using csbiginteger lib

Author: igormcoelho

.gitignore

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+*.pyc

.gitmodules

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+[submodule "csBigIntegerpp"]
+	path = csBigIntegerpp
+	url = https://github.com/NeoResearch/csBigInteger.cpp.git

Makefile

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+all:
+	g++ --shared csBigIntegerpp/src/csBigIntegerLib.cpp csBigIntegerpp/src/BigInteger.cpp -lgmp -lgmpxx -o build/csbiginteger.so -fPIC
+
+# test python
+run:
+	export LD_LIBRARY_PATH=. && ./test.py
+
+clean:
+	rm *.so 

build/csbiginteger.so

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+Subproject commit 3eaeddfd95bb96f981e8dd4de94d64cdc582ab34

csBigInteger

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+#!/usr/bin/python
+
+import ctypes
+from ctypes import *   #import Structure
+
+import os
+import os.path
+import re
+
+class BigInteger:
+    def __init__(self):
+        self.lib = ctypes.cdll.LoadLibrary('./build/csbiginteger.so')
+        self.lib.csbiginteger_init_empty.argtypes = [ctypes.c_void_p, ctypes.c_int]
+        self.lib.csbiginteger_init_empty.restype  = ctypes.c_int
+
+    def initEmpty(self, data, datasize):
+        sz = self.lib.csbiginteger_init_empty(data, datasize)
+        return sz

csBigInteger.py

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+#!/usr/bin/python
+# basic example from SimplePyCuda library
+# MIT License - Igor Machado Coelho (2017)
+
+import ctypes
+
+from csBigInteger import BigInteger
+
+import numpy
+'''
+def simpleLoadTest(cuda):
+	lib = ctypes.cdll.LoadLibrary('./__simplepycuda_kernel_doublify.so')
+	lib.kernel_loader.argtypes = [ctypes.c_void_p, grid, block, ctypes.c_ulong, ctypes.c_ulong]
+	a = numpy.random.randn(4,4)
+	a_gpu = cuda.mem_alloc(a.nbytes)
+	lib.kernel_loader(a_gpu, grid(1,1), block(4,4,1), 0, 0)
+	print "Kernel OK"
+	# finish
+
+def classicExample(cuda):
+	a = numpy.random.randn(4,4)
+	a = a.astype(numpy.float32)
+	print a
+	a_gpu = cuda.mem_alloc(a.nbytes)
+	cuda.memcpy_htod(a_gpu, a)
+	mod = SimpleSourceModule(""" 
+          #include<stdio.h>
+          __global__ void doublify ( float* a )
+	  {
+	    int idx = threadIdx.x + threadIdx.y*4;
+	    a[idx] *= 2;
+            printf("oi=%d\\n",idx);
+	  }
+	""","nvcc", ["--ptxas-options=-v","--compiler-options -O3","--compiler-options -Wall"])
+	func = mod.get_function("doublify")
+	# TODO: this next line will be made automatically in get_function method... just need a few more time :)
+	func.argtypes = [ctypes.c_void_p, grid, block, ctypes.c_ulong, ctypes.c_ulong]
+	func(a_gpu, grid(1,1), block(4,4,1), 0, 0)
+	cuda.memcpy_dtoh(a, a_gpu)
+	cuda.deviceSynchronize()
+	print a
+	cuda.free(a_gpu) # this is not necessary in PyCUDA
+	print "Finished"
+'''
+
+def main():
+    big = BigInteger()
+    data = (ctypes.c_uint8*5)()
+    sz = big.initEmpty(data, 5)
+    print('size = ', sz)
+    return 0
+
+if __name__ == '__main__':
+    main()
+
+