This is the Linux app named Numba CUDA Target whose latest release can be downloaded as v0.29.0sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named Numba CUDA Target with OnWorks for free.
Follow these instructions in order to run this app:
- 1. Downloaded this application in your PC.
- 2. Enter in our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 3. Upload this application in such filemanager.
- 4. Start the OnWorks Linux online or Windows online emulator or MACOS online emulator from this website.
- 5. From the OnWorks Linux OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 6. Download the application, install it and run it.
SCREENSHOTS
Ad
Numba CUDA Target
DESCRIPTION
Numba CUDA Target is NVIDIA’s maintained CUDA backend for the Numba JIT compiler, enabling developers to write GPU-accelerated code directly in Python. It allows users to define CUDA kernels using Python syntax, which are then compiled into efficient GPU code at runtime using LLVM-based toolchains. This approach significantly lowers the barrier to entry for GPU programming by eliminating the need to write CUDA C++ while still delivering high performance. The project supports the SIMT programming model, allowing developers to control threads, blocks, and memory hierarchies similarly to native CUDA programming. It is also used as a foundation for accelerating higher-level libraries such as RAPIDS, where custom user-defined GPU functions are required. The repository represents the continuation of CUDA support after its deprecation in core Numba, ensuring ongoing development and optimization under NVIDIA’s ecosystem.
Features
- Python-based definition of CUDA kernels
- JIT compilation to GPU-executable code
- SIMT programming model with thread and block control
- Integration with Numba and RAPIDS ecosystems
- Support for GPU memory management and device arrays
- Replacement for deprecated built-in Numba CUDA backend
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/numba-cuda-target.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
