当我使用cupy处理一些大数组时,出现了内存不足的错误,但是当我检查nvidia-smi查看内存使用情况时,它没有达到我的GPU内存的限制,我正在使用nvidia geforce RTX 2060,GPU 内存为 6 GB,这是我的代码:
import cupy as cp
mempool = cp.get_default_memory_pool()
print(mempool.used_bytes()) # 0
print(mempool.total_bytes()) # 0
a = cp.random.randint(0, 256, (10980, 10980)).astype(cp.uint8)
a = a.ravel()
print(a.nbytes) # 120560400
print(mempool.used_bytes()) # 120560640
print(mempool.total_bytes()) # 602803712
# when I finish create this array, the nvidia-smi shows like this
#+-----------------------------------------------------------------------------+
| NVIDIA-SMI 430.86 Driver Version: 430.86 CUDA Version: 10.2 |
|-------------------------------+----------------------+----------------------+
| GPU Name TCC/WDDM | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GeForce RTX 2060 WDDM | 00000000:01:00.0 On | N/A |
| N/A 46C P8 9W / N/A | 1280MiB / 6144MiB | 1% Default |
+-------------------------------+----------------------+----------------------+
# but then I run this command, and error cames out
s_values, s_idx, s_counts = cp.unique(
a, return_inverse=True, return_counts=True)
# and the error shows
# cupy.cuda.memory.OutOfMemoryError: out of memory to allocate 964483584 bytes (total 5545867264 bytes)
# the nvidia-smi shows
# +-----------------------------------------------------------------------------+
| NVIDIA-SMI 430.86 Driver Version: 430.86 CUDA Version: 10.2 |
|-------------------------------+----------------------+----------------------+
| GPU Name TCC/WDDM | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GeForce RTX 2060 WDDM | 00000000:01:00.0 On | N/A |
| N/A 45C P8 9W / N/A | 5075MiB / 6144MiB | 3% Default |
+-------------------------------+----------------------+----------------------+
似乎有足够的空间可以使用,为什么会发生这个错误,这是因为我的 GPU 没有足够的内存,还是因为我的代码错误或我没有正确分配内存。