This is the GPU based ANUGA 
===========================



Documentation
-------------

Documentation is under doc directory, and the html version generated by **Sphinx** under the directory *doc/sphinx/build/html/*





Install Guide
-------------

1. Original [ANUGA](anuga.anu.edu.au) is required
- For CUDA version, [PyCUDA](documen.tician.de/pycuda) is required
- For OpenHMPP version, current implementation is based on the [CAPS OpenHMPP Compiler](www.caps-entreprise.com)
	* When compiling the code with **Makefile**, the NVIDIA device architecture and compute capability need to be specified
		* For example, GTX480 with 2.0 compute capability </br>
		```HMPP_FLAGS13 = -e --nvcc-options -Xptxas=-v,-arch=sm_20 -c --force```
		* For GTX680 with 3.0 compute capability </br>
		```HMPP_FLAGS13 = -e --nvcc-options -Xptxas=-v,-arch=sm_30 -c --force```
	* Also the path for **python**, **numpy**, and **ANUGA/utilities** packages need to be specified
	* Defining the macro **USING_MIRROR_DATA** in **hmpp_fun.h** </br>
	```#define USING_MIRROR_DATA```
	</br>will enable the advanced version, which uses OpenHMPP Mirrored Data technology so that data transmission costs can be effectively cut down, otherwise basic version is enabled.





Environment Vars
----------------

Please add following vars to you **.bashrc** or **.bash_profile** file

```
export ANUGA_CUDA=/where_the_anuga-cuda/src

export $PYTHONPATH=$PYTHONPATH:$ANUGA_CUDA
```



Basic Code Structure
--------------------

![Code Structure](docs/codeStructure.pdf "anuga-cuda code structure")

* **README** (What you are reading)
* **docs/** Documentation directory
	* **codeStructure.pdf** The diagram above 
	* **Evolve workflow.pdf** The overall workflow of the evolve procedure. This includes all the function dependency and function interfaces, which is helpful to understand the evolve procedure of ANUGA
	* **device_spe/** Some device specifications of our working station
	* **profiling/** Profiling results
		* **CUDA/** All the profiling results on CUDA implementation
	* **sphinx/** The [Sphinx](http://sphinx-doc.org/) generated documentation
		* **source/** The source files for Sphinx based documents
		* **build/** The generated documents
			* **html/** HTML version documentation
* **src/** Source code directory
	* **anuga_cuda/** The CUDA implementation
		* **config.py** Detail configuration for the CUDA implementation, including the path for all the kernel functions, optimal CUDA thread block configuration, etc. 
		* **gpu_domain_advanced.py** Python Class for CUDA implementation in advanced version
		* **gpu_domain_basic.py** Python Class for CUDA implementation in basic version
	* **anuga_HMPP/** The OpenHMPP implementation
		* **Makefile** The Makefile 
		* **hmpp_dimain.py** Python Class for OpenHMPP implementation
		* **hmpp_python_glue.c** The Python/C API to set up communication between Python ANUGA and OpenHMPP.
		* **sw_domain.h** The C Struct type **domain** used in C implementation to access mesh information generated in Python ANUGA
		* **sw_domain_fun.h** Connect C Struct type **domain** to all mesh information
		* **hmpp_fun.h** All function declarations. 
		* **evolve.c** The evolve procedure
	* **scripts/** Some useful bash script
	* **utilities/** Utilities for sorting mesh information, checking results, etc.
* **test/** Testing cases
	* **CUDA/** Testing cases for CUDA implementation
		* **merimbula/** Merimbula testing case directory
			* **merimbula.py** Merimbula testing case
	* **OpenHMPP/** Testing cases for OpenHMPP implementation
		* **merimbula.py** Merimbula testing case	


Examples
--------

Running Merimbula model with CUDA implementation.

```$ python merimbula.py -gpu```

With pair-testing.

```$ python merimbula.py -gpu -test```

With rearranged mesh information.

```$ python merimbula.py -gpu -rg```



Author
------

Mail to [Zhe Weng (John)](wengcsyz@gmail.com)