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             ____) | | | | | | | |_) | |  __/ |  | | |__| | |____ 
            |_____/|_|_| |_| |_| .__/|_|\___|_|  |_|\____/ \_____|
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                                   Version 4

==============================================================================
Contact Information
==============================================================================

Organizations:     Computational Reactor Physics Group
                   Massachusetts Institute of Technology

                   Center for Exascale Simulation of Advanced Reactors (CESAR)
                   Argonne National Laboratory

Development Leads: John Tramm     <[email protected]>
                   Geoffrey Gunow <[email protected]>
                   Tim He         <[email protected]>
                   Ron Rahaman    <[email protected]>
                   Amanda Lund    <[email protected]>
    
===============================================================================
What is SimpleMOC-kernel?
===============================================================================

SimpleMOC-kernel represents the core computational of a larger application
(SimpleMOC). This app was written in order to abstract away much of the
complexity of the full application in order to facilitate easier porting of
the code and enable more transparent analysis techniques on high performance
architectures.

The scope of this kernel is essentially the inner-loop of SimpleMOC, i.e., the
attentuation of neutron fluxes across an individual geometrical segment.
This kernel composes approximately 92% of the walltime of the full application,
and is therefore useful for analyzing optimization methods and performance
implications for exascale supercomputer architectures.

More information can be found in the following publication:

http://dx.doi.org/10.1016/j.cpc.2016.01.007

==============================================================================
Architectural Support
==============================================================================

SimpleMOC-kernel supports the following architectures:

- Multi-threaded CPU
- Xeon Phi
- NVIDIA Tesla GPU

Both the CPU and Phi codes are available in the "cpu" folder of the
repository. To enable Phi support, simply set the "MIC" flag in the
makefile to yes.

The CUDA version of the code is available in the "cuda" folder of the
repository. 

==============================================================================
Quick Start Guide
==============================================================================

Download----------------------------------------------------------------------

	For the most up-to-date version of SimpleMOC-kernel, we recommend that you
	download from our git repository. This can be accomplished via
	cloning the repository from the command line, or by downloading a zip
	from our github page.

	Git Repository Clone:
		
		Use the following command to clone SimpleMOC-kernel to your machine:

		>$ git clone https://github.com/ANL-CESAR/SimpleMOC-kernel.git

		Once cloned, you can update the code to the newest version
		using the following command (when in the SimpleMOC-kernel directory):

		>$ git pull

Compilation-------------------------------------------------------------------

	To compile SimpleMOC-kernel with default (serial mode) settings,
	use the following command:

	>$ make

	To disable shared memory (OpenMP) paralleism, set the OpenMP flag to
	"no" in the makefile before building.  See below for more details
	regarding advanced compilation options.

Running SimpleMOC-kernel-------------------------------------------------------

	To run SimpleMOC-kernel with default settings, use the following command:

	>$ ./SimpleMOC-kernel

	For non-default settings, SimpleMOC-kernel supports the following
	command line options:

	< CPU Version >

	Usage: ./SimpleMOC-kernel <options>
	Options include:
	  -t <threads>        Number of OpenMP threads to run
	  -s <segments>       Number of segments to process
	  -e <energy groups>  Number of energy groups
	  -p <PAPI event>     PAPI event name to count (1 only)

	< GPU Version >

	Usage: ./SimpleMOC-kernel <options>
	Options include:
	  -t <threads>          Number of OpenMP threads to run
	  -s <segments>         Number of segments to process
	  -e <energy groups>    Number of energy groups
	  -p <segs per thread>  Number of segments per CUDA Block
	

	If not options are specified, then a default set of parameters will
	automatically be run. These parameters reflect the approximate per node
	work load for a full core reactor simulation (the the number of geometry
	segments has been signficantly reduced to reduce runtime while preserving
	the computational profile).

==============================================================================
Advanced Compilation, Debugging, Optimization, and Profiling
==============================================================================

There are a number of switches that can be set at the top of the makefile
to enable OpenMP parallelism, along with more advanced compilation
features.

Here is a sample of the control panel at the top of the makefile:

< CPU Version >

COMPILER    = intel
OPENMP      = yes
OPTIMIZE    = yes
DEBUG       = no
PROFILE     = no
PAPI        = no
MIC         = no

Explanation of Flags:

COMPILER <gnu, intel> - This selects your compiler.

OpenMP - Enables OpenMP support in the code. By default, the code will
         run using the maximum number of threads on the system, unless
         otherwise specified with the "-t" command line argument.

OPTIMIZE - Adds compiler optimization flag "-O3" and other optimizations

DEBUG - Adds the compiler flag "-g".

PROFILE - Adds the compiler flag "-pg".

PAPI - Enables PAPI support in the code. You may need to alter the makefile
       or your environment to ensure proper linking with the PAPI library.
       See PAPI section below for more details.

MIC -  Enables Intel Xeon Phi (MIC) native mode compilation.

< GPU Version >

COMPILER    = nvcc
OPTIMIZE    = yes
DEBUG       = no
PROFILE     = no

Explanation of Flags:

COMPILER <nvcc> - This selects your compiler (Nvidia is only one supported).

OPTIMIZE - Adds compiler optimization flag "-O3" and other optimizations.

DEBUG - Adds the compiler flag "-g".

PROFILE - Adds the compiler flag "-pg".

===============================================================================
SimpleMOC-kernel Strawman Reactor Defintion
===============================================================================

For the purposes of simplicity this mini-app uses a conservative "strawman"
reactor model to represent a good target problem for full core reactor
simualations to be run on exascale class supercomputers. Arbitrary
user-defined geometries are not supported.

===============================================================================
Citing SimpleMOC-kernel
===============================================================================

Papers citing SimpleMOC-kernel should in general refer to:

John R. Tramm, Geoffrey Gunow, Tim He, Kord S. Smith, Benoit Forget, 
Andrew R. Siegel, (2016) "A task-based parallelism and vectorized approach
to 3D Method of Characteristics (MOC) reactor simulation for high performance
computing architectures", Computer Physics Communications, Volume 202, 
Pages 141–150, (https://doi.org/10.1016/j.cpc.2016.01.007).

The bibtext entry for this paper is given below:

@article{Tramm2016,
title = "A task-based parallelism and vectorized approach to 3D Method of Characteristics (MOC) reactor simulation for high performance computing architectures",
journal = "Computer Physics Communications",
volume = "202",
pages = "141 - 150",
year = "2016",
issn = "0010-4655",
doi = "https://doi.org/10.1016/j.cpc.2016.01.007",
url = "http://www.sciencedirect.com/science/article/pii/S0010465516000266",
author = "John R. Tramm and Geoffrey Gunow and Tim He and Kord S. Smith and Benoit Forget and Andrew R. Siegel",
}

===============================================================================