 30% of CPU processing power goes towards handling network and storage functions. Offloading storage and network functions to the DPU frees up precious CPU processing power for functions such as virtual or containerized workloads. Additionally, DPUs can be used to handle functions that include network security, firewall tasks, encryption, and infrastructure management. 

DPUs will become the third component in data center servers along with CPU (central processing units) and GPUs (graphics processing units) because of their ability to accelerate and perform network and storage functions. The CPU would be used for general-purpose computing. The GPU would be used to accelerate artificial intelligence applications. The DPU in a DPU equipped server would be used to process data and move data around the data center. 

Overall, DPUs have a bright future thanks to the ever-increasing amount of data stored in data centers, requiring a solution that can accelerate storage and networking functions performed by high-performance data center servers. DPUs can breathe new life into existing servers because they can reduce the CPU utilization of servers by offloading network and storage functions to the DPU. Estimates indicate that 30% of CPU utilization goes towards networking functions, so moving them to the DPU will provide you with extra CPU processing power. Thus, DPUs can extend the life of your servers for months or even years, depending on how much of your system’s resources are being used for network functions. 

What Are The Components Of A DPU? 

A DPU is a system on a chip that is made from three primary elements. First, data processing units typically have a multi-core CPU that is software programmable. The second element is a high-performance network interface that enables the DPU to parse, process, and efficiently move data through the network. The third element is a rich set of flexible, programmable acceleration engines that offload network and storage functions from the CPU to the DPU. DPUs are often integrated with smart NICs offering powerful network data processing. 

Nvidia is leading the way when it comes to DPUs, recently releasing the Nvidia Bluefield 2 DPU, which is the world’s first data infrastructure on chip architecture, optimized for modern data centers. The Bluefield 2 DPU allows data center servers to offload network and storage functions from the CPU to the DPU, allowing the DPU to handle mundane storage and network functions. 

Nvidia DPUs are accessible through the DOCA SDK, enabling a programmable API for DPU hardware. DOCA enables organizations to program DPUs to accelerate data processing for moving data in and out of servers, virtual machines, and containers. DPUs accelerate network functions and handle east-west traffic associated with VMs and containers and north-south traffic flowing in and out of data centers. That said, where DPUs shine is in moving data within a data center because they are optimized for data movement.  

Furthermore, Nvidia states that DPUs are capable of offloading and accelerating all data center security services. This is so because they include next-generation firewalls, micro-segmentation, data encryption capabilities, and intrusion detection. In the past, security was handled by software utilizing x86 CPUs; however, security can be offloaded to DPUs, freeing up CPU resources for other tasks. 

What Are The Most Common Features Of DPUs? 

DPUs have a ton of features, but here are the most common features that are found on DPUs: 

  • High-speed connectivity via one or multiple 100 Gigabit to 200 Gigabit interfaces 
  • High-speed packet processing 
  • Multi-core processing via ARM or MIPS based CPUs (8x 64-bit Arm CPU Cores)
  • Memory controllers offering support for DDR4 and DDR5 RAM 
  • Accelerators 
  • PCI Express Gen 4 Support 
  • Security features 
  • Custom operating system separated from the host system’s OS 

What Are Some Of The Most Common DPU Solutions? 

Nvidia has released a DPU known as the Nvidia Mellanox BlueField 2 DPU and the BlueField 2X DPU. The BlueField 2X DPU has everything that the BlueField 2 DPU has, plus an additional Ampere GPU, enabling artificial intelligence functionality on the DPU. Nvidia included a GPU on its DPU to handle security, network, and storage management. For example, machine learning or deep learning can run on the data processing unit itself and be used to identify and stop an attempted network breach. Furthermore, Nvidia has stated that it intends to launch Bluefield 3 in 2022 and Bluefield 4 in 2023.  

Companies such as Intel and Xilinx are introducing some DPUs into the space. That said, some of the offerings from Xilinx and Intel are known as SmartNICs. SmartNICs from Xilinx and Intel utilize FPGAs to accelerate network and storage functions. Smart NICs work the same way as do data processing units in that they offload network functions from the CPU to the SmartNIC, freeing up processing power by intelligently delegating network and storage functions to the SmartNIC. FPGAs bring parallelism and customization to the data path because of the reprogrammable nature of FPGAs.  

Why Are DPUs Increasing In Popularity? 

We live in a bare metal data center age where tons of data is being generated daily. This is especially true as the number of IoT devices, autonomous vehicles, connected homes, and connect workplaces come online, saturating data centers with data. So, there is a need for solutions that can enable data centers to cope with the ever-increasing amount of data moving in/out of data centers and the data moving through a data center. 

DPUs contain a data movement system that accelerates data movement and processing operations, offloading networking functions from a server’s processor to the DPU. DPUs are a great way for extracting more processing power out of a server, especially when considering that Moore’s Law has slowed down, pushing organizations to use hardware accelerators to gain more performance from their hardware, reducing an organization’s total cost of ownership since more performance can be extracted from existing hardware, allowing a server to perform more application workloads. 

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