Move algo to class
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@ -16,7 +16,7 @@ an arbitrary number of processors, as Amdahl’s and Gustafson-Barsis’ laws
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require.
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Assuming that this equal division is possible, estimate α, i.e., the part of the
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program that can be parallelized, by using a profiler like gprof or valgrind to
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measure the duration of mergesort’s execution relative to the overall execution
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measure the duration of sort’s execution relative to the overall execution
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time. Use this number to estimate the predicted speedup for your program.
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Does α depend on the size of the input? If it does, how should you modify
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your predictions and their graphical illustration?
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@ -52,7 +52,7 @@ int main(int argc, char *argv[]) {
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auto t1 = std::chrono::high_resolution_clock::now();
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algo::mergesort(dataset.begin(), dataset.end(), [](int32_t a, int32_t b) {
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algo::MergeSort_v1::sort(dataset.begin(), dataset.end(), [](int32_t a, int32_t b) {
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return (a > b);
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});
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@ -5,71 +5,76 @@
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namespace algo {
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template<typename Iterator, typename Comparator>
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void merge(Iterator start, Iterator middle, Iterator end, Comparator cmp, Iterator output_start) {
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Iterator start_m = start;
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Iterator begin = output_start;
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Iterator start2 = middle + 1;
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class MergeSort_v1 {
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private:
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template<typename Iterator, typename Comparator>
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static auto merge(Iterator start, Iterator middle, Iterator end, Comparator cmp, Iterator output_start) -> void {
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Iterator start_m = start;
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Iterator begin = output_start;
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Iterator start2 = middle + 1;
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//merge from input until one half completes
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while (start <= middle && start2 <= end) {
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if (cmp(*start, *start2)) {
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//merge from input until one half completes
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while (start <= middle && start2 <= end) {
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if (cmp(*start, *start2)) {
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*output_start = *start;
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start++;
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} else {
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*output_start = *start2;
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start2++;
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}
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output_start++;
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}
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//try to finish first half
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while (start <= middle) {
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*output_start = *start;
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start++;
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} else {
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output_start++;
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}
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while (start2 <= end) {
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*output_start = *start2;
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start2++;
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output_start++;
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}
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output_start++;
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const auto size = std::distance(start_m, end);
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for (auto i = 0; i <= size; i++, start_m++, begin++) {
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*start_m = *begin;
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}
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}
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//try to finish first half
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while (start <= middle) {
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*output_start = *start;
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start++;
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output_start++;
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template<typename Container, typename Iterator, typename Comparator>
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static auto ms_split(Container &output_vec, Iterator start, Iterator end, Comparator cmp, Iterator output_start) -> void {
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Iterator mid = start;
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Iterator begin = output_start;
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if (std::distance(start, end) < 1) {
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return;
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} else {
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//move mid iterator litterally to the mid
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std::advance(mid, std::distance(start, end) / 2);
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//sort the first half within an recursion
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ms_split(output_vec, start, mid, cmp, output_start);
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//move output iterator
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std::advance(output_start, std::distance(start, mid + 1));
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//sort the second half within a recursion
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ms_split(output_vec, mid + 1, end, cmp, output_start);
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//merge everything together starting from the complete beginning
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merge(start, mid, end, cmp, begin);
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}
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}
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while (start2 <= end) {
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*output_start = *start2;
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start2++;
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output_start++;
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public:
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template<typename Iterator, typename Comparator>
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static auto sort(Iterator start, Iterator end, Comparator cmp) -> void {
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using valtype = typename std::iterator_traits<Iterator>::value_type;
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std::vector<valtype> temporary_dataset(std::distance(start, end));
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ms_split(temporary_dataset, start, end - 1, cmp, temporary_dataset.begin());
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}
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};
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const auto size = std::distance(start_m, end);
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for (auto i = 0; i <= size; i++, start_m++, begin++) {
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*start_m = *begin;
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}
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}
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template<typename Container, typename Iterator, typename Comparator>
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void ms_split(Container &output_vec, Iterator start, Iterator end, Comparator cmp, Iterator output_start) {
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Iterator mid = start;
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Iterator begin = output_start;
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if (std::distance(start, end) < 1) {
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return;
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} else {
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//move mid iterator litterally to the mid
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std::advance(mid, std::distance(start, end) / 2);
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//sort the first half within an recursion
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ms_split(output_vec, start, mid, cmp, output_start);
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//move output iterator
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std::advance(output_start, std::distance(start, mid + 1));
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//sort the second half within a recursion
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ms_split(output_vec, mid + 1, end, cmp, output_start);
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//merge everything together starting from the complete beginning
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merge(start, mid, end, cmp, begin);
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}
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}
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template<typename Iterator, typename Comparator>
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void mergesort(Iterator start, Iterator end, Comparator cmp) {
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using valtype = typename std::iterator_traits<Iterator>::value_type;
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std::vector<valtype> temporary_dataset(std::distance(start, end));
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ms_split(temporary_dataset, start, end - 1, cmp, temporary_dataset.begin());
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}
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}
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