PyCUDAライブラリは、PythonプログラムでNvidia 3090グラフィックカードを利用するのに適した選択肢です。ここでは、PyCUDAを使用してデータのリストに対してSHA-256ハッシュ関数を10万回実行する方法を、小さいながらも機能的な例として紹介します：

```
import pycuda.autoinit
import pycuda.driver as drv
import numpy
from pycuda.compiler import SourceModule

# Define the CUDA kernel for running SHA-256 hash function
mod = SourceModule("""
__global__ void sha256(unsigned char *input, unsigned char *output, int length)
{
    int idx = blockDim.x * blockIdx.x + threadIdx.x;
    if (idx < length)
    {
        // perform the SHA-256 hash function here (example code not provided)
    }
}
""")

# Allocate memory on the GPU
data = numpy.array(list_of_data, dtype=numpy.uint8)
data_gpu = drv.mem_alloc(data.nbytes)
output_gpu = drv.mem_alloc(len(list_of_data)*32)

# Copy data from CPU to GPU
drv.memcpy_htod(data_gpu, data)

# Call the CUDA kernel with 100,000 blocks, each containing a single thread
sha256 = mod.get_function("sha256")
sha256(data_gpu, output_gpu, numpy.int32(len(list_of_data)), block=(1,1,1), grid=(100000,1,1))

# Copy results from GPU to CPU
output = numpy.empty_like(data)
drv.memcpy_dtoh(output, output_gpu)

# Free GPU memory
data_gpu.free()
output_gpu.free()
```

この例では、PythonでCUDAカーネルを書き、GPUにメモリを割り当て、 CPUからGPUにデータをコピーし、CUDAカーネルを呼び出し、GPUからCPUに結果をコ ピーし、GPUメモリを解放する方法を示しています。実際の SHA-256 ハッシュ関数のコードは、簡潔にするために省略されていることに注意してください。
The PyCUDA library is a good choice for utilizing your Nvidia 3090 graphics card in your Python program. Here is a small but functional example of how you could use PyCUDA to run the SHA-256 hash function 100,000 times on a list of data:

"
import pycuda.autoinit
import pycuda.driver as drv
import numpy
from pycuda.compiler import SourceModule

# Define the CUDA kernel for running SHA-256 hash function
mod = SourceModule("""
__global__ void sha256(unsigned char *input, unsigned char *output, int length)
{
    int idx = blockDim.x * blockIdx.x + threadIdx.x;
    if (idx < length)
    {
        // perform the SHA-256 hash function here (example code not provided)
    }
}
""")

# Allocate memory on the GPU
data = numpy.array(list_of_data, dtype=numpy.uint8)
data_gpu = drv.mem_alloc(data.nbytes)
output_gpu = drv.mem_alloc(len(list_of_data)*32)

# Copy data from CPU to GPU
drv.memcpy_htod(data_gpu, data)

# Call the CUDA kernel with 100,000 blocks, each containing a single thread
sha256 = mod.get_function("sha256")
sha256(data_gpu, output_gpu, numpy.int32(len(list_of_data)), block=(1,1,1), grid=(100000,1,1))

# Copy results from GPU to CPU
output = numpy.empty_like(data)
drv.memcpy_dtoh(output, output_gpu)

# Free GPU memory
data_gpu.free()
output_gpu.free()
"

This example demonstrates how to write a CUDA kernel in Python, allocate memory on the GPU, copy data from CPU to GPU, call the CUDA kernel, copy results from GPU to CPU, and free GPU memory. Note that the code for the actual SHA-256 hash function has been omitted for brevity.