Fast Iteration of Spaced k-mers
This work addresses performance bottlenecks in high-performance bioinformatics applications, enabling faster processing of sequence data.
The paper tackled the problem of efficiently extracting spaced k-mers from nucleotide sequences by developing methods based on CPU-level bit manipulation, resulting in up to an order of magnitude faster performance and a throughput of up to 750MB per second per core.
We present efficient approaches for extracting spaced k-mers from nucleotide sequences. They are based on bit manipulation instructions at CPU level, making them both simpler to implement and up to an order of magnitude faster than existing methods. We further evaluate common pitfalls in k-mer processing, which can cause major inefficiencies. Combined, our approaches allow the utilization of spaced k-mers in high-performance bioinformatics applications without major performance degradation, offering a throughput of up to 750MB of sequence data per second per core. Availability: The implementation in C++20 is published under the MIT license, and freely available at https://github.com/lczech/fisk