PyCUDA帮助说明了如何创建一个空数组或归零数组,但没有说明如何将现有的 numpy 数组移动(?)到页面锁定的内存中。我是否需要获取 numpy 数组的指针并将其传递给pycuda.driver.PagelockedHostAllocation
?我该怎么做?
更新
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更新 2
谢谢你的帮助。现在内存传输是页面锁定的,但程序以以下错误结束:
PyCUDA WARNING: a clean-up operation failed (dead context maybe?)
cuMemFreeHost failed: invalid context
这是更新的代码:
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import numpy as np
import ctypes
from pycuda import driver, compiler, gpuarray
from pycuda.tools import PageLockedMemoryPool
import pycuda.autoinit
memorypool = PageLockedMemoryPool()
indata = np.random.randn(5).astype(np.float32)
outdata = gpuarray.zeros(5, dtype=np.float32)
pinnedinput = memorypool.allocate(indata.shape,np.float32)
source = indata.ctypes.data_as(ctypes.POINTER(ctypes.c_float))
dest = pinnedinput.ctypes.data_as(ctypes.POINTER(ctypes.c_float))
sz = indata.size * ctypes.sizeof(ctypes.c_float)
ctypes.memmove(dest,source,sz)
kernel_code = """
__global__ void kernel(float *indata, float *outdata) {
int globalid = blockIdx.x * blockDim.x + threadIdx.x ;
outdata[globalid] = indata[globalid]+1.0f;
}
"""
mod = compiler.SourceModule(kernel_code)
kernel = mod.get_function("kernel")
kernel(
driver.In(pinnedinput), outdata,
grid = (5,1),
block = (1, 1, 1),
)
print indata
print outdata.get()
memorypool.free_held()