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merge.cu
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merge.cu
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#include <iostream>
#include <moderngpu.cuh>
#include <thrust/device_vector.h>
#include <thrust/merge.h>
#include <thrust/sort.h>
#include <thrust/detail/temporary_array.h>
#include <bulk/bulk.hpp>
#include "join_iterator.hpp"
#include "time_invocation_cuda.hpp"
template<std::size_t groupsize, std::size_t grainsize, typename RandomAccessIterator1, typename Size,typename RandomAccessIterator2, typename RandomAccessIterator3, typename RandomAccessIterator4, typename Compare>
__device__
RandomAccessIterator4
staged_merge(bulk::concurrent_group<bulk::agent<grainsize>,groupsize> &exec,
RandomAccessIterator1 first1, Size n1,
RandomAccessIterator2 first2, Size n2,
RandomAccessIterator3 stage,
RandomAccessIterator4 result,
Compare comp)
{
// copy into the stage
bulk::copy_n(bulk::bound<groupsize * grainsize>(exec),
::make_join_iterator(first1, n1, first2),
n1 + n2,
stage);
// inplace merge in the stage
bulk::inplace_merge(bulk::bound<groupsize * grainsize>(exec),
stage, stage + n1, stage + n1 + n2,
comp);
// copy to the result
// XXX this might be slightly faster with a bounded copy_n
return bulk::copy_n(exec, stage, n1 + n2, result);
} // end staged_merge()
struct merge_kernel
{
template<std::size_t groupsize, std::size_t grainsize, typename RandomAccessIterator1, typename Size, typename RandomAccessIterator2, typename RandomAccessIterator3, typename RandomAccessIterator4, typename Compare>
__device__
void operator()(bulk::concurrent_group<bulk::agent<grainsize>,groupsize> &g,
RandomAccessIterator1 first1, Size n1,
RandomAccessIterator2 first2, Size n2,
RandomAccessIterator3 merge_paths_first,
RandomAccessIterator4 result,
Compare comp)
{
typedef int size_type;
size_type elements_per_group = g.size() * g.this_exec.grainsize();
// determine the ranges to merge
size_type mp0 = merge_paths_first[g.index()];
size_type mp1 = merge_paths_first[g.index()+1];
size_type diag = elements_per_group * g.index();
size_type local_size1 = mp1 - mp0;
size_type local_size2 = thrust::min<size_type>(n1 + n2, diag + elements_per_group) - mp1 - diag + mp0;
first1 += mp0;
first2 += diag - mp0;
result += elements_per_group * g.index();
typedef typename thrust::iterator_value<RandomAccessIterator4>::type value_type;
#if __CUDA_ARCH__ >= 200
// merge through a stage
value_type *stage = reinterpret_cast<value_type*>(bulk::malloc(g, elements_per_group * sizeof(value_type)));
if(bulk::is_on_chip(stage))
{
staged_merge(g,
first1, local_size1,
first2, local_size2,
bulk::on_chip_cast(stage),
result,
comp);
} // end if
else
{
staged_merge(g,
first1, local_size1,
first2, local_size2,
stage,
result,
comp);
} // end else
bulk::free(g, stage);
#else
__shared__ bulk::uninitialized_array<value_type, groupsize * grainsize> stage;
staged_merge(g, first1, local_size1, first2, local_size2, stage.data(), result, comp);
#endif
} // end operator()
}; // end merge_kernel
template<typename Size, typename RandomAccessIterator1,typename RandomAccessIterator2, typename Compare>
struct locate_merge_path
{
Size partition_size;
RandomAccessIterator1 first1, last1;
RandomAccessIterator2 first2, last2;
Compare comp;
locate_merge_path(Size partition_size, RandomAccessIterator1 first1, RandomAccessIterator1 last1, RandomAccessIterator2 first2, RandomAccessIterator2 last2, Compare comp)
: partition_size(partition_size),
first1(first1), last1(last1),
first2(first2), last2(last2),
comp(comp)
{}
template<typename Index>
__device__
Size operator()(Index i)
{
Size n1 = last1 - first1;
Size n2 = last2 - first2;
Size diag = thrust::min<Size>(partition_size * i, n1 + n2);
return bulk::merge_path(first1, n1, first2, n2, diag, comp);
}
};
template<typename RandomAccessIterator1,
typename RandomAccessIterator2,
typename RandomAccessIterator3,
typename Compare>
RandomAccessIterator3 my_merge(RandomAccessIterator1 first1,
RandomAccessIterator1 last1,
RandomAccessIterator2 first2,
RandomAccessIterator2 last2,
RandomAccessIterator3 result,
Compare comp)
{
typedef typename thrust::iterator_value<RandomAccessIterator1>::type value_type;
typedef typename thrust::iterator_difference<RandomAccessIterator1>::type difference_type;
typedef int size_type;
// 90/86/97
const size_type groupsize = (sizeof(value_type) == sizeof(int)) ? 256 : 256 + 32;
const size_type grainsize = (sizeof(value_type) == sizeof(int)) ? 9 : 5;
const size_type tile_size = groupsize * grainsize;
difference_type n = (last1 - first1) + (last2 - first2);
difference_type num_groups = (n + tile_size - 1) / tile_size;
thrust::cuda::tag t;
thrust::detail::temporary_array<size_type,thrust::cuda::tag> merge_paths(t, num_groups + 1);
thrust::tabulate(merge_paths.begin(), merge_paths.end(), locate_merge_path<size_type,RandomAccessIterator1,RandomAccessIterator2,Compare>(tile_size,first1,last1,first2,last2,comp));
// merge partitions
size_type heap_size = tile_size * sizeof(value_type);
bulk::concurrent_group<bulk::agent<grainsize>,groupsize> g(heap_size);
bulk::async(bulk::par(g, num_groups), merge_kernel(), bulk::root.this_exec, first1, last1 - first1, first2, last2 - first2, merge_paths.begin(), result, comp);
return result + n;
} // end merge()
template<typename T>
void my_merge(const thrust::device_vector<T> *a,
const thrust::device_vector<T> *b,
thrust::device_vector<T> *c)
{
my_merge(a->begin(), a->end(),
b->begin(), b->end(),
c->begin(),
thrust::less<T>());
}
template<typename T>
void sean_merge(const thrust::device_vector<T> *a,
const thrust::device_vector<T> *b,
thrust::device_vector<T> *c)
{
mgpu::ContextPtr ctx = mgpu::CreateCudaDevice(0);
mgpu::MergeKeys(a->begin(), a->size(),
b->begin(), b->size(),
c->begin(),
thrust::less<T>(),
*ctx);
}
template<typename T>
void thrust_merge(const thrust::device_vector<T> *a,
const thrust::device_vector<T> *b,
thrust::device_vector<T> *c)
{
thrust::merge(a->begin(), a->end(),
b->begin(), b->end(),
c->begin(),
thrust::less<T>());
}
template<typename T>
struct hash
{
template<typename Integer>
__device__ __device__
T operator()(Integer x)
{
x = (x+0x7ed55d16) + (x<<12);
x = (x^0xc761c23c) ^ (x>>19);
x = (x+0x165667b1) + (x<<5);
x = (x+0xd3a2646c) ^ (x<<9);
x = (x+0xfd7046c5) + (x<<3);
x = (x^0xb55a4f09) ^ (x>>16);
return x;
}
};
template<typename Vector>
void random_fill(Vector &vec)
{
thrust::tabulate(vec.begin(), vec.end(), hash<typename Vector::value_type>());
}
template<typename T>
void compare(size_t n)
{
thrust::device_vector<T> a(n / 2), b(n / 2);
thrust::device_vector<T> c(n);
random_fill(a);
random_fill(b);
thrust::sort(a.begin(), a.end());
thrust::sort(b.begin(), b.end());
my_merge(&a, &b, &c);
double my_msecs = time_invocation_cuda(50, my_merge<T>, &a, &b, &c);
sean_merge(&a, &b, &c);
double sean_msecs = time_invocation_cuda(50, sean_merge<T>, &a, &b, &c);
thrust_merge(&a, &b, &c);
double thrust_msecs = time_invocation_cuda(50, thrust_merge<T>, &a, &b, &c);
std::cout << "Sean's time: " << sean_msecs << " ms" << std::endl;
std::cout << "Thrust's time: " << thrust_msecs << " ms" << std::endl;
std::cout << "My time: " << my_msecs << " ms" << std::endl;
std::cout << "Performance relative to Sean: " << sean_msecs / my_msecs << std::endl;
std::cout << "Performance relative to Thrust: " << thrust_msecs / my_msecs << std::endl;
}
template<typename T>
void validate(size_t n)
{
thrust::device_vector<T> a(n / 2), b(n / 2);
thrust::device_vector<T> c(n);
random_fill(a);
random_fill(b);
thrust::sort(a.begin(), a.end());
thrust::sort(b.begin(), b.end());
thrust::device_vector<T> ref(n);
thrust::merge(a.begin(), a.end(), b.begin(), b.end(), ref.begin());
my_merge(&a, &b, &c);
std::cout << "CUDA error: " << cudaGetErrorString(cudaThreadSynchronize()) << std::endl;
assert(c == ref);
}
int main()
{
size_t n = 123456789;
validate<int>(n);
std::cout << "Large input: " << std::endl;
std::cout << "int: " << std::endl;
compare<int>(n);
std::cout << "float: " << std::endl;
compare<float>(n);
std::cout << "double: " << std::endl;
compare<double>(n);
std::cout << std::endl;
return 0;
}