Developer Resources For Telecommunications
A hub of news, SDKs, technical resources, and more for developers working in the telco industry.
App Frameworks and SDKs
NVIDIA Aerial is an application framework for building high-performance, software-defined, GPU-accelerated 5G virtual radio access networks (RANs). NVIDIA Aerial provides two critical SDKs—cuVNF and cuBB—to help you optimize your results with parallel processing on GPU for baseband signals and data flow.
NVIDIA CloudXR SDK
The NVIDIA CloudXR™ SDK enables streaming of graphics-intensive augmented reality, virtual reality, or mixed reality content—often called extended reality (XR)—over a radio signal (5G or Wi-Fi) to one or more devices. The SDK also enables streaming of Open VR applications to a number of 5G-connected Android devices.
NVIDIA TensorRT SDK
NVIDIA Triton Inference Server
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Machine Learning on the Edge for 5G
In modern mobile communication, edge computing addresses latency constraints, reduces bandwidth, and saves energy. This talk covers three machine learning approaches that are especially suitable for edge computing on GPUs.
Building O-RAN-Based High-Performance 5G RAN Systems
This session reviews implementation of the fronthaul I/O interface to enable an O-RAN-compliant dialog with a radio unit, giving an overview of the most challenging issues faced in differentiating between hardware- and software-accelerated features.
NVIDIA EGX Platform for Edge Computing
The EGX platform is NVIDIA’s solution for edge computing. As IoT sensor networks get more complicated and computationally challenging, we need better node management, orchestration tools, and powerful processors like NVIDIA GPUs at the edge.
Transforming Next Generation Wireless with 5T for 5G and the NVIDIA Aerial SDK
NVIDIA Mellanox 5T for 5G technology provides a real-time and high-performance solution for building an efficient, time-synchronized CloudRAN infrastructure.
Building an Accelerated 5G CloudRAN at the Edge
Network system developers are using the Aerial SDK to build massive multiple-input and multiple-output (MIMO)-capable, fully cloud-native RAN, supporting a wide range of next-generation AI and IoT services using commercial off-the-shelf (COTS) servers.
GPU-Based Design to Achieve 100µs Scheduling for 5G NR
The next-generation 5G New Radio (NR) cellular technology design supports extremely diverse use cases, such as broadband human-oriented communications and time-sensitive applications with ultra-low latency.
DeepSig: Deep Learning for Wireless Communications
Communications engineering strives to further improve metrics like throughput and interference robustness while scaling to support the explosion of low-cost wireless devices. These often-competing needs make system complexity intractable.
NVIDIA CloudXR Delivers Low-Latency AR/VR Streaming Over 5G Networks to Any Device
The CloudXR SDK helps businesses create and deliver high-quality, wireless AR and VR experiences from any application based on OpenVR, the broadly used VR hardware and software interface.
Monetizing AI at the Edge of Your 5G Network
AI is transforming the high-value, revenue-generating services that telcos can deliver for their enterprise customers at the edge across super-fast 5G networks. Hear how 5G, AI, and the edge unlock a new revenue roadmap for telcos.
Unlocking the Power of 5G vRAN with Aerial SDK
Explore key features of the Aerial SDK and how it can be used to execute complex mathematical computations for L1 processing.
5G at the Edge
Find out how Verizon is pairing 5G with an NVIDIA Quadro RTX™ server on the network edge to create dynamic real-world applications for AR and VR. You'll also learn about the components necessary to create a GPU-based Edge Platform and how to offload GPU intensive processes to the mobile edge.
Accelerate Your Operations in Telecom with AI
Using NVIDIA GPU-accelerated solutions, telecom service providers can speed time to data and insights for higher network quality, optimized resource planning, and better customer service. Learn how these transformations enable telecom innovators to use AI-optimized models for maximized productivity at the lowest TCO.
Bring Real-Time AI to the Edge
AI is erupting at the edge. On factory floors. In stores. On city streets. In urgent care facilities. But it needs a cloud-native, scalable, GPU-accelerated platform that can drive decisions in real time and allow every industry to deliver automated intelligence to the point of action. Learn how to deploy AI at the edge with the NVIDIA EGX™ platform.
NVIDIA DEEP LEARNING INSTITUTE
The NVIDIA Deep Learning Institute (DLI) offers hands-on training in AI and accelerated computing to solve real-world problems. Training is available as self-paced, online courses or in-person, instructor-led workshops.
Fundamentals of Accelerated Computing with CUDA C/C++
Learn how to accelerate and optimize existing C/C++ CPU-only applications to leverage the power of GPUs using the most essential CUDA techniquest and the NVIDIA Nsight™ System profiler.
High-Performance Computing with Containers
Reduce complexity and improve portability and efficiency of your code by using a containerized environment for high-performance computing (HPC) application development.
Introduction to AI in the Data Center
Explore an introduction to AI, GPU computing, NVIDIA AI software architecture, and how to implement and scale AI workloads in the data center. You'll understand how AI is transforming society and how to deploy GPU computing to the data center to facilitate this transformation.
NVIDIA Telecommunications News
Demo: 5G CloudRAN and Edge AI End-to-End System Featuring Aerial SDK and EGX Platform
5G CloudRAN is the cloud-native architecture that supports PHY layer processing for high-speed, low bandwidth, software-defined network applications. See an end-to-end demonstration of 5G CloudRAN on NVIDIA GPU for fast processing.
New Real-Time SmartNIC Technology 5T-for-5G Optimizes 5G Access and Edge Networks
NVIDIA announced a new technology embedded in its NVIDIA Mellanox ConnectX-6 Dx SmartNIC and BlueField-2 I/O Processing Unit to optimize 5G networks.
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