Publication date
October 2021
DOIAbstract
fix building on systems with GPUs supporting multiple CUDA_ARCHITECTURES (#16) add SWIG example doc
fix building on systems with GPUs supporting multiple CUDA_ARCHITECTURES (#16) add SWIG example doc
This chapter demonstrates how to leverage the Thrust parallel template library to implement high-per...
NumPy is a module for Python. It is well known because of how easy it is to write scientific program...
In recent years, Graphics Processing Units (GPUs) have emerged as a powerful accelerator for general...
add SWIG support via cuvec.i (#7) add & document example_swig improve & document example_mod fix ext...
catch exceptions update __init__ keywords build updates add CUVEC_DEBUG flag (default: OFF) use CMak...
Unifying Python/C++/CUDA memory: Python buffered array C++11 std::vector CUDA managed memory. P...
Jupyter Notebooks are omnipresent in the modern scientist's and engineer's toolbox just as CUDA C++ ...
add N-dimensional conv_separable() GPU (fallback: CPU) function (#15) use https://github.com/AMYPAD/...
CUDA integration for Python, plus shiny featuresIf you use this software, please cite it as below
To face the programming challenges related to heterogeneous computing, Intel recently introduced one...
cuSignal is a GPU accelerated signal processing library built around a SciPy Signal-like API, CuPy, ...
This chapter demonstrates how to leverage the Thrust parallel template library to implement high-per...
NumPy is a module for Python. It is well known because of how easy it is to write scientific program...
In recent years, Graphics Processing Units (GPUs) have emerged as a powerful accelerator for general...
add SWIG support via cuvec.i (#7) add & document example_swig improve & document example_mod fix ext...
catch exceptions update __init__ keywords build updates add CUVEC_DEBUG flag (default: OFF) use CMak...
Unifying Python/C++/CUDA memory: Python buffered array C++11 std::vector CUDA managed memory. P...
Jupyter Notebooks are omnipresent in the modern scientist's and engineer's toolbox just as CUDA C++ ...
add N-dimensional conv_separable() GPU (fallback: CPU) function (#15) use https://github.com/AMYPAD/...
CUDA integration for Python, plus shiny featuresIf you use this software, please cite it as below
To face the programming challenges related to heterogeneous computing, Intel recently introduced one...
cuSignal is a GPU accelerated signal processing library built around a SciPy Signal-like API, CuPy, ...
This chapter demonstrates how to leverage the Thrust parallel template library to implement high-per...
NumPy is a module for Python. It is well known because of how easy it is to write scientific program...
In recent years, Graphics Processing Units (GPUs) have emerged as a powerful accelerator for general...
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