Tuning Flash Attention for Peak Performance in NVIDIA CUDA Tile
In this post, we dive into one of the most critical workloads in modern AI: Flash Attention, where you’ll learn: How to implement Flash Attention using NVIDIA...
Maximizing GPU Utilization with NVIDIA Run:ai and NVIDIA NIM
Organizations deploying LLMs are challenged by inference workloads with different resource requirements. A small embedding model might use only a few gigabytes...
Optimizing Communication for Mixture-of-Experts Training with Hybrid Expert Parallel
In LLM training, Expert Parallel (EP) communication for hyperscale mixture-of-experts (MoE) models is challenging. EP communication is essentially all-to-all,...
Establishing a Scalable Sparse Ecosystem with the Universal Sparse Tensor
Sparse tensors are vectors, matrices, and higher-dimensional generalizations with many zeros. They are crucial in various fields such as scientific computing,...
How to Unlock Local Detail in Coarse Climate Projections with NVIDIA Earth-2
Global climate models are good at the big picture—but local climate extremes, like hurricanes and typhoons, often disappear in the details. Those patterns are...
Learn How NVIDIA cuOpt Accelerates Mixed Integer Optimization using Primal Heuristics
NVIDIA cuOpt is a GPU-accelerated optimization engine designed to deliver fast, high-quality solutions for large, complex decision-making problems. Mixed...
Advanced Large-Scale Quantum Simulation Techniques in cuQuantum SDK v25.11
Simulating large-scale quantum computers has become more difficult as the quality of quantum processing units (QPUs) improves. Validating the results is key to...
Model Quantization: Concepts, Methods, and Why It Matters
AI models are becoming increasingly complex, often exceeding the capabilities of available hardware. Quantization has emerged as a crucial technique to address...
Fusing Communication and Compute with New Device API and Copy Engine Collectives in NVIDIA NCCL 2.28
The latest release of the NVIDIA Collective Communications Library (NCCL) introduces a groundbreaking fusion of communication and computation for higher...
Gen AI Super-Resolution Accelerates Weather Prediction with Scalable, Low-Compute Models
As AI weather and climate prediction models rapidly gain adoption, the NVIDIA Earth-2 platform provides libraries and tools for accelerating solutions using a...
Advancing Robotics Development with Neural Dynamics in Newton
Modern robotics requires more than what classical analytic dynamics provides because of simplified contacts, omitted kinematic loops, and non-differentiable...
How to Connect Distributed Data Centers Into Large AI Factories with Scale-Across Networking
AI scaling is incredibly complex, and new techniques in training and inference are continually demanding more out of the data center. While data center...
Less Coding, More Science: Simplify Ocean Modeling on GPUs With OpenACC and Unified Memory
NVIDIA HPC SDK v25.7 delivers a significant leap forward for developers working on high-performance computing (HPC) applications with GPU acceleration. This...
Scaling LLM Reinforcement Learning with Prolonged Training Using ProRL v2
Currently, one of the most compelling questions in AI is whether large language models (LLMs) can continue to improve through sustained reinforcement learning...
Train with Terabyte-Scale Datasets on a Single NVIDIA Grace Hopper Superchip Using XGBoost 3.0
Gradient-boosted decision trees (GBDTs) power everything from real-time fraud filters to petabyte-scale demand forecasts. XGBoost open source library has long...
