high performance computing on graphics processing units: hgpu.org

We introduce SneakySnake, a highly parallel and highly accurate pre-alignment filter that remarkably reduces the need for the computationally costly sequence alignment step. The key idea of SneakySnake is to provide fast and highly accurate filtering by reducing the ASM problem to the single net routing (SNR) problem in VLSI chip layout. In the SNR problem, we are interested in only finding the path that connects two terminals with the least routing cost on a special grid layout that contains obstacles. The SneakySnake algorithm quickly and optimally solves the SNR problem and uses the found optimal path to decide whether performing sequence alignment is necessary. We also build two new hardware accelerator designs, Snake-on-Chip and Snake-on-GPU, that adopts modern FPGA and GPU architectures, respectively, to further boost the performance of our algorithm. SneakySnake significantly improves the accuracy of pre-alignment filtering by up to four orders of magnitude compared to the state-of-the-art pre-alignment filters, Shouji, GateKeeper, and SHD. SneakySnake accelerates the state-of-the-art CPU-based sequence aligners, Edlib and Parasail, by up to 37.6x and 43.9x, respectively, without requiring hardware acceleration. The addition of Snake-on-Chip and Snake-on-GPU as a pre-alignment filter reduces the execution time of four state-of-the-art sequence aligners, designed for different computing platforms, by up to 689x (101x on average). To our knowledge, SneakySnake is the only pre-alignment filtering mechanism that works on all modern high-performance computing architectures. Unlike most existing works that aim to accelerate sequence alignment, SneakySnake does not sacrifice any of the aligner capabilities (i.e., scoring and backtracking), as it does not modify or replace the aligner. SneakySnake is freely available online.