Development & Optimization

Aug 22, 2025

NVIDIA Hardware Innovations and Open Source Contributions Are Shaping AI

Open source AI models such as Cosmos, DeepSeek, Gemma, GPT-OSS, Llama, Nemotron, Phi, Qwen, and many more are the foundation of AI innovation. These models are...
8 MIN READ
Aug 13, 2025

Streamline CUDA-Accelerated Python Install and Packaging Workflows with Wheel Variants

If you’ve ever installed an NVIDIA GPU-accelerated Python package, you’ve likely encountered a familiar dance: navigating to pytorch.org, jax.dev,...
15 MIN READ
Aug 06, 2025

What’s New and Important in CUDA Toolkit 13.0

The newest update to the CUDA Toolkit, version 13.0, features advancements to accelerate computing on the latest NVIDIA CPUs and GPUs. As a major release, it...
19 MIN READ
An illustration representing CUDA.
Aug 04, 2025

Navigating GPU Architecture Support: A Guide for NVIDIA CUDA Developers

If you’ve used the NVIDIA CUDA Compiler (NVCC) for your NVIDIA GPU application recently, you may have encountered a warning message like the following: nvcc...
6 MIN READ
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Jul 24, 2025

Double PyTorch Inference Speed for Diffusion Models Using Torch-TensorRT

NVIDIA TensorRT is an AI inference library built to optimize machine learning models for deployment on NVIDIA GPUs. TensorRT targets dedicated hardware in...
8 MIN READ
Jul 18, 2025

Optimizing for Low-Latency Communication in Inference Workloads with JAX and XLA

Running inference with large language models (LLMs) in production requires meeting stringent latency constraints. A critical stage in the process is LLM decode,...
6 MIN READ
Jul 16, 2025

CUTLASS 3.x: Orthogonal, Reusable, and Composable Abstractions for GEMM Kernel Design

GEMM optimization on GPUs is a modular problem. Performant implementations need to specify hyperparameters such as tile shapes, math and copy instructions, and...
12 MIN READ
Jul 16, 2025

CUTLASS: Principled Abstractions for Handling Multidimensional Data Through Tensors and Spatial Microkernels

In the era of generative AI, utilizing GPUs to their maximum potential is essential to training better models and serving users at scale. Often, these models...
12 MIN READ
Dynamo image.
Jul 15, 2025

NVIDIA Dynamo Adds Support for AWS Services to Deliver Cost-Efficient Inference at Scale

Amazon Web Services (AWS) developers and solution architects can now take advantage of NVIDIA Dynamo on NVIDIA GPU-based Amazon EC2, including Amazon EC2 P6...
4 MIN READ
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Jul 09, 2025

Delivering the Missing Building Blocks for NVIDIA CUDA Kernel Fusion in Python

C++ libraries like CUB and Thrust provide high-level building blocks that enable NVIDIA CUDA application and library developers to write speed-of-light code...
5 MIN READ
Jul 09, 2025

Reinforcement Learning with NVIDIA NeMo-RL: Reproducing a DeepScaleR Recipe Using GRPO

Reinforcement learning (RL) is the backbone of interactive AI. It is fundamental for teaching agents to reason and learn from human preferences, enabling...
5 MIN READ
Jul 07, 2025

Think Smart and Ask an Encyclopedia-Sized Question: Multi-Million Token Real-Time Inference for 32X More Users

Modern AI applications increasingly rely on models that combine huge parameter counts with multi-million-token context windows. Whether it is AI agents...
8 MIN READ
Jul 03, 2025

New Video: Build Self-Improving AI Agents with the NVIDIA Data Flywheel Blueprint

AI agents powered by large language models are transforming enterprise workflows, but high inference costs and latency can limit their scalability and user...
2 MIN READ
Jul 02, 2025

Advanced NVIDIA CUDA Kernel Optimization Techniques: Handwritten PTX

As accelerated computing continues to drive application performance in all areas of AI and scientific computing, there's a renewed interest in GPU optimization...
11 MIN READ
Jun 25, 2025

How to Streamline Complex LLM Workflows Using NVIDIA NeMo-Skills

A typical recipe for improving LLMs involves multiple stages: synthetic data generation (SDG), model training through supervised fine-tuning (SFT) or...
10 MIN READ
Jun 18, 2025

Improved Performance and Monitoring Capabilities with NVIDIA Collective Communications Library 2.26

The NVIDIA Collective Communications Library (NCCL) implements multi-GPU and multinode communication primitives optimized for NVIDIA GPUs and networking. NCCL...
11 MIN READ