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6,383 bytes added, 02:18, 8 April 2018
LZW Data Compression Algorithm
Original algorithm: https://codereview.stackexchange.com/questions/86543/simple-lzw-compression-algorithm
Raw Flat profile (50Mb Test file for compression): Each sample counts as 0.01 seconds. % cumulative self self total time seconds seconds calls us/call us/call name 35.52 4.23 4.23 compress(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, int, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >) 27.54 7.51 3.28 102062309 0.03 0.03 std::_Hashtable<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::pair<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const, int>, std::allocator<std::pair<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const, int> >, std::__detail::_Select1st, std::equal_to<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > >, std::hash<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > >, std::__detail::_Mod_range_hashing, std::__detail::_Default_ranged_hash, std::__detail::_Prime_rehash_policy, std::__detail::_Hashtable_traits<true, false, true> >::_M_find_before_node(unsigned int, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, unsigned int) const 20.15 9.91 2.40 204116423 0.01 0.01 std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >::_M_replace_aux(unsigned int, unsigned int, unsigned int, char) 8.23 10.89 0.98 49629412 0.02 0.05 std::__detail::_Map_base<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::pair<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const, int>, std::allocator<std::pair<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const, int> >, std::__detail::_Select1st, std::equal_to<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > >, std::hash<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > >, std::__detail::_Mod_range_hashing, std::__detail::_Default_ranged_hash, std::__detail::_Prime_rehash_policy, std::__detail::_Hashtable_traits<true, false, true>, true>::operator[](std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) 4.28 11.40 0.51 52428800 0.01 0.01 std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >::_M_assign(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) 3.02 11.76 0.36 52436762 0.01 0.01 show_usage() 1.26 11.91 0.15 _Z22convert_char_to_stringB5cxx11PKci 0.00 11.91 0.00 4097 0.00 0.00 std::_Hashtable<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::pair<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const, int>, std::allocator<std::pair<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const, int> >, std::__detail::_Select1st, std::equal_to<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > >, std::hash<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > >, std::__detail::_Mod_range_hashing, std::__detail::_Default_ranged_hash, std::__detail::_Prime_rehash_policy, std::__detail::_Hashtable_traits<true, false, true> >::_M_insert_unique_node(unsigned int, unsigned int, std::__detail::_Hash_node<std::pair<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const, int>, true>*) 0.00 11.91 0.00 22 0.00 0.01 std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >::_M_mutate(unsigned int, unsigned int, char const*, unsigned int) 0.00 11.91 0.00 1 0.00 0.00 _GLOBAL__sub_I__Z18convert_int_to_binB5cxx11i 0.00 11.91 0.00 1 0.00 28.13 std::_Hashtable<std::__cxx11::basic_ Summarized Flat Profile (50Mb Test file for compression): % cumulative self self total time seconds seconds calls us/call us/call name 35.52 4.23 4.23 compress() 27.54 7.51 3.28 102062309 0.03 0.03 std::_Hashtable 20.15 9.91 2.40 204116423 0.01 0.01 std::__cxx11::basic_string 8.23 10.89 0.98 49629412 0.02 0.05 std::__detail::_Map_base 4.28 11.40 0.51 52428800 0.01 0.01 std::__cxx11::basic_string 3.02 11.76 0.36 52436762 0.01 0.01 show_usage() 1.26 11.91 0.15 _Z22convert_char_to_stringB5cxx11PKci 0.00 11.91 0.00 4097 0.00 0.00 std::_Hashtable 0.00 11.91 0.00 22 0.00 0.01 std::__cxx11::basic_string 0.00 11.91 0.00 1 0.00 0.00 _GLOBAL__sub_I__Z18convert_int_to_binB5cxx11i 0.00 11.91 0.00 1 0.00 28.13 std::_Hashtable<std::__cxx11::basic_ Note how the compress() function takes up the largest amount of time (over one third), then the other functions which take up over 10% of the time are library functions. It is highly unlikely we could parallelize the library functions. The other functions that take up under 10% of the time will probably not give enough improvement in time to make a significant impact. Thus, the function we should focus on is the compress function. Summary of Compress() Profiles
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The compress function seems to have some room for improvement as can be seen in the source code below:
void compress(string input, int size, string filename) {
outputFile.close();
}
 
There are two loops which show possibility of parallelization:
 
for ( int unsigned i = 0 ; i < 256 ; i++ ){
compress_dictionary[string(1,i)] = i;
}
 
and
 
for(char& c: input){
current_string = current_string + c; // Possible area for improvement via reduction
if ( compress_dictionary.find(current_string) ==compress_dictionary.end() ){
if (next_code <= MAX_DEF)
compress_dictionary.insert(make_pair(current_string, next_code++));
current_string.erase(current_string.size()-1);
outputFile << convert_int_to_bin(compress_dictionary[current_string]);
current_string = c;
}
}
 
The first for loop is constant and probably won't show much improvement if we parallelize it.
 
Note the comment above the second for loop notes we can do something like this:
for (int i = 1; i < n; i+=) a[0] += a[i];
changed to
for (int s = 1; s <= n/2; s*=2) for(int j = 0; j < n; j +=2 * s) a[j] += a[j + s];
The first for loop is constant and probably won't show much improvement if we parallelize it. As such, the major hotspot in this function is the second for loop. This is especially true since the file might be very large and we may be dealing with millions of characters!The one thing we need to worry about is that order does seem to matter for the second for loop.
==== Conclusion ====
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