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Hi
I am newbie with Linux(I have Ubuntu 14.04) and TBB. I want to write codes with TBB library and run on computer. I have no idea how should I start .
Can anyone help me with a step by step tutorial or something that help me?
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Thanks.
My first problem is how should I be sure I have TBB on my system ? I have installed parallel studio xe 2016 and in it's directory and in my terminal run this command "source iccvars.sh intel64".
My first example is
#include <tbb/tbb.h> #include <iostream> #include <omp.h> using namespace std; using namespace tbb; class Average { public: float* input; float* output; void operator( )( const blocked_range<int>& range ) const { for( int i=range.begin(); i!=range.end( ); ++i ) { output = (input[i-1]+input+input[i+1])/3.0f; } } }; void ParallelAverage( float* output, float* input, size_t n ) { Average avg; avg.input = input; avg.output = output; output[0]=(input[0]+input[1])/2.0f; parallel_for( blocked_range<int>( 1, n-1, 100 ), avg ); output[n-1]=(input[n-1]+input[n-2])/2.0f; } void SerialAverage(float* output,float* input,int n){ output[0] = (input[0]+input[1])/2.0f; for(long int i=1; i<n-1; ++i ) { output = (input[i-1]+input+input[i+1])/3.0f; } output[n-1] = (input[n-1]+input[n-2])/2.0f; } int main() { task_scheduler_init init; srand ( time(NULL) ); unsigned long long int lenght=1000000; float input[lenght]; float output[lenght],temp[lenght]; double serial_timer = 0.; double compute_timer = 0.; for(size_t i=0;i<lenght;i++) input=rand()%100; compute_timer -= omp_get_wtime(); ParallelAverage(output,input,lenght); compute_timer += omp_get_wtime(); cout << "Calculation time in parallel = " << compute_timer<<endl; compute_timer = 0.; serial_timer -= omp_get_wtime(); SerialAverage(temp,input,lenght); serial_timer += omp_get_wtime(); cout<<"Calculation time in serial="<< serial_timer<<endl; return 0; }
But calculating average of next and previous of each item is much faster than in serial loop than parallel one.
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Thanks.
My first problem is how should I be sure I have TBB on my system ? I have installed parallel studio xe 2016 and in it's directory and in my terminal run this command "source iccvars.sh intel64".
My first example is
#include <tbb/tbb.h> #include <iostream> #include <omp.h> using namespace std; using namespace tbb; class Average { public: float* input; float* output; void operator( )( const blocked_range<int>& range ) const { for( int i=range.begin(); i!=range.end( ); ++i ) { output = (input[i-1]+input+input[i+1])/3.0f; } } }; void ParallelAverage( float* output, float* input, size_t n ) { Average avg; avg.input = input; avg.output = output; output[0]=(input[0]+input[1])/2.0f; parallel_for( blocked_range<int>( 1, n-1, 100 ), avg ); output[n-1]=(input[n-1]+input[n-2])/2.0f; } void SerialAverage(float* output,float* input,int n){ output[0] = (input[0]+input[1])/2.0f; for(long int i=1; i<n-1; ++i ) { output = (input[i-1]+input+input[i+1])/3.0f; } output[n-1] = (input[n-1]+input[n-2])/2.0f; } int main() { task_scheduler_init init; srand ( time(NULL) ); unsigned long long int lenght=1000000; float input[lenght]; float output[lenght],temp[lenght]; double serial_timer = 0.; double compute_timer = 0.; for(size_t i=0;i<lenght;i++) input=rand()%100; compute_timer -= omp_get_wtime(); ParallelAverage(output,input,lenght); compute_timer += omp_get_wtime(); cout << "Calculation time in parallel = " << compute_timer<<endl; compute_timer = 0.; serial_timer -= omp_get_wtime(); SerialAverage(temp,input,lenght); serial_timer += omp_get_wtime(); cout<<"Calculation time in serial="<< serial_timer<<endl; return 0; }
But calculating average of next and previous of each item is much faster than in serial loop than parallel one.
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(Please remove the second copy of your posting. Well, edit it down to "(Removed second copy)" or something.)
TBB has to get out of the starting blocks first (even task-based toolkits have to start up some worker threads), so your timings will be useless in such a small benchmark. Try a few ParallelAverage executions, and only then start the timer. Tip: decrease variance by averaging out several executions.
What's the difference in timing, if any, if you "hoist" end() out of the loop: "for( int i=range.begin(), i_end=range.end(); i!=i_end; ++i )"? This might help the compiler unroll or even auto-vectorise the loop, which can make a huge difference. Alternatively, try accepting the blocked_range by value: maybe the compiler can figure it all out by itself, then. Please give times for the original, both variants, and perhaps the combination: supposedly you should have one "slow" execution" and 2 or 3 that are close to each other and a lot faster.
Also, you should probably use a far larger grainsize for such a simple Body, especially if you have a lot of hardware parallelism on your machine (which makes the auto_partitioner pick a fairly small average effective grainsize). Please also provide timings for what you find here.
Then there's telling the compiler to vectorise, using "#pragma simd" (instead of merely hoping that it might). Same request about timings...

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