|Source: BGI OSS|
BGI's announcement indicates that at least two key parts of the analysis process can be tackled with GPUs. Alignment, where the billions of sequence fragments generated by the sequencing instrument are matched up to a known genome, is typically one of the first steps in analysis and represents a non-trivial portion of the overall workload. Further into analysis, there can be the need to identify single variations or SNPs, and BGI was also successful in applying GPU technology to this problem. But as the Wired article points out, these are only two of the dozens of steps in the analysis process, and so it's really too early to make any major claims about the potential for GPUs to revolutionize genomics analysis end-to-end.
While somewhat overshadowed by the nVidia announcement, FPGA approaches also recently took a step forward with Pico's announcement at PAG XX of their success in applying their technology to the BFAST sequence alignment algorithm. They are reporting orders of magnitude improvements in performance, as well as improved alignment accuracy.
These technologies bear careful watching as they hold the promise of improving the performance of genetic analysis and reducing the cost of the technology and data center facilities required to handle the onslaught of genetic sequence data.
UPDATE 1/13: Looks like there was another FPGA announcement at PAG XX, this one from CLC Bio and Sciengines. They are reporting similar orders-of-magnitude performance improvements running BLAST and Smith-Waterman alignment algorithms.