Skip to content

Commit 6885857

Browse files
AnderBiguriAnderBiguri
committed
Update Install instructions
1 parent 78185b0 commit 6885857

File tree

2 files changed

+58
-23
lines changed

2 files changed

+58
-23
lines changed

‎Frontispiece/MATLAB_installation.md‎

Lines changed: 21 additions & 12 deletions
Original file line numberDiff line numberDiff line change
@@ -11,7 +11,7 @@ Installation Instructions for MATLAB
1111
- [Requirements](#requirements-1)
1212
- [Simple Instructions](#simple-instructions-1)
1313
- [Step by Step Instructions](#step-by-step-instructions1)
14-
14+
- [Advanced](#advanced)
1515
*****
1616

1717
## Windows
@@ -20,24 +20,24 @@ Installation Instructions for MATLAB
2020

2121
1. MATLAB
2222
2. Visual Studio (Community or Profesional)
23-
3. A CUDA capable GPU from NVIDIA with [compute capability greater or equal to 3.0](https://en.wikipedia.org/wiki/CUDA#GPUs_supported)
23+
3. A CUDA capable GPU from NVIDIA with [compute capability greater or equal to 3.5](https://en.wikipedia.org/wiki/CUDA#GPUs_supported)
2424
4. CUDA Toolkit (9.2 or newer)
2525

2626
Tested on
2727

2828
| Software | Version |
2929
| ------------- |:-------------:|
3030
|**Windows**| 7, 8, 10.|
31-
|**MATLAB**| 2014b 2016b 2017a 2018b|
32-
|**CUDA**| 9.2 10|
33-
|**Visual Studio**| 2010 2013 2015|
31+
|**MATLAB**|Any MATLAB >2016b|
32+
|**CUDA**|Any CUDA 9.2>|
33+
|**Visual Studio**| 2010 2013 2015 2019 2022|
3434

3535

3636

3737
### Simple Instructions
3838

39-
1. Install MATLAB, Visual Studio and CUDA
40-
2. Rename either `mex_CUDA_win64_MVS2013.xml` (Visual Studio 2013 or older) or `mex_CUDA_win64_MVS2015.xml`(Visual Studio 2015 or newer) to `mex_CUDA_win64.xml`
39+
1. Install MATLAB, Visual Studio and CUDA (Remember to install C++ when isntalling Visual Studio!)
40+
2. Rename the XML file corresponding to the Visual Studio you have. e.g. `mex_CUDA_win64_MVS2015.xml`(Visual Studio 2015/2017) to `mex_CUDA_win64.xml`
4141
3. Run `Compile.m`
4242

4343
A succesfull installation should be able to execute the script at `TIGRE/MATLAB/Demos/d03_generateData.m` without errors.
@@ -129,9 +129,9 @@ Tested on
129129

130130
| Software | Version |
131131
| ------------- |:-------------:|
132-
| **Ubuntu**| 16.04 17.10|
133-
| **MATLAB**| 2017a 2018b|
134-
| **CUDA**| 9.2 10.0|
132+
| **Ubuntu**| Any ubuntu 16.04>|
133+
| **MATLAB**| Any MATLAB 2016b>|
134+
| **CUDA**| Any Cuda 0.2>|
135135
| **gcc**| 6.4.0 7.2.0|
136136

137137
### Simple Instructions
@@ -141,7 +141,7 @@ Tested on
141141

142142
A succesfull installation should be able to execute the script at `TIGRE/MATLAB/Demos/d03_generateData.m` without errors.
143143

144-
### Step by Step Instructions:<sup>1</sup>
144+
### Step by Step Instructions:
145145

146146
1. Install MATLAB
147147

@@ -181,4 +181,13 @@ If none of this works, please contact the authors at [tigre.toolbox@gmail.com](m
181181
182182
****
183183
184-
<sup>1</sup> Testing by the TIGRE team in Linux is limited, thus the step by step instructions are less detailed than expected. Please do [contact us](mailto:ander.biguri@gmail.com) if you are having trouble or would like to contribute to the instructions.
184+
## Advanced
185+
186+
If you are doing reconstruction of large datasets, and you want to use swap memory, you will need to deactivate TIGREs pinned memory feature at compile time. This will allow you to use swap memory, but it will make the operators in TIGRE slower, as pinned memory is used for simultaneous memory and compute.
187+
188+
189+
You can do this by calling the `Compile.m` file from the MATLAB command line as `Compile --no_pinned_memory`.
190+
191+
192+
193+

‎Frontispiece/python_installation.md‎

Lines changed: 37 additions & 11 deletions
Original file line numberDiff line numberDiff line change
@@ -1,22 +1,35 @@
11
Installation Instructions for Python
22
======
33

4+
## Table of contents
5+
6+
- [Windows](#windows)
7+
- [Requirements](#requirements)
8+
- [Simple Instructions](#simple-instructions)
9+
- [Step by Step Instructions](#step-by-step-instructions)
10+
- [Linux](#linux)
11+
- [Requirements](#requirements-1)
12+
- [Simple Instructions](#simple-instructions-1)
13+
- [Step by Step Instructions](#step-by-step-instructions1)
14+
- [Optional Code Style Enforcement](#Optional-Code-Style-Enforcement)
15+
- [Advanced](#advanced)
16+
*****
417
## Windows
518

619
### Requirements:
720

8-
1. Python 3
21+
1. Python 3.7-3.10
922
2. MVS
10-
3. A CUDA capable GPU from NVIDIA with [compute capability greater or equal to 3.0](https://en.wikipedia.org/wiki/CUDA#GPUs_supported)
23+
3. A CUDA capable GPU from NVIDIA with [compute capability greater or equal to 3.5](https://en.wikipedia.org/wiki/CUDA#GPUs_supported)
1124
4. CUDA Toolkit
1225

1326
Tested on
1427

1528
| Software | Version |
1629
| ------------- |:-------------:|
1730
|**Windows**| 10 |
18-
|**Python**| 3.7 3.8 |
19-
|**CUDA**| 10.1 |
31+
|**Python**| 3.7 3.8 3.9 3.10|
32+
|**CUDA**| 9.2>|
2033
|**MSVC**| 19.24 |
2134

2235
### Simple Instructions
@@ -63,19 +76,19 @@ A succesfull installation should be able to execute the script at `TIGRE/Python/
6376

6477
### Requirements:
6578

66-
1. Python 2/Python 3
79+
1. Python 3
6780
2. gcc
68-
3. A CUDA capable GPU from NVIDIA with [compute capability greater or equal to 3.0](https://en.wikipedia.org/wiki/CUDA#GPUs_supported)
81+
3. A CUDA capable GPU from NVIDIA with [compute capability greater or equal to 3.5](https://en.wikipedia.org/wiki/CUDA#GPUs_supported)
6982
4. CUDA Toolkit
7083

7184

7285
Tested on
7386

7487
| Software | Version |
7588
| ------------- |:-------------:|
76-
|**Ubuntu**| 16.04 17.10|
77-
|**Python**| 2.7 3.7 |
78-
|**CUDA**| 8.0 9.2 10.1 10.2|
89+
|**Ubuntu**| 16.04>|
90+
|**Python**| 3.7-3.10|
91+
|**CUDA**| 9.2>|
7992
|**gcc**| 7.6.0|
8093

8194
### Simple Instructions
@@ -90,14 +103,17 @@ A succesfull installation should be able to execute the script at `TIGRE/Python/
90103

91104
For Ubuntu
92105

93-
1. Install python and pip (you can use 2 or 3, example show for 2)
106+
1. Install python and pip
107+
108+
Recommended to do it via [Anaconda3](https://docs.anaconda.com/free/anaconda/install/linux/)
94109

95110
```
96111
sudo apt update
97112
sudo apt upgrade
98-
sudo apt install python2.7 python-pip
113+
sudo apt install python3.10 python-pip
99114
```
100115

116+
101117
2. Install CUDA
102118

103119
Installing CUDA in linux (specially one with a GUI) can be a challenge. Please follow [NVIDIAs instructions](https://developer.download.nvidia.com/compute/cuda/10.0/Prod/docs/sidebar/CUDA_Installation_Guide_Linux.pdf) carefully.\
@@ -185,3 +201,13 @@ check blanket noqa.......................................................Passed
185201
```
186202

187203
**NOTE:** pre-commit may also be manually invoked against *all* files (staged and unstaged) using the `pre-commit run --all-files`. However, some changes made to Python's TIGRE codebase by `black` have been manually reverted for readability reasons and should not be committed in their blackened state.
204+
205+
## Advanced
206+
207+
If you are doing reconstruction of large datasets, and you want to use swap memory, you will need to deactivate TIGREs pinned memory feature at compile time. This will allow you to use swap memory, but it will make the operators in TIGRE slower, as pinned memory is used for simultaneous memory and compute.
208+
209+
You can do this by calling the `stup.py` with the flag `--no_pinned_memory`.
210+
211+
212+
213+

0 commit comments

Comments
 (0)