71 lines
2.4 KiB
Python
71 lines
2.4 KiB
Python
#!/usr/bin/env python3
|
|
# cd disassemblers/ && git clone --recursive github.com:geohot/cuda_ioctl_sniffer.git
|
|
# LD_PRELOAD=$PWD/disassemblers/cuda_ioctl_sniffer/out/sniff.so GPU=1 python3 test/external/external_multi_gpu.py
|
|
import numpy as np
|
|
from tinygrad.tensor import Tensor
|
|
from tinygrad.helpers import colored
|
|
from tinygrad.helpers import Timing
|
|
from tinygrad.runtime.ops_gpu import CL
|
|
|
|
# TODO: support multidevice in cuda
|
|
device = 'gpu'
|
|
|
|
if __name__ == "__main__":
|
|
sz = 1024*1024*256 # 1 GB
|
|
#sz = 1024*64
|
|
|
|
with Timing("CPU creation: ", on_exit=lambda x: f", {(sz*4*2)/x:.2f} GB/sec"):
|
|
c0 = Tensor.ones(sz, device="cpu").realize()
|
|
c1 = (Tensor.ones(sz, device="cpu")/2).realize()
|
|
|
|
with Timing("CPU -> 0: ", on_exit=lambda x: f", {(sz*4)/x:.2f} GB/sec"):
|
|
a0 = c0.to(f'{device}:0').realize()
|
|
CL.synchronize()
|
|
with Timing("CPU -> 1: ", on_exit=lambda x: f", {(sz*4)/x:.2f} GB/sec"):
|
|
b1 = c1.to(f'{device}:1').realize()
|
|
CL.synchronize()
|
|
|
|
# cross copy. this is going through the CPU
|
|
with Timing("0 -> CPU -> 1: ", on_exit=lambda x: f", {(sz*4)/x:.2f} GB/sec"):
|
|
a1 = a0.to(f'{device}:1').realize()
|
|
CL.synchronize()
|
|
with Timing("1 -> CPU -> 0: ", on_exit=lambda x: f", {(sz*4)/x:.2f} GB/sec"):
|
|
b0 = b1.to(f'{device}:0').realize()
|
|
CL.synchronize()
|
|
|
|
# sum
|
|
with Timing("0+0 -> 0 (sum): ", on_exit=lambda x: f", {(sz*4)/x:.2f} GB/sec"):
|
|
ab0 = (a0 + b0).realize()
|
|
CL.synchronize()
|
|
with Timing("1+1 -> 1 (sum): ", on_exit=lambda x: f", {(sz*4)/x:.2f} GB/sec"):
|
|
ab1 = (a1 + b1).realize()
|
|
CL.synchronize()
|
|
|
|
# cross device sum (does this work?)
|
|
# is this making a copy first? is that copy through the CPU?
|
|
# the slowness comes from the *blocking* clprg call, is this pyopencl?
|
|
with Timing(colored("0+1 -> 0 (sum): ", "red"), on_exit=lambda x: f", {(sz*4)/x:.2f} GB/sec"):
|
|
abx0 = (a0 + b1).realize()
|
|
CL.synchronize()
|
|
|
|
with Timing(colored("1+0 -> 1 (sum): ", "red"), on_exit=lambda x: f", {(sz*4)/x:.2f} GB/sec"):
|
|
abx1 = (b1 + a0).realize()
|
|
CL.synchronize()
|
|
|
|
# copy back
|
|
# NOTE: half of this slowness is caused by allocating memory on the CPU
|
|
with Timing("0 -> CPU: ", on_exit=lambda x: f", {(sz*4)/x:.2f} GB/sec"):
|
|
cc0 = ab0.numpy()
|
|
with Timing("1 -> CPU: ", on_exit=lambda x: f", {(sz*4)/x:.2f} GB/sec"):
|
|
cc1 = ab1.numpy()
|
|
|
|
# same
|
|
print("testing")
|
|
np.testing.assert_allclose(cc0, cc1)
|
|
|
|
# devices
|
|
print(ab0)
|
|
print(ab1)
|
|
print(abx0)
|
|
print(abx1)
|