The NVIDIA DOCA framework has evolved to become a vital component of next-generation AI infrastructure. From its initial release to the highly anticipated launch of NVIDIA DOCA 3.0, each version has expanded capabilities for NVIDIA BlueField DPUs and ConnectX SuperNICs, enabling unprecedented AI platform scalability and performance. DOCA leverages BlueField DPUs and SuperNICs through a rich��
]]>The NVIDIA Collective Communications Library (NCCL) implements multi-GPU and multinode communication primitives optimized for NVIDIA GPUs and networking. NCCL is a central piece of software for multi-GPU deep learning training. It handles any kind of inter-GPU communication, be it over PCI, NVIDIA NVLink, or networking. It uses advanced topology detection, optimized communication graphs��
]]>Explore the latest advancements in AI infrastructure, acceleration, and security from March 17-21.
]]>AI factories rely on more than just compute fabrics. While the East-West network connecting the GPUs is critical to AI application performance, the storage fabric��connecting high-speed storage arrays��is equally important. Storage performance plays a key role across several stages of the AI lifecycle, including training checkpointing, inference techniques such as retrieval-augmented generation��
]]>Organizations are increasingly turning to accelerated computing to meet the demands of generative AI, 5G telecommunications, and sovereign clouds. NVIDIA has unveiled the DOCA Platform Framework (DPF), providing foundational building blocks to unlock the power of NVIDIA BlueField DPUs and optimize GPU-accelerated computing platforms. Serving as both an orchestration framework and an implementation��
]]>WEKA, a pioneer in scalable software-defined data platforms, and NVIDIA are collaborating to unite WEKA��s state-of-the-art data platform solutions with powerful NVIDIA BlueField DPUs. The WEKA Data Platform advanced storage software unlocks the full potential of AI and performance-intensive workloads, while NVIDIA BlueField DPUs revolutionize data access, movement, and security.
]]>NVIDIA DOCA enhances the capabilities of NVIDIA networking platforms by providing a comprehensive software framework for developers to leverage hardware acceleration, boosting performance, security, and efficiency. Its ecosystem of APIs, libraries, and tools streamlines development for data center infrastructure, enabling workload offloading, acceleration, and isolation to support modern��
]]>The NVIDIA DOCA software platform unlocks the potential of the NVIDIA BlueField networking platform and provides all needed host drivers for NVIDIA BlueField and ConnectX devices. Optimized for peak performance, DOCA equips users to meet the demands of increasingly complex workloads. Its modular structure offers the flexibility needed to adapt to emerging technologies and higher data throughputs.
]]>The new release includes support for Spectrum-X 1.1 RA and new features for AI Cloud Data Centers.
]]>NVIDIA DOCA GPUNetIO is a library within the NVIDIA DOCA SDK, specifically designed for real-time inline GPU packet processing. It combines technologies like GPUDirect RDMA and GPUDirect Async to enable the creation of GPU-centric applications where a CUDA kernel can directly communicate with the network interface card (NIC) for sending and receiving packets, bypassing the CPU and excluding it��
]]>The NVIDIA DOCA acceleration framework empowers developers with extensive libraries, drivers, and APIs to create high-performance applications and services for NVIDIA BlueField DPUs and SuperNICs. DOCA 2.7 is a comprehensive, feature-rich release that further underpins the scope and value of the DOCA software framework. It offers several new libraries, turn-key applications��
]]>The NVIDIA DOCA 2.6 release includes support for NVIDIA Spectrum-X reference architecture with the NVIDIA BlueField-3 SuperNIC and enhances DOCA host-based networking (HBN).
]]>As a comprehensive software framework for data center infrastructure developers, NVIDIA DOCA has been adopted by leading AI, cloud, enterprise, and ISV innovators. The release of DOCA 2.5 marks its third anniversary. And, due to the stability and robustness of the code base combined with several networking and platform upgrades, DOCA 2.5 is the first NVIDIA BlueField-3 long-term support (LTS)��
]]>NVIDIA, working with Fujitsu and Wind River, has enabled NTT DOCOMO to launch the first GPU-accelerated commercial Open RAN 5G service in its network in Japan. This makes it the first-ever telco in the world to deploy a GPU-accelerated commercial 5G network. The announcement is a major milestone as the telecom industry strives to address the multi-billion-dollar problem of driving��
]]>Ransomware attacks have become increasingly popular, more sophisticated, and harder to detect. For example, in 2022, a destructive ransomware attack took 233 days to identify and 91 days to contain, for a total lifecycle of 324 days. Going undetected for this amount of time can cause irreversible damage. Faster and smarter detection capabilities are critical to addressing these attacks.
]]>NVIDIA DOCA SDK and acceleration framework empowers developers with extensive libraries, drivers, and APIs to create high-performance applications and services for NVIDIA BlueField DPUs and ConnectX SmartNICs. It fuels data center innovation, enabling rapid application deployment. With comprehensive features, NVIDIA DOCA serves as a one-stop-shop for BlueField developers looking to accelerate��
]]>The NVIDIA DOCA framework aims to simplify the programming and application development for NVIDIA BlueField DPUs and ConnectX SmartNICs. It provides high-level abstraction building blocks relevant to network applications through an SDK, runtime binaries, and high-level APIs that enable developers to rapidly create applications and services. NVIDIA DOCA Flow is a newly updated set of software��
]]>Real-time processing of network traffic can be leveraged by the high degree of parallelism GPUs offer. Optimizing packet acquisition or transmission in these types of applications avoids bottlenecks and enables the overall execution to keep up with high-speed networks. In this context, DOCA GPUNetIO promotes the GPU as an independent component that can exercise network and compute tasks without��
]]>ChatGPT, Stable Diffusion, DALL-E, and similar applications have awakened the world to generative AI. ChatGPT is the fastest-growing application in history. The ease of use and impressive capabilities have attracted over a hundred million users in just a few months. Generative AI has created a sense of urgency for companies to reimagine their products and business models. As NVIDIA CEO Jensen��
]]>Announced in March 2023, NVIDIA DOCA 2.0, the newest release of the NVIDIA SDK for BlueField DPUs, is now available. Together, NVIDIA DOCA and BlueField DPUs accelerate the development of applications that deliver breakthrough networking, security, and storage performance with a comprehensive, open development platform. NVIDIA DOCA 2.0 includes newly added support for the BlueField-3 Data��
]]>Deep packet inspection (DPI) is a critical technology for network security that enables the inspection and analysis of data packets as they travel across a network. By examining the content of these packets, DPI can identify potential security threats such as malware, viruses, and malicious traffic, and prevent them from infiltrating the network. However, the implementation of DPI also comes with��
]]>NVIDIA BlueField-3 data processing units (DPUs) are now in full production, and have been selected by Oracle Cloud Infrastructure (OCI) to achieve higher performance, better efficiency, and stronger security, as announced at NVIDIA GTC 2023. As a 400 Gb/s infrastructure compute platform, BlueField-3 enables organizations to deploy and operate data centers at massive scale.
]]>As part of NVIDIA efforts to advance research towards a more secure data center, the NVIDIA Advanced Development Group is conducting research on quantum key distribution (QKD) technologies, along with other top organizations in Europe and in Israel. The initiatives are funded by the European Union��s Horizon 2020 program and the Israel Innovation Authority. QKD is a highly secure cryptographic��
]]>This post was updated May 8, 2023. A growing number of network applications need to exercise GPU real-time packet processing in order to implement high data rate solutions: data filtering, data placement, network analysis, sensors�� signal processing, and more. One primary motivation is the high degree of parallelism that the GPU can enable to process in parallel multiple packets while��
]]>The latest NVIDIA Cybersecurity Hackathon brought together 10 teams to create exciting cybersecurity innovations using the NVIDIA Morpheus cybersecurity AI framework, NVIDIA BlueField data processing unit (DPU), and NVIDIA DOCA. The event featured seven onsite Israeli teams and three remote teams from India and the UK. Working around the clock for 24 hours, the teams were challenged with��
]]>NVIDIA recently announced the long-term support (LTS) release of NVIDIA DOCA 1.5. NVIDIA DOCA is the open cloud SDK and acceleration framework for NVIDIA BlueField DPUs. It unlocks data center innovation by enabling you to rapidly create applications and services for BlueField DPUs by using industry-standard APIs. The new NVIDIA DOCA 1.5 release includes several important platform��
]]>Supercomputers are used to model and simulate the most complex processes in scientific computing, often for insight into new discoveries that otherwise would be impractical or impossible to demonstrate physically. The NVIDIA BlueField data processing unit (DPU) is transforming high-performance computing (HPC) resources into more efficient systems, while accelerating problem solving across a��
]]>The incredible increase of traffic within data centers along with increased adoption of virtualization is placing strains on the traditional data centers. Customarily, virtual machines rely on software interfaces such as VirtIO to connect with the hypervisor. Although VirtIO is significantly more flexible compared to SR-IOV, it can use up to 50% more compute power in the host��
]]>The acceleration of digital transformation within data centers and the associated application proliferation is exposing new attack surfaces to potential security threats. These new attacks typically bypass the well-established perimeter security controls such as traditional and web application firewalls, making detection and remediation of cybersecurity threats more challenging.
]]>In this new course learn about creating software-defined, cloud-native, DPU-accelerated services with zero-trust protection for increasing the performance and security demands of modern data centers.
]]>The DPU, or data processing unit, is a new class of programmable processors that specializes in moving data around the data center and now joins CPUs and GPUs as the third pillar of modern computing. NVIDIA DOCA is core to the NVIDIA Bluefield DPU offering because it provides ecosystem partners with an open platform to deliver the advanced networking, storage, and security services needed today.
]]>Today��s cybersecurity landscape is changing in waves with threat and attack methods putting the business world on high alert. Modern attacks continue to gain sophistication, staying one step ahead of traditional cyber defense measures, by continuously altering attack techniques. With the increasing use of AI, ML, 5G, and IoT, network speeds readily run at 100G rates or more.
]]>The NVIDIA DOCA Software framework includes everything needed to program the NVIDIA BlueField data processing unit (DPU) and provides a consistent experience regardless of the development environment. NVIDIA offers the following resources: NVIDIA delivers the stack by offering a DOCA SDK for developers and DOCA runtime software for out-of-the-box deployment.
]]>The NVIDIA DOCA software framework provides a comprehensive, open development platform to accelerate the creation of DPU applications. DOCA continues to gain momentum and push the boundaries of the data center to offload, accelerate, and isolate network, storage, security, and management infrastructure. The release of the NVIDIA DOCA 1.3 software framework focuses on new features and enhancements��
]]>The inline processing of network packets using GPUs is a packet-analysis technique useful to a number of different application domains: signal processing, network security, information gathering, input reconstruction, and so on. The main requirement of these application types is to move received packets into GPU memory as soon as possible, to trigger the CUDA kernel responsible to execute��
]]>The IT world is moving to cloud, and cloud is built on containers managed with Kubernetes. We believe the next logical step is to accelerate this infrastructure with data processing units (DPUs) for greater performance, efficiency, and security. Red Hat and NVIDIA are building an integrated cloud-ready infrastructure solution with the management and automation of Red Hat OpenShift combined��
]]>Step-A Step-B Go get a cup of coffee�� Step-C How often have you seen ��Go get a coffee�� in the instructions? As a developer, I found early on that this pesky quip is the bane of my life. Context switches, no matter the duration, are a high cost to pay in the application development cycle. Of all the steps that require you to step away, waiting for an application to compile��
]]>The third in a series of global NVIDIA DOCA Hackathons took place on March 21, during NVIDIA 2022 GTC. Competing in the event were 10 teams from a variety of universities, enterprises, and technology partners from across Europe and the Middle East. As part of GTC, NVIDIA CEO, Jensen Huang, gave a powerful keynote highlighting efforts in AI to supercharge industries including DPU and switching.
]]>The NVIDIA BlueField-2 data processing unit (DPU) delivers unmatched software-defined networking (SDN) performance, programmability, and scalability. It integrates eight Arm CPU cores, the secure and advanced ConnectX-6 Dx cloud network interface, and hardware accelerators that together offload, accelerate, and isolate SDN functions, performing connection tracking, flow matching��
]]>In this post, I take you through the creation of the FRR DOCA dataplane plugin and show you how to offload PBR rules using the new DOCA flow library. In the previous post, you saw the creation of a FRR dataplane plugin to accelerate PBR rules on BlueField using the DPDK library. For part 1, see Developing Applications with NVIDIA BlueField DPU and DPDK. I still used the DPDK APIs for��
]]>The NVIDIA BlueField DPU (data processing unit) can be used for network function acceleration. This network offloading is possible using DPDK and the NVIDIA DOCA software framework. In this series, I built an app and offloaded it two ways, through the use of DPDK and the NVIDIA DOCA SDK libraries. I recorded each step as a separate code patch and provided the complete steps in each series.
]]>On January 13, NVIDIA hosted an online workshop to engage with the NVIDIA DOCA developer community in China. The core team at NVIDIA and leading partner representatives joined the workshop to discuss the application scenarios of NVIDIA BlueField DPUs and the NVIDIA DOCA software framework for cloud, data center, and edge. The workshop focused on the requirements for DOCA developers in key��
]]>The latest NVIDIA DPU Hackathon brought together 11 teams with the goal of creating new and exciting data processing unit (DPU) innovations. Spanning 24 hours from December 8 to 9, the second in a series of global NVIDIA DPU Hackathons received over 50 team applications from various universities and enterprises. As a new class of programmable processors, a DPU ignites unprecedented��
]]>Following the announcement of Early Access to the NVIDIA DOCA Software Framework at this year��s GTC, held in November, we launched a self-paced DOCA course to help you start working with this new framework. The NVIDIA Deep Learning Institute (DLI) is offering a free self-paced course titled ��Introduction to DOCA for DPUs.�� In this 2-hour introductory course, you will learn how DOCA and DPUs enable��
]]>Today, NVIDIA released the NVIDIA DOCA 1.2 software framework for NVIDIA BlueField DPUs, the world��s most advanced data processing unit (DPU). Designed to enable the NVIDIA BlueField ecosystem and developer community, DOCA is the key to unlocking the potential of the DPU by offering services to offload, accelerate, and isolate infrastructure applications services from the CPU.
]]>NVIDIA recently introduced the NVIDIA DOCA 1.2 software framework for NVIDIA BlueField DPUs, the world��s most advanced Data Processing Unit (DPU). This latest release builds on the momentum of the DOCA early access program to enable partners and customers to accelerate the development of applications and holistic zero trust solutions on the DPU. NVIDIA is working with leading platform vendors��
]]>The modern data center is becoming increasingly difficult to manage. There are billions of possible connection paths between applications and petabytes of log data. Static rules are insufficient to enforce security policies for dynamic microservices, and the sheer magnitude of log data is impossible for any human to analyze. AI provides the only path to the secure and self-managed data��
]]>Today NVIDIA introduced the NVIDIA DOCA 1.2 software for NVIDIA BlueField DPUs, the world��s most advanced data processing unit (DPU). This latest release, scheduled for late November, builds on the momentum of the NVIDIA DOCA early access program to enable partners and customers to accelerate the development of applications and holistic zero trust solutions on the DPU. New authentication��
]]>The global series of regional Data Processing Unit (DPU) software hackathons continues in North America. Aimed at advancing research and development in data center and AI technologies, this free event is open to all developers, innovators, and technologists. On December 8, 2021, 10 teams will compete to develop accelerated applications for the NVIDIA? BlueField? DPU using NVIDIA? DOCA��
]]>The early access version of the NVIDIA DOCA SDK was announced earlier this year at GTC. DOCA marks our focus on finding new ways to accelerate computing. The emergence of the DPU paradigm as the evolution of SmartNICs is finally here. We enable developers and application architects to squeeze more value out of general-purpose CPUs by accelerating, offloading, and isolating the data center��
]]>Today NVIDIA released the NVIDIA DOCA 1.1 software framework for NVIDIA BlueField DPUs, the world��s most advanced Data Processing Unit (DPU). This latest release aims to continue the momentum of the DOCA early access program with additional DOCA SDK, Runtime, and Services to enable developers to accelerate the development of applications on the DPU. DPUs are increasingly useful for��
]]>As organizations embrace cloud and edge computing models, they are looking for more efficient, modern computing architectures that create a secure, accelerated, virtual private cloud (SA-VPC), able to support multi-tenancy and deliver applications at data center scale with all the necessary levels of performance and cyber protection. NVIDIA is enabling these organizations to easily develop��
]]>First in a global series of NVIDIA developer events, the DPU hackathons unleashes breakthrough technologies built on NVIDIA DOCA, furthering advancements in AI, cloud and accelerated computing ��The data center is the new unit of computing. Cloud computing and AI are driving fundamental changes in the architecture of data centers.�� �� NVIDIA founder and CEO Jensen Huang At NVIDIA where non��
]]>DOCA is a software framework for developing applications on BlueField DPUs. By using DOCA, you can offload infrastructure workloads from the host CPU and accelerate them with the BlueField DPU. This enables an infrastructure that is software-defined yet hardware accelerated, maximizing both performance and flexibility in the data center. NVIDIA first introduced DOCA in October 2020.
]]>As NVIDIA CEO Jensen Huang stated in last year��s GTC, ��the data center is the new unit of computing.�� Traditional way of using the server as the unit of computing is fading away quickly. More and more applications are moving to data centers that are located at the edge, in different availability zones or in private enterprise clouds. Modern workloads such as AI/ML, edge computing��
]]>Today, in his NVIDIA GTC Fall keynote, CEO Jensen Huang introduced a new kind of processor, the BlueField-2 data processing unit (DPU), a powerful new software development kit for the DPU, DOCA, along with a three year roadmap of DPU and AI innovation. The NVIDIA BlueField-2 DPU is the world��s first data center infrastructure on a chip architecture optimized for modern enterprise data centers.
]]>