Illegal instruction (core dumped) -Tensorflow GPU
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I have installed Tensorflow-GPU version 1.9.0 and simple tensorflow import statement gives exception "Illegal instruction (core dumped)". If I downgrade tensorflow version to 1.5.0, it works fine. How to fix this issue for higher version as I need to work with it?
Thanks
tensorflow
asked Nov 20 at 11:00
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I have installed Tensorflow-GPU version 1.9.0 and simple tensorflow import statement gives exception "Illegal instruction (core dumped)". If I downgrade tensorflow version to 1.5.0, it works fine. How to fix this issue for higher version as I need to work with it?
Thanks
tensorflow
asked Nov 20 at 11:00
Pervaiz Niazi
297
add a comment |
up vote
1
down vote
favorite
up vote
1
down vote
favorite
I have installed Tensorflow-GPU version 1.9.0 and simple tensorflow import statement gives exception "Illegal instruction (core dumped)". If I downgrade tensorflow version to 1.5.0, it works fine. How to fix this issue for higher version as I need to work with it?
Thanks
tensorflow
asked Nov 20 at 11:00
Pervaiz Niazi
297
I have installed Tensorflow-GPU version 1.9.0 and simple tensorflow import statement gives exception "Illegal instruction (core dumped)". If I downgrade tensorflow version to 1.5.0, it works fine. How to fix this issue for higher version as I need to work with it?
Thanks
tensorflow
tensorflow
asked Nov 20 at 11:00
Pervaiz Niazi
297
asked Nov 20 at 11:00
Pervaiz Niazi
297
asked Nov 20 at 11:00
Pervaiz Niazi
297
asked Nov 20 at 11:00
Pervaiz Niazi
297
asked Nov 20 at 11:00
Pervaiz Niazi
297
297
add a comment |
add a comment |
1 Answer
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Starting with v1.5.1 on Linux and v1.6.0 on other platforms, the official TensorFlow distribution is compiled with AVX instructions, meaning that older CPUs will not work with it (you can look up model compatibility, but it does not have to be an ancient CPU, it happened to me on an old Core i7).
If you want to use official releases, the only solution is to switch to a different hardware or to stick to the older version. There have been requests for support for older CPUs (and some people have uploaded their own build for a particular configuration, if it works for you and you trust it), but the general answer is that if you need specific support for your platform you can always build it yourself, disabling AVX optimizations (see the installation guide).
answered Nov 20 at 11:18
jdehesa
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1 Answer
1
active
oldest
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1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
1
down vote
accepted
Starting with v1.5.1 on Linux and v1.6.0 on other platforms, the official TensorFlow distribution is compiled with AVX instructions, meaning that older CPUs will not work with it (you can look up model compatibility, but it does not have to be an ancient CPU, it happened to me on an old Core i7).
If you want to use official releases, the only solution is to switch to a different hardware or to stick to the older version. There have been requests for support for older CPUs (and some people have uploaded their own build for a particular configuration, if it works for you and you trust it), but the general answer is that if you need specific support for your platform you can always build it yourself, disabling AVX optimizations (see the installation guide).
answered Nov 20 at 11:18
jdehesa
22k43150
add a comment |
up vote
1
down vote
accepted
Starting with v1.5.1 on Linux and v1.6.0 on other platforms, the official TensorFlow distribution is compiled with AVX instructions, meaning that older CPUs will not work with it (you can look up model compatibility, but it does not have to be an ancient CPU, it happened to me on an old Core i7).
If you want to use official releases, the only solution is to switch to a different hardware or to stick to the older version. There have been requests for support for older CPUs (and some people have uploaded their own build for a particular configuration, if it works for you and you trust it), but the general answer is that if you need specific support for your platform you can always build it yourself, disabling AVX optimizations (see the installation guide).
answered Nov 20 at 11:18
jdehesa
22k43150
add a comment |
up vote
1
down vote
accepted
up vote
1
down vote
accepted
Starting with v1.5.1 on Linux and v1.6.0 on other platforms, the official TensorFlow distribution is compiled with AVX instructions, meaning that older CPUs will not work with it (you can look up model compatibility, but it does not have to be an ancient CPU, it happened to me on an old Core i7).
If you want to use official releases, the only solution is to switch to a different hardware or to stick to the older version. There have been requests for support for older CPUs (and some people have uploaded their own build for a particular configuration, if it works for you and you trust it), but the general answer is that if you need specific support for your platform you can always build it yourself, disabling AVX optimizations (see the installation guide).
answered Nov 20 at 11:18
jdehesa
22k43150
Starting with v1.5.1 on Linux and v1.6.0 on other platforms, the official TensorFlow distribution is compiled with AVX instructions, meaning that older CPUs will not work with it (you can look up model compatibility, but it does not have to be an ancient CPU, it happened to me on an old Core i7).
If you want to use official releases, the only solution is to switch to a different hardware or to stick to the older version. There have been requests for support for older CPUs (and some people have uploaded their own build for a particular configuration, if it works for you and you trust it), but the general answer is that if you need specific support for your platform you can always build it yourself, disabling AVX optimizations (see the installation guide).
answered Nov 20 at 11:18
jdehesa
22k43150
answered Nov 20 at 11:18
jdehesa
22k43150
answered Nov 20 at 11:18
jdehesa
22k43150
answered Nov 20 at 11:18
jdehesa
22k43150
22k43150
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