Commit 085f85f8 authored by Pavel Gajdušek's avatar Pavel Gajdušek

mdlint

parent 2843c882
......@@ -29,8 +29,8 @@ Mellanox
### Formulas are made with:
* https://facelessuser.github.io/pymdown-extensions/extensions/arithmatex/
* https://www.mathjax.org/
* [https://facelessuser.github.io/pymdown-extensions/extensions/arithmatex/](https://facelessuser.github.io/pymdown-extensions/extensions/arithmatex/)
* [https://www.mathjax.org/](https://www.mathjax.org/)
You can add formula to page like this:
......
......@@ -31,19 +31,19 @@ Compile the application which you want to debug as usual. It is advisable to add
For example, lets look at this C code, which has two problems :
```cpp
#include <stdlib.h>
void f(void)
{
int* x = malloc(10 * sizeof(int));
x[10] = 0; // problem 1: heap block overrun
} // problem 2: memory leak -- x not freed
int main(void)
{
f();
return 0;
}
#include <stdlib.h>
void f(void)
{
int* x = malloc(10 * sizeof(int));
x[10] = 0; // problem 1: heap block overrun
} // problem 2: memory leak -- x not freed
int main(void)
{
f();
return 0;
}
```
Now, compile it with Intel compiler :
......@@ -161,19 +161,19 @@ so it is better to use the MPI-enabled valgrind from module. The MPI version req
Lets look at this MPI example :
```cpp
#include <stdlib.h>
#include <mpi.h>
#include <stdlib.h>
#include <mpi.h>
int main(int argc, char *argv[])
{
int *data = malloc(sizeof(int)*99);
int main(int argc, char *argv[])
{
int *data = malloc(sizeof(int)*99);
MPI_Init(&argc, &argv);
MPI_Bcast(data, 100, MPI_INT, 0, MPI_COMM_WORLD);
MPI_Finalize();
MPI_Init(&argc, &argv);
MPI_Bcast(data, 100, MPI_INT, 0, MPI_COMM_WORLD);
MPI_Finalize();
return 0;
}
return 0;
}
```
There are two errors - use of uninitialized memory and invalid length of the buffer. Lets debug it with valgrind :
......
......@@ -6,9 +6,9 @@ TensorFlow is an open-source software library for machine intelligence.
Anselm provides three different TensorFlow modules:
* Tensorflow/1.1.0
* Tensorflow/1.1.0-CUDA-7.5.18-Python-3.6.1
* Tensorflow/1.1.0-CUDA-8.0.44-Python-3.6.1
* Tensorflow/1.1.0
* Tensorflow/1.1.0-CUDA-7.5.18-Python-3.6.1
* Tensorflow/1.1.0-CUDA-8.0.44-Python-3.6.1
### Tensorflow/1.1.0 (CPU only)
......@@ -20,8 +20,8 @@ $ ml Tensorflow/1.1.0
This module was built with:
* GCC/4.9.3
* Python/3.6.1
* GCC/4.9.3
* Python/3.6.1
### Tensorflow/1.1.0-CUDA-7.5.18-Python-3.6.1 (GPU enabled)
......@@ -33,10 +33,10 @@ $ ml Tensorflow/1.1.0-CUDA-7.5.18-Python-3.6.1
This module was built with:
* GCC/4.9.3
* Python/3.6.1
* CUDA/7.5.18
* cuDNN/5.1-CUDA-7.5.18
* GCC/4.9.3
* Python/3.6.1
* CUDA/7.5.18
* cuDNN/5.1-CUDA-7.5.18
### Tensorflow/1.1.0-CUDA-8.0.44-Python-3.6.1 (GPU enabled)
......@@ -48,10 +48,10 @@ $ ml Tensorflow/1.1.0-CUDA-8.0.44-Python-3.6.1
This module was built with:
* GCC/4.9.3
* Python/3.6.1
* CUDA/8.0.44
* cuDNN/5.1-CUDA-8.0.44
* GCC/4.9.3
* Python/3.6.1
* CUDA/8.0.44
* cuDNN/5.1-CUDA-8.0.44
## TensorFlow application example
......
......@@ -30,19 +30,19 @@ Compile the application which you want to debug as usual. It is advisable to add
For example, lets look at this C code, which has two problems:
```cpp
#include <stdlib.h>
void f(void)
{
int* x = malloc(10 * sizeof(int));
x[10] = 0; // problem 1: heap block overrun
} // problem 2: memory leak -- x not freed
int main(void)
{
f();
return 0;
}
#include <stdlib.h>
void f(void)
{
int* x = malloc(10 * sizeof(int));
x[10] = 0; // problem 1: heap block overrun
} // problem 2: memory leak -- x not freed
int main(void)
{
f();
return 0;
}
```
Now, compile it with Intel compiler:
......@@ -164,19 +164,19 @@ which must be included in the LD_PRELOAD environment variable.
Lets look at this MPI example:
```cpp
#include <stdlib.h>
#include <mpi.h>
#include <stdlib.h>
#include <mpi.h>
int main(int argc, char *argv[])
{
int *data = malloc(sizeof(int)*99);
int main(int argc, char *argv[])
{
int *data = malloc(sizeof(int)*99);
MPI_Init(&argc, &argv);
MPI_Bcast(data, 100, MPI_INT, 0, MPI_COMM_WORLD);
MPI_Finalize();
MPI_Init(&argc, &argv);
MPI_Bcast(data, 100, MPI_INT, 0, MPI_COMM_WORLD);
MPI_Finalize();
return 0;
}
return 0;
}
```
There are two errors - use of uninitialized memory and invalid length of the buffer. Lets debug it with valgrind :
......
......@@ -6,9 +6,9 @@ TensorFlow is an open-source software library for machine intelligence.
Salomon provides three different TensorFlow modules:
* Tensorflow/1.1.0
* Tensorflow/1.2.0-GCC-7.1.0-2.28
* Tensorflow/1.2.0-intel-2017.05-mkl
* Tensorflow/1.1.0
* Tensorflow/1.2.0-GCC-7.1.0-2.28
* Tensorflow/1.2.0-intel-2017.05-mkl
### Tensorflow/1.1.0 (not recommended)
......@@ -21,8 +21,8 @@ $ ml Tensorflow/1.1.0
This module was built with:
* GCC/4.9.3
* Python/3.6.1
* GCC/4.9.3
* Python/3.6.1
### Tensorflow/1.2.0-GCC-7.1.0-2.28 (default, recommended)
......@@ -35,9 +35,9 @@ $ ml Tensorflow/1.2.0-GCC-7.1.0-2.28
This module was built with:
* GCC/7.1.0-2.28
* Python/3.6.1
* protobuf/3.2.0-GCC-7.1.0-2.28-Python-3.6.1
* GCC/7.1.0-2.28
* Python/3.6.1
* protobuf/3.2.0-GCC-7.1.0-2.28-Python-3.6.1
### Tensorflow/1.2.0-intel-2017.05-mkl
......@@ -50,9 +50,9 @@ $ ml Tensorflow/1.2.0-intel-2017.05-mkl
This module was built with:
* icc/2017.4.196-GCC-7.1.0-2.28
* Python/3.6.1
* protobuf/3.2.0-GCC-7.1.0-2.28-Python-3.6.1
* icc/2017.4.196-GCC-7.1.0-2.28
* Python/3.6.1
* protobuf/3.2.0-GCC-7.1.0-2.28-Python-3.6.1
## TensorFlow application example
......
......@@ -36,6 +36,6 @@ $("#searchInput").keyup(function () {
"color": "black"
});
}).css({
"color": "#C0C0C0"
"color": "#C0C0C0"
});
</script>
......@@ -12,8 +12,8 @@ All builds and installations are performed at user level, so you don't need the
EasyBuild relies on two main concepts
* Toolchains
* EasyConfig file (our easyconfigs is [here](https://code.it4i.cz/sccs/easyconfigs-it4i))
* Toolchains
* EasyConfig file (our easyconfigs is [here](https://code.it4i.cz/sccs/easyconfigs-it4i))
Detailed documentations is available [here](http://easybuild.readthedocs.io).
......@@ -21,8 +21,8 @@ Detailed documentations is available [here](http://easybuild.readthedocs.io).
A toolchain corresponds to a compiler and a set of libraries which are commonly used to build a software. The two main toolchains frequently used on the IT4Innovations clusters are the **foss** and **intel**.
* **foss** is based on the GCC compiler and on open-source libraries (OpenMPI, OpenBLAS, etc.).
* **intel** is based on the Intel compiler and on Intel libraries (Intel MPI, Intel Math Kernel Library, etc.).
* **foss** is based on the GCC compiler and on open-source libraries (OpenMPI, OpenBLAS, etc.).
* **intel** is based on the Intel compiler and on Intel libraries (Intel MPI, Intel Math Kernel Library, etc.).
Additional details are available on [here](https://github.com/hpcugent/easybuild/wiki/Compiler-toolchains).
......
# Singularity Container
[Singularity](http://singularity.lbl.gov/) enables users to have full control of their environment. A non-privileged user can "swap out" the operating system on the host for one they control. So if the host system is running RHEL6 but your application runs in Ubuntu/RHEL7, you can create an Ubuntu/RHEL7 image, install your applications into that image, copy the image to another host, and run your application on that host in it’s native Ubuntu/RHEL7 environment.
Singularity also allows you to leverage the resources of whatever host you are on. This includes HPC interconnects, resource managers, file systems, GPUs and/or accelerators, etc. Singularity does this by enabling several key facets:
......
......@@ -241,7 +241,7 @@ $ spack edit git
!!! note
To change source link (ftp:// to http://) use `spack create URL -f` to regenerates rules.
**Example**
#### **Example**
```console
$ spack install git
......@@ -290,7 +290,7 @@ autoconf@2.69 cmake@3.7.1 expat@2.2.0 git@2.11.0 libsigsegv@2.10 m4
bzip2@1.0.6 curl@7.50.3 gettext@0.19.8.1 libiconv@1.14 libxml2@2.9.4 ncurses@6.0 pcre@8.41 pkg-config@0.29.1 xz@5.2.2
```
**Spack colorizes output**
Spack colorizes output.
```console
$ spack find | less -R
......@@ -317,7 +317,7 @@ $ spack load git
source ~/.local/easybuild/software/Spack/0.10.0/share/spack/setup-env.csh
```
**First usage**
### First usage
```console
$ . ~/.local/easybuild/software/Spack/0.10.0/share/spack/setup-env.sh
......
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