What Are DPUs And Why Do We Need Them

We have heard of CPUs and TPUs, now, NVIDIA with the help of its recent acquisition Mellanox is bringing a new class of processors to power up deep learning applications — DPUs or data processing units.

DPUs or Data Processing Units, originally popularised by Mellanox, now wear a new look with NVIDIA; Mellanox was acquired by NVIDIA earlier this year. DPUs are a new class of programmable processor that consists of flexible and programmable acceleration engines which improve applications performance for AI and machine learning, security, telecommunications, storage, among others.

The team at Mellanox has already deployed the first generation of BlueField DPUs in leading high-performance computing, deep learning, and cloud data centres to provide new levels of performance, scale, and efficiency with improved operational agility. 

Subscribe to our Newsletter

Join our editors every weekday evening as they steer you through the most significant news of the day, introduce you to fresh perspectives, and provide unexpected moments of joy
Your newsletter subscriptions are subject to AIM Privacy Policy and Terms and Conditions.

The improvement in performance is due to the presence of high-performance, software programmable, multi-core CPU and a network interface capable of parsing, processing, and efficiently transferring data at line rate to GPUs and CPUs.

According to NVIDIA, a DPU can be used as a stand-alone embedded processor. DPUs are usually incorporated into a SmartNIC, a network interface controller. SmartNICs are ideally suited for high-traffic web servers.

A DPU based SmartNIC is a network interface card that offloads processing tasks that the system CPU would normally handle. Using its own on-board processor, the DPU based SmartNIC may be able to perform any combination of encryption/decryption, firewall, TCP/IP and HTTP processing.

“The CPU is for general-purpose computing, the GPU is for accelerated computing and the DPU, which moves data around the data centre, does data processing.”


Why Do We Need DPUs

These DPUs are known by the name of BlueField that have a unique design that can enable programmability to run at speeds of up to 200Gb/s. The BlueField DPU integrates the NVIDIA Mellanox Connect best-in-class network adapter, encompassing hardware accelerators with advanced software programmability to deliver diverse software-defined solutions.

Organisations that rely on cloud-based solutions, especially can benefit immensely from DPUs. Here are few such instances, where DPUs flourish: –

  • Enabling storage, networking, and security to be part of composable infrastructure for cloud service providers
  • Allowing the operator to facilitate bare metal to the cloud tenant as a service while preserving control over the server and protecting the environment

Bare metal environment is a network where a virtual machine is installed

  • Can enable and isolate environment to accelerate compute-intensive security functions
  • Can store, compute and secure data at the highest speeds while lowering cost and time by analysing data at the edge

The shift towards microservices architecture has completely transformed the way enterprises ship applications at scale. Applications that are based on the cloud have a lot of activity or data generation, even for processing a single application request. According to Mellanox, one key application of DPU is securing the cloud-native workloads.

For instance, Kubernetes security is an immense challenge comprising many highly interrelated parts. The data intensity makes it hard to implement zero-trust security solutions, and this creates challenges for the security team to protect customers’ data and privacy.

As of late last year, the team at Mellanox stated that they are actively researching into various platforms and integrating schemes to leverage the cutting-edge acceleration engines in the DPU-based SmartNICs for securing cloud-native workloads at 100Gb/s.

According to NVIDIA, a DPU comes with the following features:

  • Data packet parsing, matching, and manipulation
  • GPU-Direct accelerators to bypass the CPU and feed networked data directly to GPUs
  • Traffic shaping “packet pacing” accelerator to enable streaming 4K/8K Video
  • Precision timing accelerators for 5G capabilities
  • Crypto acceleration
  • Virtualisation support 
  • Secure Isolation

Know more about DPUs here.

Ram Sagar
I have a master's degree in Robotics and I write about machine learning advancements.

Download our Mobile App


AI Hackathons, Coding & Learning

Host Hackathons & Recruit Great Data Talent!

AIM Research

Pioneering advanced AI market research

Request Customised Insights & Surveys for the AI Industry


Strengthen Critical AI Skills with Trusted Corporate AI Training

Our customized corporate training program on Generative AI provides a unique opportunity to empower, retain, and advance your talent.

AIM Leaders Council

World’s Biggest Community Exclusively For Senior Executives In Data Science And Analytics.

3 Ways to Join our Community

Telegram group

Discover special offers, top stories, upcoming events, and more.

Discord Server

Stay Connected with a larger ecosystem of data science and ML Professionals

Subscribe to our Daily newsletter

Get our daily awesome stories & videos in your inbox

Subscribe to Our Newsletter

The Belamy, our weekly Newsletter is a rage. Just enter your email below.