Parsing CSV files with GPU
Parsing delimiter-separated files is a common task in data processing. The regular way of extracting the columns from a text file is to use strtok function :
char * p = strtok(line, "|");
while (p != NULL)
{
printf ("%s\n",p);
p = strtok (NULL, "|");
}
However this method of parsing is CPU bound because
-
it doesn't take advantage of multiple cores of modern CPUs.
-
memory bandwidth limitations
This is how the same task can be done using a GPU :
auto break_cnt = thrust::count(d_readbuff.begin(), d_readbuff.end(), '\n');
thrust::device_vector<int> dev_pos(break_cnt);
thrust::copy_if(thrust::make_counting_iterator(0),
thrust::make_counting_iterator(bytes_read-1),
d_readbuff.begin(), dev_pos.begin(), _1 == '\n');
The first line counts the number of lines in a buffer (assuming that file is read into memory and copied to gpu buffer d_readbuff). The second line creates a vector in gpu memory that will hold the positions of new line characters. The last line compares the characters in a buffer to new line character and, if a match is found, copies the position of the character to dev_pos vector.
Now that we know the starting positions of every line in a buffer, we can launch a gpu procedure that will parse the lines using several thousands gpu cores :
thrust::counting_iterator<unsigned int> begin(0);
parse_functor ff(...); // examples of call's parameters are in test.cu file
thrust::for_each(begin, begin + break_cnt, ff);
As a result we get the needed columns in separate arrays in gpu memory and can copy them to host memory. Or convert them to binary values using relevant gpu procedures :
gpu_atoll atoll_ff(...);
thrust::for_each(begin, begin + break_cnt, atoll_ff);
Benchmarks !
Hardware : PC with one Intel i3-4130, 16GB of RAM, one 2TB hard drive and GTX Titan
File : 750MB lineitem.tbl text file (6001215 lines)
Parsing 1 field using CPU :
$ time cut -d "|" -f 6 lineitem.tbl > /dev/null
real 0m28.764s
Parsing 11 fields using hand-written program with strtok : (no threads, no memory-mapped file)
14.5s
Parsing 11 fields using GPU :
$ time ./test
0.77s
And the actual gpu parsing part is done in just 0.25 seconds.
P.S. Thanks to Nicolas Guillemot for suggestion on memory-mapping files.