On Wednesday, May 11, 2016 at 6:10:52 PM UTC+1, Sihuang Hu wrote:
>
> I think I downloaded the binaries. Thanks for your suggestions. I will try
> it.
>
well, you might try Sage 7.1 binary, perhaps it would work better...
(or build from source, on such a machine it won't take much time,
I think I downloaded the binaries. Thanks for your suggestions. I will try
it.
在 2016年5月11日星期三 UTC+3下午6:14:37，Dima Pasechnik写道：
>
> Have you built Sage from source? If not, it could happen, in principle,
> that lapack/atlas/blas shipped
> do not quite work on your system...
>
> If you built it
Have you built Sage from source? If not, it could happen, in principle,
that lapack/atlas/blas shipped
do not quite work on your system...
If you built it from source, did you do anything special to build Atlas in
particular?
You can also try building csdp completely separately from Sage,
Yes, it still works on many other graphs.
---
(sage-sh) shhu@shhu-ee-tau:~$ ldd `which theta`
linux-vdso.so.1 => (0x7ffea69d6000)
libsdp.so.0 =>
It does work on some graphs, still, right?
It's a high-end relatively new CPU, perhaps Atlas and/or gcc has a problem
with it?
Can you post the output of 'ldd theta', i.e.
(sage-sh) dimpase@clpc171:sage$ ldd `which theta`
linux-vdso.so.1 (0x7ffd2c34f000)
libsdp.so.0 =>
My Cpu information is attached...
在 2016年5月11日星期三 UTC+3下午2:58:43，Sihuang Hu写道：
>
> I just did what you suggested, and it didn't work. I got those messages:
>
> (sage-sh) shhu@shhu-ee-tau:~$ theta 2k2
> Segmentation fault (core dumped)
>
> My Cpu information is attached.
> Ubuntu 14.04LTS
>
I just did what you suggested, and it didn't work. I got those messages:
(sage-sh) shhu@shhu-ee-tau:~$ theta 2k2
Segmentation fault (core dumped)
My Cpu information is attached.
Ubuntu 14.04LTS
SageMath Version 7.0, Release Date: 2016-01-19
在 2016年5月10日星期二 UTC+3下午11:55:55，Dima Pasechnik写道：
>
He Andrew,
I used @parallel in sage to parallelize some tensorial calculus (for
example : src/sage/tensor/modules/comp.py)
It is not very complicate to use it but sometimes you need to reorganize
your computation.
The parallelism depends strictly on your code so the part of code you
posted is
He Andrew,
I used @parallel in sage to parallelize some tensorial calculus (for
example : src/sage/tensor/modules/comp.py)
It is not very complicate to use it but sometimes you need to reorganize
your computation.
The parallelism depends strictly on your code so the part of code you
posted is
Thanks Vincent for both your answers. I am planning on using just one
machine with up to 24 cores. (If I am not able to get far enough this way
then I will think about using the cluster. Using 24 cores will already be a
big step up compared with what I am currently doing.)
If the processes can
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