CUDA C++ Compiler Updates Impacting ELF Visibility and Linkage
In the next CUDA major release, CUDA 13.0, NVIDIA is introducing two significant changes to the NVIDIA CUDA Compiler Driver (NVCC) that will impact ELF...
Applying Specialized LLMs with Reasoning Capabilities to Accelerate Battery Research
Scientific research in complex fields like battery innovation is often slowed by manual evaluation of materials, limiting progress to just dozens of candidates...
Applying Autoencoder-Based GNNs for High-Throughput Network Anomaly Detection in NetFlow Data
As modern enterprise and cloud environments scale, the complexity and volume of network traffic increase dramatically. NetFlow is used to record metadata about...
Extending the NVIDIA Agent Intelligence Toolkit to Support New Agentic Frameworks
NVIDIA Agent Intelligence toolkit is an open-source library for efficiently connecting and optimizing teams of AI agents. It focuses on enabling developers to...
Turbocharge LLM Training Across Long-Haul Data Center Networks with NVIDIA Nemo Framework
Multi-data center training is becoming essential for AI factories as pretraining scaling fuels the creation of even larger models, leading the demand for...
Revolutionizing Neural Reconstruction and Rendering in gsplat with 3DGUT
Realistic 3D simulation is becoming a cornerstone of modern AI and graphics, from training autonomous vehicles (AV) to powering robotics and digital twins....
Accelerate Deep Learning and LLM Inference with Apache Spark in the Cloud
Apache Spark is an industry-leading platform for big data processing and analytics. With the increasing prevalence of unstructured data—documents, emails,...
Building Nemotron-CC, A High-Quality Trillion Token Dataset for LLM Pretraining from Common Crawl Using NVIDIA NeMo Curator
Curating high-quality pretraining datasets is critical for enterprise developers aiming to train state-of-the-art large language models (LLMs). To enable...
Using Python to Automate 3D Workflows with OpenUSDÂ
Universal Scene Description (OpenUSD) offers a powerful, open, and extensible ecosystem for describing, composing, simulating, and collaborating within complex...
LLM Inference Benchmarking Guide: NVIDIA GenAI-Perf and NIM
This is the second post in the LLM Benchmarking series, which shows how to use GenAI-Perf to benchmark the Meta Llama 3 model when deployed with NVIDIA NIM. ...
Integrate and Deploy Tongyi Qwen3 Models into Production Applications with NVIDIA
Alibaba recently released Tongyi Qwen3, a family of open-source hybrid-reasoning large language models (LLMs). The Qwen3 family consists of two MoE models,...
NVIDIA Blackwell and NVIDIA CUDA 12.9 Introduce Family-Specific Architecture Features
One of the earliest architectural design decisions that went into the CUDA platform for NVIDIA GPUs was support for backward compatibility of GPU code. This...
Stacking Generalization with HPO: Maximize Accuracy in 15 Minutes with NVIDIA cuML
Stacking generalization is a widely used technique among machine learning (ML) engineers, where multiple models are combined to boost overall predictive...
When interacting with transformer-based models like large language models (LLMs) and vision-language models (VLMs), the structure of the input shapes the...
R²D²: Adapting Dexterous Robots with NVIDIA Research Workflows and Models
Robotic arms are used today for assembly, packaging, inspection, and many more applications. However, they are still preprogrammed to perform specific and often...
