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### Local examples ###
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#### CUDA example ####
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Based on the pi estimation :
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* basic code : [pi_gpu.cu](gpu/pi-test/pi_gpu.cu)
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* better implemented code : [pi_gpu_v2.cu](gpu/pi-test/pi_gpu_v2.cu)
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* Multi-GPU version : [pi_gpu_multiGPU.cu](gpu/pi-test/pi_gpu_multiGPU.cu)
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* Using [thrust](http://docs.nvidia.com/cuda/thrust/) : [pi_gpu_thrust.cu](gpu/pi-test/pi_gpu_thrust.cu)
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* basic code : [pi_gpu.cu](https://gitlab.in2p3.fr/lpnhe/HPC/tree/master/gpu/pi-test/pi_gpu.cu)
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* better implemented code : [pi_gpu_v2.cu](https://gitlab.in2p3.fr/lpnhe/HPC/tree/master/gpu/pi-test/pi_gpu_v2.cu)
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* Multi-GPU version : [pi_gpu_multiGPU.cu](https://gitlab.in2p3.fr/lpnhe/HPC/tree/master/gpu/pi-test/pi_gpu_multiGPU.cu)
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* Using [thrust](http://docs.nvidia.com/cuda/thrust/) : [pi_gpu_thrust.cu](https://gitlab.in2p3.fr/lpnhe/HPC/tree/master/gpu/pi-test/pi_gpu_thrust.cu)
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#### Python examples ####
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In order to use pythlon examples, one should install some python modules locally. The simpliest way is to use [anaconda](https://www.continuum.io/downloads), which gives a local python environment, and install needed modules which does not require root privileges. The tool is available on the GPU machine. To proceed :
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