试用Python语言编写GPU程序（PyCUDA环境）实现Mandelbrot集

以下是使用Python语言编写GPU程序（PyCUDA环境）实现Mandelbrot集的代码： ```python import pycuda.autoinit import pycuda.driver as drv import numpy as np from pycuda.compiler import SourceModule # 定义Mandelbrot集计算函数 mandelbrot_kernel = """ __global__ void mandelbrot(float *real, float *imag, int *output, int max_iter) { const int idx = blockIdx.x * blockDim.x + threadIdx.x; const int idy = blockIdx.y * blockDim.y + threadIdx.y; const int width = gridDim.x * blockDim.x; const int height = gridDim.y * blockDim.y; const int index = idy * width + idx; float c_real = real[idx]; float c_imag = imag[idy]; float z_real = 0.0f; float z_imag = 0.0f; int iter = 0; while (z_real * z_real + z_imag * z_imag < 4.0f && iter < max_iter) { float temp_real = z_real * z_real - z_imag * z_imag + c_real; float temp_imag = 2.0f * z_real * z_imag + c_imag; z_real = temp_real; z_imag = temp_imag; iter++; } output[index] = iter; } """ # 设置参数 width, height = 512, 512 max_iter = 200 block_size = (16, 16) grid_size = (int(np.ceil(width / block_size[0])), int(np.ceil(height / block_size[1]))) # 创建输入数据 real = np.linspace(-2, 1, width).astype(np.float32) imag = np.linspace(-1, 1, height).astype(np.float32) # 创建输出数据 output = np.zeros((height, width), dtype=np.int32) # 编译CUDA代码 mod = SourceModule(mandelbrot_kernel) # 获取函数句柄 mandelbrot_func = mod.get_function("mandelbrot") # 将数据传输到GPU real_gpu = drv.mem_alloc(real.nbytes) imag_gpu = drv.mem_alloc(imag.nbytes) output_gpu = drv.mem_alloc(output