When I use BWA(version 0.7.15-r1140), I select the BWA-MEM algorithm and here is my command:

`bwa mem -t 2 reference_file fastq1.fq.gz fastq2.fq.gz > result1.sam`

This works well and then I use this command to improve the threads:

`bwa mem -t 10 reference_file fastq1.fq.gz fastq2.fq.gz > result2.sam`

This also works well but when I compare the result1.sam with result2.sam, they are different! I also test with `-t 6, -t 16`, and all the results are different. However, when I run with the same threads twice, the results are identical. So I found that BWA-MEM will get different results with different threads.  

Then I read the source code and found this:

    kt_for(opt->n_threads, worker1, &w, (opt->flag&MEM_F_PE)? n>>1 : n); // find mapping positions
	    for (i = 0; i < opt->n_threads; ++i) smem_aux_destroy(w.aux[i]);
    free(w.aux);
    if (opt->flag&MEM_F_PE) { // infer insert sizes if not provided
        if (pes0) memcpy(pes, pes0, 4 * sizeof(mem_pestat_t));
        else mem_pestat(opt, bns->l_pac, n, w.regs, pes);
    }
    kt_for(opt->n_threads, worker2, &w, (opt->flag&MEM_F_PE)? n>>1 : n);

That is, BWA-MEM use n_threads(such as -t 6, n = 6) to find mapping positions, but use only 1 thread to execute the function `mem_pestat` to calculate `avg`(average of the insert size) and `std`(standard deviation of the insert size), which are important to find pair information. According to BWA, every thread will process around 10000000bp, so:

If I use -t 2, BWA will calculate avg and std with 2 x 10000000bp

If I use -t 10, BWA will calculate avg and std with 10 x 10000000bp

If I use -t 16, BWA will calculate avg and std with 16 x 10000000bp

So I know why the results are different with different threads.

I wonder to know if there is anything wrong with my opinion? If it's correct, I want to know how to evaluate the difference? The difference will change which filed of the SAM record( such as RNAME or POS)? If it's wrong, I want to know the real reason to make the difference.

Any reply will be much appreciated!
> I wonder to know if there is anything wrong with my opinion?

Well, no, not really.  Everyone wants correct and reproducible results...

But in this case, you can't have correct and reproducible results.  The problem is, you can't have correct results.  The insert size estimate depends on read order, and read order is random.  There's no way accurately claim "My estimate using the first 10000 reads is better than using 5 threads with 2000 reads each", or whatever.

For N reads, there are N! orderings.  Even if it took a nanosecond to evaluate the best insert size for a given read ordering, it's still impossible for even 100 reads, to determine the optimal order or optimal insert size, in a system where the insert size affects mapping.  I think bwa's approach of using multiple threads to refine the estimate is pretty good.

BBMap uses continuous refinement of insert-size estimation, so for an infinitely-long file with uniform insert-size distribution, it will converge on the correct answer.  This approach is more robust to scenarios in which the first 1m reads happen to be junk, which is a chronic occurrence on some platforms.  But, that makes it even more nondeterministic than bwa.

I think, if you want the best results from mapping modern sequence output in a usable timeframe, you will have to accept nondeterministic software.
