Don't see any transfers on NVLINK with NCCL all_sum test
With the following code (uses tensorflow.contrib.nccl.all_sum), I expected to see bytes being transferred over NVLINK.
In reality, I don't.
from tensorflow.contrib.nccl import all_sum
with tf.device('/gpu:0'):
a = tf.get_variable(
"a", initializer=tf.constant(1.0, shape=(args.dim, args.dim)))
with tf.device('/gpu:1'):
b = tf.get_variable(
"b", initializer=tf.constant(2.0, shape=(args.dim, args.dim)))
with tf.device('/gpu:0'):
summed_node = all_sum([a, b])
sess = tf.Session(config=tf.ConfigProto(allow_soft_placement=True,
log_device_placement=True))
init = tf.global_variables_initializer()
sess.run(init)
with tf.device('/gpu:0'):
summed = sess.run(summed_node)
My machine is an AWS instance of p3.8xlarge. My understanding is, this configuration supports NVLINK.
The execution is fine but when I use nvidia-smi nvlink -g 0 -i 0 the link Tx/Rx counts are zero.
tensorflow cudnn nvlink
asked Nov 28 '18 at 20:02
auroauro
496519
add a comment |
With the following code (uses tensorflow.contrib.nccl.all_sum), I expected to see bytes being transferred over NVLINK.
In reality, I don't.
from tensorflow.contrib.nccl import all_sum
with tf.device('/gpu:0'):
a = tf.get_variable(
"a", initializer=tf.constant(1.0, shape=(args.dim, args.dim)))
with tf.device('/gpu:1'):
b = tf.get_variable(
"b", initializer=tf.constant(2.0, shape=(args.dim, args.dim)))
with tf.device('/gpu:0'):
summed_node = all_sum([a, b])
sess = tf.Session(config=tf.ConfigProto(allow_soft_placement=True,
log_device_placement=True))
init = tf.global_variables_initializer()
sess.run(init)
with tf.device('/gpu:0'):
summed = sess.run(summed_node)
My machine is an AWS instance of p3.8xlarge. My understanding is, this configuration supports NVLINK.
The execution is fine but when I use nvidia-smi nvlink -g 0 -i 0 the link Tx/Rx counts are zero.
tensorflow cudnn nvlink
asked Nov 28 '18 at 20:02
auroauro
496519
1
My removal of the CUDA tag wasn't an accident. This isn't a CUDA programming question and should not be tagged as one
– talonmies
Nov 28 '18 at 21:26
removed CUDA tag
– auro
Nov 28 '18 at 21:39
add a comment |
With the following code (uses tensorflow.contrib.nccl.all_sum), I expected to see bytes being transferred over NVLINK.
In reality, I don't.
from tensorflow.contrib.nccl import all_sum
with tf.device('/gpu:0'):
a = tf.get_variable(
"a", initializer=tf.constant(1.0, shape=(args.dim, args.dim)))
with tf.device('/gpu:1'):
b = tf.get_variable(
"b", initializer=tf.constant(2.0, shape=(args.dim, args.dim)))
with tf.device('/gpu:0'):
summed_node = all_sum([a, b])
sess = tf.Session(config=tf.ConfigProto(allow_soft_placement=True,
log_device_placement=True))
init = tf.global_variables_initializer()
sess.run(init)
with tf.device('/gpu:0'):
summed = sess.run(summed_node)
My machine is an AWS instance of p3.8xlarge. My understanding is, this configuration supports NVLINK.
The execution is fine but when I use nvidia-smi nvlink -g 0 -i 0 the link Tx/Rx counts are zero.
tensorflow cudnn nvlink
asked Nov 28 '18 at 20:02
auroauro
496519
With the following code (uses tensorflow.contrib.nccl.all_sum), I expected to see bytes being transferred over NVLINK.
In reality, I don't.
from tensorflow.contrib.nccl import all_sum
with tf.device('/gpu:0'):
a = tf.get_variable(
"a", initializer=tf.constant(1.0, shape=(args.dim, args.dim)))
with tf.device('/gpu:1'):
b = tf.get_variable(
"b", initializer=tf.constant(2.0, shape=(args.dim, args.dim)))
with tf.device('/gpu:0'):
summed_node = all_sum([a, b])
sess = tf.Session(config=tf.ConfigProto(allow_soft_placement=True,
log_device_placement=True))
init = tf.global_variables_initializer()
sess.run(init)
with tf.device('/gpu:0'):
summed = sess.run(summed_node)
My machine is an AWS instance of p3.8xlarge. My understanding is, this configuration supports NVLINK.
The execution is fine but when I use nvidia-smi nvlink -g 0 -i 0 the link Tx/Rx counts are zero.
tensorflow cudnn nvlink
tensorflow cudnn nvlink
asked Nov 28 '18 at 20:02
auroauro
496519
asked Nov 28 '18 at 20:02
auroauro
496519
edited Nov 28 '18 at 21:38
auro
asked Nov 28 '18 at 20:02
auroauro
496519
asked Nov 28 '18 at 20:02
auroauro
496519
asked Nov 28 '18 at 20:02
auroauro
496519
496519
1
My removal of the CUDA tag wasn't an accident. This isn't a CUDA programming question and should not be tagged as one
– talonmies
Nov 28 '18 at 21:26
removed CUDA tag
– auro
Nov 28 '18 at 21:39
add a comment |
1
My removal of the CUDA tag wasn't an accident. This isn't a CUDA programming question and should not be tagged as one
– talonmies
Nov 28 '18 at 21:26
removed CUDA tag
– auro
Nov 28 '18 at 21:39
1
1
My removal of the CUDA tag wasn't an accident. This isn't a CUDA programming question and should not be tagged as one
– talonmies
Nov 28 '18 at 21:26
My removal of the CUDA tag wasn't an accident. This isn't a CUDA programming question and should not be tagged as one
– talonmies
Nov 28 '18 at 21:26
removed CUDA tag
– auro
Nov 28 '18 at 21:39
removed CUDA tag
– auro
Nov 28 '18 at 21:39
add a comment |
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1
My removal of the CUDA tag wasn't an accident. This isn't a CUDA programming question and should not be tagged as one
– talonmies
Nov 28 '18 at 21:26
removed CUDA tag
– auro
Nov 28 '18 at 21:39