A data processing unit (DPU) is a programmable computer processor that tightly integrates a general-purpose CPU with network interface hardware.^[1] Sometimes they are called "IPUs" (for "infrastructure processing unit") or "SmartNICs".^[2] They can be used in place of traditional NICs to relieve the main CPU of complex networking responsibilities and other "infrastructural" duties; although their features vary, they may be used to perform encryption/decryption, serve as a firewall, handle TCP/IP, process HTTP requests, or even function as a hypervisor or storage controller.^[1][3] These devices can be attractive to cloud computing providers whose servers might otherwise spend a significant amount of CPU time on these tasks, cutting into the cycles they can provide to guests.^[1]

AI factories are an emerging use case for DPUs. In these environments, massive amounts of data must be moved rapidly among CPUs, GPUs, and storage systems to handle complex AI workloads. By offloading tasks such as packet processing, encryption, and traffic management, DPUs help reduce latency and improve energy efficiency, enabling these AI factories to maintain the high throughput and scalability needed for advanced machine learning operations.^[4]

Alongside their role in accelerating network and storage functions, DPUs are increasingly viewed as the “third pillar of computing,” complementing both CPUs and GPUs. Unlike traditional processors, a DPU typically resides on a network interface card, allowing data to be processed at the network’s line rate before it reaches the CPU. This approach offloads critical but lower-level system duties—such as security, load balancing, and data routing—from the central processor, thus freeing CPUs and GPUs to focus on application logic and AI-specific computations.^[5]

In 2024, Microsoft introduced the Azure Boost DPU, a custom-designed data processing unit aimed at optimizing network and infrastructure efficiency across its Azure cloud platform. This DPU offloads network-related tasks such as packet processing, security enforcement, and traffic management from central CPUs, enabling better performance for application workloads.^[6][7]

• Network Optimization: The Azure Boost DPU enhances network throughput and reduces latency by processing data packets and offloading these tasks from traditional CPUs.^[8]
• Security Capabilities: It integrates advanced isolation techniques to secure multi-tenant environments, protecting sensitive workloads.^[7]
• Hyperscale Adaptability: Designed for large-scale data centers, the DPU supports Azure’s hyperscale infrastructure, ensuring scalability for modern cloud applications.^[6]

The Azure Boost DPU aligns with the trend of custom silicon development in hyperscale cloud environments. Similar to AWS’s Nitro System and NVIDIA’s BlueField DPUs, Microsoft’s DPU focuses on enhancing cloud efficiency while addressing rising energy and security demands.^[7] This innovation positions Microsoft alongside other cloud leaders leveraging DPUs to optimize data center operations and provide cost-effective, high-performance solutions for customers.^[8]

The introduction of DPUs like Azure Boost reflects a broader shift in the cloud computing industry toward offloading specific functions from general-purpose processors to specialized hardware. Microsoft’s Azure Boost DPU represents its strategy to reduce costs, enhance security, and achieve sustainability goals while improving infrastructure efficiency.^[6][7]

• Compute Express Link (CXL)

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