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Ghost Cells

8,088 bytes added, 04:00, 17 February 2019
Tony
==== Tony ====
Subject: Jacobi's method for Poisson's equation
===== Source Code =====
{| class="wikitable mw-collapsible mw-collapsed"
! poissan.h
|-
|
<source>
#ifndef POISSON_H
#define POISSON_H
#include <fstream>
 
namespace DPS{
class Poisson {
size_t nRowsTotal;
size_t nColumns;
float* data;
int bufferSide;
 
void update (size_t startRow, size_t endRow, const float wx, const float wy);
void bufferSwitch(){ bufferSide = 1 - bufferSide; };
 
public:
Poisson(std::ifstream& ifs);
Poisson(const size_t r, const size_t c, float* d);
~Poisson(){ delete[] data; };
float* operator()(const size_t iteration, const float wx, const float wy);
float* operator()(const size_t iteration){
return operator()(iteration,0.1,0.1);
}
void show(std::ostream& ofs) const;
};
}
#endif
 
</source>
|}
{| class="wikitable mw-collapsible mw-collapsed"
! poissan.cpp
|-
|
<source>
#include <cstring>
#include <cstdlib>
#include <iomanip>
#include <iostream>
#include <string>
#include "poisson.h"
 
namespace DPS{
Poisson::Poisson(std::ifstream& ifs){
std::string line;
bufferSide = 0;
 
/* find number of columns */
std::getline(ifs,line);
for (size_t i = 0 ; i < line.size() ; i++){
if(line[i]==' ') nColumns++;
}
nColumns++;
 
/* find number of rows */
nRowsTotal++; /* already fetched one */
while(std::getline(ifs,line))
nRowsTotal++;
ifs.clear();
 
try{
data = new float[nColumns * nRowsTotal * 2];
}
catch (...){
throw std::runtime_error("Failed to Allocate Memory");
}
 
/* readin data */
ifs.seekg(0,ifs.beg);
std::cout << ifs.tellg() << std::endl;
for (size_t i = 0 ; i < nRowsTotal * nColumns ; i++) {
ifs >> data[i];
}
 
std::memset(data+nRowsTotal*nColumns,0,nRowsTotal*nColumns*sizeof(float));
}
 
Poisson::Poisson(const size_t r, const size_t c, float* d){
bufferSide = 0;
nRowsTotal = r;
nColumns = c;
try{
data = new float[r*c*2];
}
catch (...){
throw std::runtime_error("Failed to Allocate Memory");
}
std::memcpy(data,d,r*c*sizeof(float));
std::memset(data+r*c,0,r*c*sizeof(float));
}
 
void Poisson::update (size_t startRow, size_t endRow, const float wx, const float wy){
float* x_new = data + (1-bufferSide)*nRowsTotal*nColumns;
float* x_old = data + bufferSide*nRowsTotal*nColumns;
for (size_t i = startRow; i <= endRow; i++)
for (size_t j = 1; j < nColumns - 1; j++)
x_new[i * nColumns + j] = x_old[i * nColumns + j]
+ wx * (x_old[(i + 1) * nColumns + j] + x_old[(i - 1) * nColumns + j]
- 2.0f * x_old[i * nColumns + j])
+ wy * (x_old[i * nColumns + j + 1] + x_old[i * nColumns + j - 1]
- 2.0f * x_old[i * nColumns + j]);
}
 
float* Poisson::operator()(const size_t nIterations, const float wx, const float wy){
for (size_t i = 0; i < nIterations; i++) {
update(0, nRowsTotal-1, wx, wy);
bufferSwitch();
}
return data;
}
 
void Poisson::show(std::ostream& ofs) const{
ofs << std::fixed << std::setprecision(1);
for (size_t j = 0; j < nColumns ; j++) {
for (size_t i = 0 ; i < nRowsTotal ; i++)
ofs << std::setw(8) << data[ bufferSide*nColumns*nRowsTotal + i * nColumns + j];
ofs << std::endl;
}
}
}
 
</source>
|}
{| class="wikitable mw-collapsible mw-collapsed"
! main.cpp
|-
|
<source>
// based on code from LLNL tutorial mpi_heat2d.c
// Master-Worker Programming Model
// Chris Szalwinski - 2018/11/13
// Adopted by Tony Sim - 2019/02/16
#include <iostream>
#include <fstream>
#include <iomanip>
#include <cstdlib>
#include <stdexcept>
 
#include "poisson.h"
 
// solution constants
const size_t NONE = 0;
const size_t MINPARTITIONS = 1;
const size_t MAXPARTITIONS = 7;
// weights
const float wx = 0.1f;
const float wy = 0.1f;
 
int main(int argc, char** argv) {
if (argc != 4) {
std::cerr << "*** Incorrect number of arguments ***\n";
std::cerr << "Usage: " << argv[0]
<< " input_file output_file no_of_iterations\n";
return 1;
}
 
std::ifstream input(argv[1]);
std::ofstream output(argv[2]);
std::ofstream temp("init.csv");
 
if(!input.is_open()){
std::cerr << "Invalid Input File" << std::endl;
return 2;
}
if(!output.is_open()){
std::cerr << "Invalid Output File" << std::endl;
return 2;
}
 
DPS::Poisson* p = nullptr;
try{
p = new DPS::Poisson(input);
}
catch(std::exception& e){
std::cerr << "Error: " << e.what() << std::endl;
}
 
p->show(temp);
 
size_t nIterations = std::atoi(argv[3]);
 
(*p)(nIterations);
 
// write results to file
p->show(output);
 
delete p;
 
}
 
</source>
|}
===== Introduction =====
The presented code simulates heat map using Jacobi's method for Poisson's equation. It is represented in a 2D array, and each element updates its value based on the adjacent elements at a given moment. Each iteration represent one instance in time. By repeating the calculation over the entire array through multiple iterations, we can estimate the state of the heat transfer after a given time interval.
 
===== Profiling =====
The profiling was conducted using a data set of 79 rows and 205 columns over 150000 iterations.
{| class="wikitable mw-collapsible mw-collapsed"
! Flat profile
|-
|
 
Flat profile:
 
Each sample counts as 0.01 seconds.
% cumulative self self total
time seconds seconds calls us/call us/call name
98.57 2.75 2.75 150000 18.33 18.33 DPS::Poisson::update(unsigned long, unsigned long, float, float)
0.00 2.75 0.00 1 0.00 0.00 _GLOBAL__sub_I__ZN3DPS7PoissonC2ERSt14basic_ifstreamIcSt11char_traitsIcEE
0.00 2.75 0.00 1 0.00 0.00 _GLOBAL__sub_I_main
 
 
|}
{| class="wikitable mw-collapsible mw-collapsed"
! Call graph
|-
|
Call graph
 
 
granularity: each sample hit covers 2 byte(s) for 0.36% of 2.75 seconds
 
index % time self children called name
2.75 0.00 150000/150000 DPS::Poisson::operator()(unsigned long, float, float) [2]
[1] 100.0 2.75 0.00 150000 DPS::Poisson::update(unsigned long, unsigned long, float, float) [1]
-----------------------------------------------
<spontaneous>
[2] 100.0 0.00 2.75 DPS::Poisson::operator()(unsigned long, float, float) [2]
2.75 0.00 150000/150000 DPS::Poisson::update(unsigned long, unsigned long, float, float) [1]
-----------------------------------------------
0.00 0.00 1/1 __libc_csu_init [21]
[10] 0.0 0.00 0.00 1 _GLOBAL__sub_I__ZN3DPS7PoissonC2ERSt14basic_ifstreamIcSt11char_traitsIcEE [10]
-----------------------------------------------
0.00 0.00 1/1 __libc_csu_init [21]
[11] 0.0 0.00 0.00 1 _GLOBAL__sub_I_main [11]
-----------------------------------------------
 
 
Index by function name
 
[10] _GLOBAL__sub_I__ZN3DPS7PoissonC2ERSt14basic_ifstreamIcSt11char_traitsIcEE (poisson.cpp) [11] _GLOBAL__sub_I_main (main.cpp) [1] DPS::Poisson::update(unsigned long, unsigned long, float, float)
 
 
|}
 
=====Analysis=====
given 98.57 percent of time is spent on the update() function, it is considered the hotspot.
Total time taken was 2.75.
 
If we consider a GPU environment with 1000 cores, we can estimate the following speedup:
S1000 = 1/(1-.9857 + .9857/1000) = 65.00
In fact, the speed will decrease from 2.75 seconds to 0.0450 seconds.
 
==== Robert ====
===== Multi Sampling Anti Aliasing =====
70
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