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Shankar

Total Points:
535
Status Points:
35

Brown Belt

November 9, 2009 10:53 PM PST

Performance degradation

This is about the performance degradation that I find in my application with changes in the tbb::task usage. I have made two sample programs which best replicate the cahnges I made to my application program. Most importantly it also replicates the performance degradation I find in my application as well.

// Serial Fibonnaci sum
long SerialFib( long n ) {
if( n < 2)
return n;
else
return SerialFib(n-1) + SerialFib(n-2);
}

static const int CutOff = 16;
// Parallel Fibonnaci sum using tbb::task
struct FibTask: public tbb::task{
public:
long n;
long x, y;
long* sum;
bool is_continuation;

FibTask( long n_, long* sum_ ) :
n(n_), sum(sum_), is_continuation(false), x(0), y(0)
{}

tbb::task* execute()
{
if( is_continuation ) {
*sum = x+y;
return NULL;
}
else
{
if( n<CutOff ) {
*sum = SerialFib(n);
return NULL;
}
else {
FibTask& a = *new(allocate_child()) FibTask( n-2, &x);
FibTask& b = *new(allocate_child()) FibTask( n-1, &y);
recycle_as_continuation();
is_continuation = true;
// Set ref_count to "two children".
set_ref_count(2);
spawn( b );
return &a;
}
}
}
};

long ParallelFib( long n ) {
long sum;
FibTask& a = *new(tbb::task::allocate_root()) FibTask( n, &sum);
tbb::task::spawn_root_and_wait(a);
return sum;
}

Here is the main program :
Main Program 1

int main( int argc, char *argv[])
{
long n = 36;
int nrTask = 1; // ( 10, 100, 1000)
std::cout << "Computing Fib( " << n << " )" << std::endl;

TaskSchedulerInit init;
tbb::tick_count t0 = tbb::tick_count::now();
for( int i = 0; i < nrTasks; ++i)
long result = ParallelFib( n);
tbb::tick_count t1 = tbb::tick_count::now();
std::cout << "Result :: " << result << " Time Taken :: " << (t1 - t0).seconds() << std::endl;
return 0;
}

The results of main program 1 on a Quad core machine with nrTasks varied from 1, 10, 100, 1000 are as follows

nrTasks                    Total Time taken( in seconds)
1                                     0.071
10                                   0.70
100                                 6.99
1000                               69.83

But if I change the program as follows :
Main Program 2

static const int cacheLineSize = 64;
static const int JumpFactor = cacheLineSize / sizeof(long);

int main( int argc, char *argv[])
{
long n = 36;
int nrTasks = 1; //(10, 100, 1000)

std::cout << "Computing Fib( " << n << " )" << std::endl;
std::cout << "Number of Tasks submitted by input thread => " << nrTasks << "." << std::endl;

long* pSums = reinterpret_cast<long*>( tbb::cache_aligned_allocator<char>().allocate( nrTasks * cacheLineSize));
memset( pSums, 0, nrTasks * cacheLineSize);

TaskSchedulerInit init;
tbb::tick_count t0 = tbb::tick_count::now();
EmptyTask& a = *new( tbb::task::allocate_root()) EmptyTask();
a.set_ref_count(1);
for( int i = 0; i < nrTasks; ++i) {
FibTask& b = *new ( a.allocate_additional_child_of( a)) FibTask( n, &pSums[i * JumpFactor]);
a.spawn( b);
}
a.wait_for_all();
a.destroy( a);
tbb::tick_count t1 = tbb::tick_count::now();
std::cout << "Time Taken :: " << (t1 - t0).seconds() << std::endl;

std::cout << "Validating Results .. " << std::endl;
long sum = SerialFib( n);
for( int i = 0; i < nrTasks; ++i) {
if( sum != pSums[i * JumpFactor]) {
std::cout << "Error in the Fibnocci Calculation for task " << i << std::endl;
throw;
}
}
std::cout << "Validation Passed" << std::endl;
tbb::cache_aligned_allocator<char>().deallocate( reinterpret_cast<char*>(pSums), 0);
return 0;
}

The results of main program 2 are as follows

nrTasks       Total Time taken( in seconds)
1                 0.080
10                 0.80
100       8.015
1000             80.164

Now the results of the main program 1 are as expected. However the results of main program 2 suffer some performance degradation. It looks like per task overhead that is causing the degradation.(or is it because of something else.?)

The difference in main program 1 and main program 2 is that in Program 1 the main thread waits until each task is complete and in Program 2 the main thread just spawns all the tasks and then waits on all the tasks to complete.

Are there ways where the main program 2 could be made to perform as main program 1, keeping the fact that the main thread should spawn all the tasks before it can starts working on the taks spawned?

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