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#include <sycl/ext/intel/fpga_extensions.hpp>
#include <chrono>
#include "kernel.hpp"
template<typename T>
SYCL_EXTERNAL bool checkOptimality(device_ptr<T> C, int size) {
bool isOptimal = false;
int positveValueCount = 0;
//check if the coefficients of the objective function are negative
for(int i=0; i<size;i++){
float value = C[i];
if(value >= 0){
positveValueCount++;
}
}
//if all the constraints are positive now,the table is optimal
if(positveValueCount == size){
isOptimal = true;
}
return isOptimal;
}
template<typename T>
SYCL_EXTERNAL int findPivotColumn(device_ptr<T> C, int size) {
int location = 0;
float minimum = C[0];
for(int i=1; i<size; ++i) {
if(C[i]<minimum) {
minimum = C[i];
location = i;
}
}
return location;
}
//find the row with the pivot value.The least value item's row in the B array
template<typename T>
SYCL_EXTERNAL int findPivotRow(device_ptr<T> A, device_ptr<T> B, device_ptr<T> C, int pivotColumn, int rows, int cols, bool *isUnbounded) {
int negativeValueCount = 0;
for (int i = 0; i < rows; i++) {
// 2d to 1d array index mapping
int pivotColumnIndex = (i*cols)+pivotColumn;
if (A[pivotColumnIndex] <= 0) {
negativeValueCount += 1;
}
}
int location = 0;
//checking the unbound condition if all the values are negative ones
if (negativeValueCount == rows) {
*isUnbounded = true;
} else {
float minimum = 99999999.0;
for (int i = 0; i < rows; ++i) {
// 2d to 1d array index mapping
int pivotColumnIndex = (i*cols)+pivotColumn;
float tmpACols = A[pivotColumnIndex];
if (tmpACols > 0) {
float result = B[i] / tmpACols;
if (result > 0 && result < minimum) {
minimum = result;
location = i;
}
}
}
}
return location;
}
template<typename T>
SYCL_EXTERNAL void doPivotting(device_ptr<T> A, device_ptr<T> B, device_ptr<T> C, int pivotRow, int pivotColumn, int rows, int cols) {
int columnIndex = (pivotRow*cols)+pivotColumn;
float pivetValue = A[columnIndex];
float pivotRowVals[6]; //the column with the pivot
float pivotColVals[3]; //the row with the pivot
float rowNew[6]; //the row after processing the pivot value
float maximum = 0;
maximum = maximum-(C[pivotColumn]*(B[pivotRow]/pivetValue)); //set the maximum step by step
//get the row that has the pivot value
for (int i = 0; i < cols; ++i) {
int pivotRowIndex = (pivotRow*cols)+i;
pivotRowVals[i] = A[pivotRowIndex];
}
//get the column that has the pivot value
for (int j = 0; j < rows; ++j) {
int pivotColIndex = (j*cols)+pivotColumn;
pivotColVals[j] = A[pivotColIndex];
}
//set the row values that has the pivot value divided by the pivot value and put into new row
for (int k = 0; k < cols; ++k) {
rowNew[k] = pivotRowVals[k]/pivetValue;
}
B[pivotRow] = B[pivotRow]/pivetValue;
//process the other coefficients in the A array by subtracting
for (int m=0; m < rows; ++m) {
//ignore the pivot row as we already calculated that
if (m != pivotRow) {
for (int p = 0; p<cols; ++p) {
float multiplyValue = pivotColVals[m];
int indexA_M_P = (m*cols)+p;
A[indexA_M_P] = A[indexA_M_P] - (multiplyValue * rowNew[p]);
//C[p] = C[p] - (multiplyValue*C[pivotRow]);
//B[i] = B[i] - (multiplyValue*B[pivotRow]);
}
}
}
//process the values of the B array
for (int i = 0; i<rows; ++i) { // rows = B.size()
if (i != pivotRow) {
float multiplyValue = pivotColVals[i];
B[i] = B[i]-(multiplyValue*B[pivotRow]);
}
}
//the least coefficient of the constraints of the objective function
float multiplyValue = C[pivotColumn];
//process the C array
for (int i = 0; i < C.size(); i++) {
C[i] = C[i]-(multiplyValue * rowNew[i]);
}
//replacing the pivot row in the new calculated A array
for (int i = 0; i<cols; ++i) {
int indexA_pivotRow_i = (pivotRow*cols)+i;
A[indexA_pivotRow_i] = rowNew[i];
}
}
// Forward declare the kernel names in the global scope. This FPGA best practice
// reduces compiler name mangling in the optimization reports.
class SimplexCalc;
double RunKernel(queue &q, std::vector<T> &inAHost, std::vector<T> &inBHost,
std::vector<T> &inCHost, std::vector<int>& resultFlags) {
int rowSizeA = inBHost.size();
int colSizeA = inCHost.size();
T *inADevice = malloc_device<T> (inAHost.size(), q);
T *inBDevice = malloc_device<T> (inBHost.size(), q);
T *inCDevice = malloc_device<T> (inCHost.size(), q);
int *inResultFlagsDevice = malloc_device<int> (resultFlags.size(), q);
if (inADevice == nullptr) {
std::cerr << "ERROR: failed to allocate space for 'inADevice'\n";
std::terminate();
}
if (inBDevice == nullptr) {
std::cerr << "ERROR: failed to allocate space for 'inBDevice'\n";
std::terminate();
}
if (inCDevice == nullptr) {
std::cerr << "ERROR: failed to allocate space for 'inCDevice'\n";
std::terminate();
}
auto start = std::chrono::high_resolution_clock::now();
q.memcpy(inADevice, inAHost.data(), inAHost.size()*sizeof(T)).wait();
q.memcpy(inBDevice, inBHost.data(), inBHost.size() * sizeof(T)).wait();
q.memcpy(inCDevice, inCHost.data(), inCHost.size() * sizeof(T)).wait();
q.memcpy(inResultFlagsDevice, resultFlags.data(), resultFlags.size()*sizeof(int)).wait();
q.submit([&](handler &h) {
h.single_task < SimplexCalc > ([=]()[[intel::kernel_args_restrict]] {
device_ptr<T> inA(inADevice);
device_ptr<T> inB(inBDevice);
device_ptr<T> inC(inCDevice);
device_ptr<int> inResultFlags(inResultFlagsDevice);
bool tempIsOptimizal = checkOptimality(inC, colSizeA);
if (tempIsOptimizal) {
inResultFlags[0] = 1;
return;
} else {
inResultFlags[0] = 0;
}
int pivotColumn = findPivotColumn(inC, colSizeA);
inResultFlags[1] = pivotColumn;
inA[0] = 43.0; //test only
bool isUnbounded = true;
int pivotRow = findPivotRow(inA, inB, inC, pivotColumn, rowSizeA, colSizeA, &isUnbounded);
inResultFlags[2] = pivotRow;
});
}).wait();
q.memcpy(inAHost.data(), inADevice, inAHost.size()*sizeof(T));
q.memcpy(inBHost.data(), inBDevice, inBHost.size()*sizeof(T));
q.memcpy(inCHost.data(), inCDevice, inCHost.size()*sizeof(T));
q.memcpy(resultFlags.data(), inResultFlagsDevice, resultFlags.size()*sizeof(int));
auto end = std::chrono::high_resolution_clock::now();
std::chrono::duration<double, std::milli> diff = end - start;
sycl::free(inADevice, q);
sycl::free(inBDevice, q);
sycl::free(inCDevice, q);
sycl::free(inResultFlagsDevice, q);
return diff.count();
}
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