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Grapple

Grapple is a specialized Thrust execution policy that intercepts Thrust functions for performance profiling and debugging. It is especially useful for tuning the performance of complex Thrust-based libraries.

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A Simple Example

#include <grapple/grapple.h>

#include <thrust/device_vector.h>
#include <thrust/random.h>
#include <thrust/sort.h>

void initialize(thrust::device_vector<float>& v)
{
    thrust::default_random_engine rng(123456);
    thrust::uniform_int_distribution<int> dist(2, 19);
    for(size_t i = 0; i < v.size(); i++)
        v[i] = dist(rng) / 2.0f;
}

int main(void)
{
    size_t N = 1<<18;

    thrust::device_vector<float> keys(N);
    initialize(keys);
    thrust::sort(grapple_system(), keys.begin(), keys.end());

    return 0;
}

In the above example grapple transparently intercepts the Thrust sort function. Grapple collects data concerning the execution time and memory allocation and automatically prints this information to the console once the grapple object goes out of scope.

[ 0]sort                    : 0.790976 (ms), allocated : 1137408    bytes

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Code Litter

Grapple is designed to exploit execution policies in order to avoid littering Thrust based libraries with spurious performance profiling code. Coarse-grained profiling of entire functions, such as my_func, provides a general performance overview but fine-grained profiling may be more useful for identifying performance and memory limited sections of code. However, fine-grained profiling requires altering individual functions with timer specific code.

#include <thrust/device_vector.h>
#include <thrust/sort.h>
#include <thrust/reduce.h>

template<typename Array>
void my_func(Array& keys)
{
  // initialize some performance timer
  timer tsort;
  thrust::sort(keys.begin(), keys.end());
  // return sort elapsed time
  tsort.milliseconds_elapsed();

  timer treduce;
  thrust::reduce(keys.begin(), keys.end());
  treduce.milliseconds_elapsed();
}

int main(void)
{
    thrust::device_vector<float> keys(1<<10);

    timer tmy_func;
    my_func(keys);
    return tmy_func.milliseconds_elapsed();

    return 0;
}

Grapple leverages the use of execution policies to provide flexible profiling and allows the user to control the level of granularity without adding specialized code to any underlying functions. The cost of this flexibility is tigher integration with the Thrust dispatch system.

Adding code to integrate tightly with execution polices requires additional code but the use is much more flexible than performance specific code.

#include <thrust/device_vector.h>
#include <thrust/execution_policy.h>
#include <thrust/sort.h>
#include <thrust/reduce.h>

#include <grapple/grapple.h>

template<typename Policy, typename Array>
void my_func(const Policy& exec,
             Array& keys)
{
  thrust::sort(exec, keys.begin(), keys.end());
  thrust::reduce(exec, keys.begin(), keys.end());
}

template<typename Array>
void my_func(Array& keys)
{
  typename thrust::iterator_system<typename Array::iterator>::type system;
  my_func(system, keys);
}

int main(void)
{
  thrust::device_vector<float> keys(1<<10);

  // call my_func normally
  my_func(keys);

  // call my_func with profiling
  my_func(grapple_system(), keys);

  return 0;
}