NVIDIA/CUDALibrarySamples resource

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What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

NVIDIA's official collection of sample programs demonstrating the use of GPU-accelerated CUDA libraries such as cuBLAS, cuFFT, cuSOLVER, cuSPARSE, cuRAND, NPP, nvJPEG, and nvCOMP. Each sample provides practical, runnable C++/CUDA code showing how to apply these libraries to math, linear algebra, signal and image processing, and compression workloads.

Use cases

• learn how to use cuBLAS for GPU linear algebra
• example code for FFT on GPU with cuFFT
• JPEG encode decode on GPU with nvJPEG
• sparse matrix solver examples with cuSPARSE and cuDSS
• GPU data compression with nvCOMP
• random number generation on GPU with cuRAND
• image and video processing samples with NPP

When to choose

• you are developing CUDA applications and want official, working examples of NVIDIA's accelerated libraries
• you need reference code for GPU linear algebra, FFT, solvers, or image codecs
• you want to evaluate which CUDA library fits your HPC workload

When to avoid

• you need a production-ready library rather than example code
• you have no NVIDIA GPU or CUDA toolchain
• you want high-level frameworks or Python APIs instead of C++/CUDA samples

Facets

learning-resource · maturity active

image-processing compression math graphics sdk gpu-computing developer-tools image-processing tutorials cpp windows cuda cublas cufft cusolver cusparse curand npp nvjpeg nvcomp linear-algebra sample-code nvidia algorithms gpu linux

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