20161021
This reference describes MUMmerGPU.
| PMID | PMID 20161021 |
|---|---|
| Title | Optimizing Data Intensive GPGPU Computations for DNA Sequence Alignment |
| Year | 2009 |
| Journal | Parallel Comput |
| Author | Trapnell C, Schatz MC |
| Volume | |
| Start page |
Error: No contents found at URL http://www.ebi.ac.uk/europepmc/webservices/rest/MED/20161021/citations/4000.
According to Europe PubMed Central, this reference has Error: no local variable "citations" was set. " Error: no local variable "citations" was set. " is not a number. citations.
For reference, you can check Google Scholar, which lacks an API because Google ...
Error: Invalid JSON. According to Almetric, this reference has an Altmetric score of Error: no local variable "altscore" was set. " Error: no local variable "altscore" was set. " is not a number..
Full text description
MUMmerGPU uses highly-parallel commodity graphics processing units (GPU) to accelerate the data-intensive computation of aligning next generation DNA sequence data to a reference sequence for use in diverse applications such as disease genotyping and personal genomics. MUMmerGPU 2.0 features a new stackless depth-first-search print kernel and is 13× faster than the serial CPU version of the alignment code and nearly 4× faster in total computation time than MUMmerGPU 1.0. We exhaustively examined 128 GPU data layout configurations to improve register footprint and running time and conclude higher occupancy has greater impact than reduced latency. MUMmerGPU is available open-source at http://mummergpu.sourceforge.net
