Showing content from https://github.com/NVIDIA/DALI/issues/5320 below:
GitHub Roadmap 2024 · Issue #5320 · NVIDIA/DALI · GitHub
The following represents a high-level overview of our 2024 plan. Please be aware that this roadmap may change at any time and the order below does not reflect the priority of our future efforts.
We strongly encourage you to comment on our roadmap and provide us with feedback.
Some of the items mentioned below are the continuation of the 2023 effort (#4578)
Improving Usability:
- more pythonic user experience - function prototypes, improved python exception messages
- flexible execution model - data can go from CPU to GPU and back to the GPU in single pipeline, which can utilize NVIDIA Grace Hopper Superchip fast memory transfers
- improved checkpointing - an ability to preserve and restore the DALI processing state from the pipeline and deep learning framework iterator level
- tighter integration with NVIDIA ecosystem - extending function coverage by exposing functionalities from libraries like CV-CUDA or RAPIDS
Extending input format support:
- Extending support of formats and containers with variable frame rate videos
- Adding GPU acceleration for more image formats, like TIFF or new profiles of the existing one
Performance:
- optimizing memory consumption
- operators performance optimizations
New transformations:
We are constantly extending the set of operations supported by DALI. Currently, this section lists the most notable additions to our areas of interest that we plan to do this year. This list is not exhaustive and we plan on expanding the set of operators as the needs or requests arise.
- new transformations for general data processing
- new transformations for image processing
- new transformations for video processing
stiepan, banasraf, szkarpinski and aafaqinq
RetroSearch is an open source project built by @garambo
| Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4