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Hello

I have a piece of code which I tried to parallelize using OpenMP. And then used parallel studio to check  for data race. It reported one. But I cannot understand why this instance is reported as data race. Can some please help me understand this instance.

Below is the piece of code.

typedef int int32;
typedef char int8;

void**
Alloc ( int32 nRowNum, int32 nColumnNum, int32 sItemSize )
{
void** ppvBuffer = 0;
int8* pvBuffer = 0;
int32 lIndex;
int32 nStep = nColumnNum * sItemSize ;

if ( !nRowNum || !nColumnNum )
return NULL;

ppvBuffer = (void**)new void* [ nRowNum ];
memset(ppvBuffer, 0, sizeof(void*) * nRowNum);
pvBuffer = (int8*)new int8 [ nRowNum*nColumnNum*sItemSize ];
memset(pvBuffer, 0, sizeof(int8) * nRowNum*nColumnNum*sItemSize);
for ( lIndex = 0; lIndex < nRowNum; lIndex++, pvBuffer += nStep )
ppvBuffer[ lIndex ] = pvBuffer;

return ppvBuffer;
}

void
Free ( void** ppvBuffer)
{
if ( ppvBuffer )
{
if ( ppvBuffer[0] )
delete [] ppvBuffer[0];

delete [] ppvBuffer;
}
ppvBuffer = NULL;
}

void function1(int8 **ppBuffer)
{
int x, y;
#pragma omp parallel for private(x,y) shared(ppBuffer)
for(x = 0; x < 10; x++)
for(y = 0; y< 10; y++)
ppBuffer[x][y] = 10;
return;
}


void function2(int8 **ppBuffer1, int8 **ppBuffer2)
{
int x, y, i, j;
#pragma omp parallel for private(x,y, i, j)shared(ppBuffer2, ppBuffer1)
for(x = 0; x < 10; x++)
{
i = x + 1;
for(y = 0; y< 10; y++)
{
j = y + 1;
ppBuffer2[x][y] = ppBuffer1[i][j];
}
}
return;
}

int main(void)
{
int8 ** ppBuffer1 = NULL;
int8 ** ppBuffer2 = NULL;

ppBuffer1 = (int8 **)Alloc(11, 11, sizeof(char));
ppBuffer2 = (int8 **)Alloc(11, 11, sizeof(char));

function1(ppBuffer1);
function2(ppBuffer1, ppBuffer2);

Free((void **)ppBuffer1);
Free((void **)ppBuffer2);

return 0;
}

I have used Visuall Studio 2005 Compiler. Intel parallel studio reports that there is a data race between read in function2 and a write in function 1.( which are highlighted).

Surprisingly, if I use the Intel C++ compiler, the data race is gone.

Also in the above implementation if I separate the pragma for "parallel" and "for" as shown below in both functions  data race is gone.

#pragma omp parallel private(x,y) shared(ppBuffer)
{
#pragma omp for
for(x = 0; x < 10; x++)
for(y = 0; y< 10; y++)
ppBuffer[x][y] = 10;
return;
}

Any help in this regard is highly appreciated.

Thanks in advance.