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        "author": "Igor Machado and Rodolfo Araujo",
        "author_email": "igor.machado@ime.uerj.br",
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        "classifiers": [
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 2"
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        "description": "The library cudapp is the basis of SimplePyCuda, a simple wrapper for CUDA functions in Python.\nThe idea is to workaround the issues regarding Context in old CUDA versions, that persist on PyCuda.\n\nUsage:\n\n\"make [all]\" will build the lib cudapp.so\n\n\"make run\" will execute \"testSimplePyCuda.py\", using library \"simplepycuda.py\".\n\n==========================\n\nIn Python:\n\n```python\nimport ctypes\nimport numpy\nfrom simplepycuda import SimplePyCuda, SimpleSourceModule, grid, block\n\ndef classicExample(cuda):\n\ta = numpy.random.randn(4,4)\n\ta = a.astype(numpy.float32)\n\tprint a\n\ta_gpu = cuda.mem_alloc(a.nbytes)\n\tcuda.memcpy_htod(a_gpu, a)\n\tmod = SimpleSourceModule(\"\"\"\n          #include<stdio.h>\n          __global__ void doublify ( float* a )\n\t  {\n\t    int idx = threadIdx.x + threadIdx.y*4;\n\t    a[idx] *= 2;\n            //printf(\"oi=%d\\\\n\",idx);\n\t  }\n\t\"\"\")\n\tfunc = mod.get_function(\"doublify\")\n\t# TODO: this next line will be made automatically in get_function method... just need a few more time :)\n\tfunc.argtypes = [ctypes.c_void_p, grid, block, ctypes.c_ulong, ctypes.c_ulong]\n\tfunc(a_gpu, grid(1,1), block(4,4,1), 0, 0)\n\tcuda.memcpy_dtoh(a, a_gpu)\n\tcuda.deviceSynchronize()\n\tprint a\n\tcuda.free(a_gpu) # this is not necessary in PyCUDA\n\tprint \"Finished\"\n\ndef main():\n\tcuda = SimplePyCuda()\n\n\tclassicExample(cuda)\t\n\treturn 0\n```\n\n[MIT License](LICENSE) - Igor Machado Coelho and Rodolfo Pereira Araujo (2017)",
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        "license": "MIT",
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        "name": "simplepycuda",
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        "summary": "A simple wrapper for CUDA functions in Python.",
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