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tkphd / meta.yml
Last active January 5, 2017 00:42
MMSP spinodal decomposition benchmark, periodic domain
---
metadata:
# Describe the runtime environment
summary: MPI parallel workstation benchmark with MMSP, periodic domain
author: Trevor Keller
email: trevor.keller@nist.gov
date: Wed, 04 Jan 2017 19:30:31 -0500
hardware:
# Required hardware details
architecture: x86_64
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tkphd / Dockerfile
Last active May 13, 2016 21:31
Docker build for MMSP spinodal decomposition
# Docker file to install MMSP in a Ubuntu container
# with a Jupyter notebook exposed on port 8888
#
# Cloned from https://gist.github.com/wd15/d233c706bb493c91ecd5
#
FROM ubuntu:15.10
MAINTAINER Trevor Keller "https://github.com/tkphd"
## Install only required packages for making a user as the
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tkphd / polar_grid.py
Created September 17, 2015 22:17
Script to test polar grid memory access time
from fipy import *
from scipy import interpolate
import numpy as np
##Create mesh in Polar Coordinate system (LnR,Cta)
nLnR = 100
nCta = 50
dLnR = 0.02
dCta = 2*np.pi/nCta
PL = nLnR*dLnR
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tkphd / cartesian_grid.py
Created September 17, 2015 22:15
Script to test uniform grid memory access time
from fipy import *
from scipy import interpolate
import numpy as np
##Create mesh in the Cartesian Coordinate system (X,Y)
nx = 100
ny = nx
dx = 1.0
dy = dx
CL = nx*dx
from fipy import *
from scipy import interpolate
import numpy as np
mesh = Grid1D(dx=3, nx=10)
datx = mesh.cellCenters[0]
daty = np.sin(4*np.pi*datx/10)
valumesh = Grid1D(dx=1, nx=10)
# Based on https://gist.github.com/wd15/871797
import time
import fipy as fp
import numpy as np
from mpi4py import MPI
np.random.seed(1)
L = 1.
N = 30