NVIDIA/DALI
A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications. observed · 2026-08-28
Health v2 · maintenance only
92/100
- Activity 99
- Release rhythm 78
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 34
- age_days: 3015
- days_rel: 65
- days_push: 7
- n_releases_24m: 16
Adoption not part of the score
5734 stars · 674 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
NVIDIA DALI is a GPU-accelerated data loading and preprocessing library with optimized building blocks and an execution engine for deep learning training and inference. It provides portable pipelines for image, video, and audio processing that integrate with PyTorch, TensorFlow, JAX, and PaddlePaddle.
Use cases
- accelerate data loading for deep learning training
- offload image preprocessing from CPU to GPU
- replace torchvision transforms with GPU-accelerated versions
- build fast image augmentation pipelines
- speed up audio and video preprocessing for ML
- fix CPU bottleneck in multi-GPU training
- portable preprocessing across PyTorch and TensorFlow
When to choose
- training is bottlenecked on CPU data preprocessing
- you have NVIDIA GPUs and want to maximize GPU utilization
- you need consistent preprocessing across multiple DL frameworks
- you process large volumes of images, video, or audio
When to avoid
- you have no NVIDIA GPU or run on Windows/macOS
- your data pipeline is small and not a bottleneck
- you need CPU-only or cloud-agnostic portability
- you rely on custom operators DALI does not provide
Facets
library · maturity active
image-processing audio-processing video-processing machine-learning gpu-computing data-science etl deep-learning machine-learning computer-vision image-processing gpu-computing python cpp data-loading data-augmentation gpu-acceleration cuda data-pipeline pytorch tensorflow preprocessing audio data-engineering linux gpu
10 sources
- readme: https://github.com/NVIDIA/DALI · fetched 2026-08-28 · 23c8884d1e23
- homepage: https://docs.nvidia.com/deeplearning/dali/user-guide/docs/index.html · fetched 2026-08-29 · 2f4a65dd72e9
- site_page: https://docs.nvidia.com/deeplearning/dali/user-guide/docs/examples/getting_started/dynamic_mode.html · fetched 2026-08-29 · 93b1fd759543
- site_page: https://docs.nvidia.com/deeplearning/dali/user-guide/docs/examples/getting_started/torchvision_api.html · fetched 2026-08-29 · 4a6d06af7669
- site_page: https://docs.nvidia.com/deeplearning/dali/user-guide/docs/security.html · fetched 2026-08-29 · 9b62a133418f
- site_page: https://docs.nvidia.com/deeplearning/dali/user-guide/docs/installation.html · fetched 2026-08-29 · c89ee9d493ee
- site_page: https://docs.nvidia.com/deeplearning/dali/user-guide/docs/support_matrix.html · fetched 2026-08-29 · abc8ed5c3d8b
- site_page: https://docs.nvidia.com/deeplearning/dali/user-guide/docs/examples/getting_started/index.html · fetched 2026-08-29 · 666847d5cb95
- site_page: https://docs.nvidia.com/deeplearning/dali/user-guide/docs/examples/getting_started/pipeline_mode.html · fetched 2026-08-29 · f03c6b472027
- site_page: https://docs.nvidia.com/deeplearning/dali/user-guide/docs/pipeline_api_overview.html · fetched 2026-08-29 · b1261fe1365f
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| NVIDIA/DALI | main | 92 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem