def test_float16():
# gemv (gemm called)
float16_data = [
rand(3).astype("float16"),
np.asarray(1, dtype=np.float32),
rand(3, 3).astype("float16"),
rand(3).astype("float16"),
np.asarray(0.5, dtype=np.float32),
]
float16_shared = [
gpuarray_shared_constructor(val, target=test_ctx_name)
for val in float16_data
]
o = gemv(*float16_shared)
f = aesara.function([], o, mode=mode_with_gpu)
y, alpha, A, x, beta = float16_data
out = f()
utt.assert_allclose(np.asarray(out), alpha * np.dot(A, x) + beta * y)
topo = f.maker.fgraph.toposort()
assert any(isinstance(n.op, GpuGemm) for n in topo)
# gemm
float16_data = [
rand(3, 3).astype("float16"),
np.asarray(1, dtype=np.float32),
rand(3, 3).astype("float16"),
rand(3, 3).astype("float16"),
np.asarray(0.5, dtype=np.float32),
]
float16_shared = [
gpuarray_shared_constructor(val, target=test_ctx_name)
for val in float16_data
]
o = gpugemm_no_inplace(*float16_shared)
f = aesara.function([], o)
y, alpha, A, x, beta = float16_data
out = f()
utt.assert_allclose(np.asarray(out), alpha * np.dot(A, x) + beta * y)
# dot22
float16_data = [rand(3, 3).astype("float16"), rand(3, 3).astype("float16")]
float16_shared = [gpuarray_shared_constructor(val) for val in float16_data]
o = gpu_dot22(*float16_shared)
f = aesara.function([], o)
x, y = float16_data
out = f()
utt.assert_allclose(np.asarray(out), np.dot(x, y))
def main(dev1, dev2):
init_dev(dev1, "ctx1")
init_dev(dev2, "ctx2")
size = 1024 * 16
data = np.random.randn(size, size).astype("float32")
val1a = aesara.shared(data, target="ctx1")
val1b = aesara.shared(data, target="ctx1")
val1c = aesara.shared(data, target="ctx1")
val1d = aesara.shared(data, target="ctx1")
val2a = aesara.shared(data, target="ctx2")
val2b = aesara.shared(data, target="ctx2")
f1 = aesara.function([],
[gpu_dot22(val1a, val1b),
gpu_dot22(val1c, val1d)])
f2 = aesara.function([],
[gpu_dot22(val1a, val1b),
gpu_dot22(val2a, val2b)])
f3 = aesara.function([], [gpu_dot22(val1a, val1b)])
f4 = aesara.function([], [gpu_dot22(val2a, val2b)])
f5 = aesara.function([], [gpu_dot22(val1a, val1b)[0, 0].transfer("cpu")])
f6 = aesara.function([], [gpu_dot22(val2a, val2b)[0, 0].transfer("cpu")])
# pre-execute to load code to GPU.
r = f1.fn()
r[0].sync(), r[1].sync()
r = f2.fn()
r[0].sync(), r[1].sync()
r = f3.fn()
r[0].sync()
r = f4.fn()
r[0].sync()
r = f5.fn()
r = f6.fn()
r = None
t = time.time()
r = f1.fn()
r[0].sync(), r[1].sync()
t2 = time.time()
r = None
print(f"one ctx async {t2 - t:f}")
t = time.time()
r = f2.fn()
r[0].sync(), r[1].sync()
t2 = time.time()
r = None
print(f"two ctx async {t2 - t:f}")
t = time.time()
r = f3.fn()
r2 = f4.fn()
r[0].sync()
r2[0].sync()
t2 = time.time()
r = None
print(f"two ctx, 2 fct async {t2 - t:f}")
t = time.time()
r = f5.fn()
r2 = f6.fn()
t2 = time.time()
r = None
print(f"two ctx, 2 fct with transfer {t2 - t:f}")
# Multi-thread version
class myThread(threading.Thread):
def __init__(self, name, f, sync):
threading.Thread.__init__(self)
self.f = f
self.name = name
self.sync = sync
def run(self):
# print "Starting " + self.name
# r = self.f.fn(n_calls=10)
r = self.f()
# print "End " + self.name
if self.sync:
r[0].sync()
self.r = r
# print "Exiting " + self.name
thread1 = myThread("Thread-3", f3, True)
thread2 = myThread("Thread-4", f4, True)
t = time.time()
thread1.start()
thread2.start()
thread1.join()
thread2.join()
t2 = time.time()
print(f"two ctx, 2 fct async, 2 threads {t2 - t:f}")
thread1 = myThread("Thread-5", f5, False)
thread2 = myThread("Thread-6", f6, False)
t = time.time()
thread1.start()
thread2.start()
thread1.join()
thread2.join()
t2 = time.time()
print(f"two ctx, 2 fct with transfer, 2 threads {t2 - t:f}")