The release supports GB100 capabilities and new library enhancements to cuBLAS, cuFFT, cuSOLVER, cuSPARSE, as well as the release of Nsight Compute 2024.3.
NVIDIA is excited to collaborate with Colfax, Together.ai, Meta, and Princeton University on their recent achievement to exploit the Hopper GPU architecture and...
Measuring the GPU Occupancy of Multi-stream Workloads
NVIDIA GPUs are becoming increasingly powerful with each new generation. This increase generally comes in two forms. Each streaming multi-processor (SM), the...
Universal Scene Description, also called OpenUSD or USD, is an open and extensible framework for creating, editing, querying, rendering, collaborating, and...
Efficient CUDA Debugging: Using NVIDIA Compute Sanitizer with NVIDIA Tools Extension and Creating Custom Tools
NVIDIA Compute Sanitizer is a powerful tool that can save you time and effort while improving the reliability and performance of your CUDA applications....
Building High-Performance Applications in the Era of Accelerated Computing
AI is augmenting high-performance computing (HPC) with novel approaches to data processing, simulation, and modeling. Because of the computational requirements...
While part 1 focused on the usage of the new NVIDIA cuTENSOR 2.0 CUDA math library, this post introduces a variety of usage modes beyond that, specifically...
cuTENSOR 2.0: A Comprehensive Guide for Accelerating Tensor Computations
NVIDIA cuTENSOR is a CUDA math library that provides optimized implementations of tensor operations where tensors are dense, multi-dimensional arrays or array...
Differentiable Slang easily integrates with existing codebases—from Python, PyTorch, and CUDA to HLSL—to aid multiple computer graphics tasks and enable...
Differentiable Slang: A Shading Language for Renderers That Learn
NVIDIA just released a SIGGRAPH Asia 2023 research paper, SLANG.D: Fast, Modular and Differentiable Shader Programming. The paper shows how a single language...
When working with embedded systems such as the Jetson modules, you must optimize your application based on your power budget and compute resources. To avoid...
Accelerated Vector Search: Approximating with RAPIDS cuVS IVF-Flat
Performing an exhaustive exact k-nearest neighbor (kNN) search, also known as brute-force search, is expensive, and it doesn’t scale particularly well to...
GPU acceleration is enabling faster and more intelligent applications than ever before, and the CUDA Toolkit is key to harnessing acceleration on NVIDIA GPUs....
NVIDIA has already made available a GPU driver binary symbols server for Windows. Now, NVIDIA is making available a repository of CUDA Toolkit symbols for...
Efficient CUDA Debugging: How to Hunt Bugs with NVIDIA Compute Sanitizer
Debugging code is a crucial aspect of software development but can be both challenging and time-consuming. Parallel programming with thousands of threads can...
GPU-Accelerated Single-Cell RNA Analysis with RAPIDS-singlecell
Single-cell sequencing has become one of the most prominent technologies used in biomedical research. Its ability to decipher changes in the transcriptome and...
