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33 lines
1.1 KiB
33 lines
1.1 KiB
import time
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import tensorflow as tf
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gpus = tf.config.list_physical_devices('GPU')
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if gpus:
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try:
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# Currently, memory growth needs to be the same across GPUs
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for gpu in gpus:
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tf.config.experimental.set_memory_growth(gpu, True)
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logical_gpus = tf.config.list_logical_devices('GPU')
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print(len(gpus), "Physical GPUs,", len(logical_gpus), "Logical GPUs")
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except RuntimeError as e:
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# Memory growth must be set before GPUs have been initialized
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print(e)
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for dtype in [tf.float16, tf.float32]:
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for N in [256, 512, 1024, 2048, 4096, 8192]:
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FLOPS = N*N*N*2
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b = tf.random.uniform((N, N), dtype=dtype)
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c = tf.random.uniform((N, N), dtype=dtype)
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b = tf.Variable(b)
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c = tf.Variable(c)
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def tf_prog(b, c):
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st = time.perf_counter()
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a = tf.matmul(b, c)
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tf.debugging.check_numerics(a, "Nan or Inf in result") # Ensures that the calculation is done.
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return time.perf_counter() - st
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tm = min([tf_prog(b, c) for _ in range(20)])
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print(f"{N*N:10d} {tm*1e6:9.2f} us, would be {FLOPS*1e-9/tm:9.2f} GFLOPS {N:4d}x{N:4d}x{N:4d} matmul in {dtype}") |