Presentation Open Access
Adding CUDA® Support to Cling: JIT Compile to GPUs
Ehrig, Simeon;
Naumann, Axel;
Huebl, Axel
We present the results of a diploma thesis adding CUDA (runtime) C++ support to cling. Today's HPC systems are heterogeneous and get most of their computing power from so-called accelerator hardware, such as GPUs. Programming GPUs with modern C++ is a perfect match, allowing perfectly tailored and zero-overhead abstractions for performance-critical "kernels".
Nevertheless, tool complexity in development and debugging can be discouraging for new users. We are addressing this by not only adding low-level support for accelerators but also by going up the open source software-stack enabling interactive, CUDA C++ Jupyter notebooks, e.g. through xeus-cling.
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2018_09_10_cling_CUDA.pdf
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| Data volume | 280.6 MB | 280.6 MB |
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- Publication date:
- September 10, 2018
- DOI:
-
- Keyword(s):
- CUDA interactive JIT FOSS Cling
- Meeting:
- ROOT User's Workshop, Sarajevo, Bosnia and Herzegovina, 10-13 September 2018 (Session Parallelism, Heterogeneity and Distributed Data Processing)
- License (for files):
- Creative Commons Attribution Share Alike 4.0 International