ACADEMIA
Gene Sequencer Breaks $1000 Barrier with NVIDIA GPUs
- Written by: Webmaster
- Category: ACADEMIA
NVIDIA Tesla GPU accelerators are enabling Life Technologies Corporation's new Ion Proton System to accelerate primary genome-sequence analysis – the computation that generates DNA base pairs – by over 16 times. This will dramatically reduce the cost to sequence an entire human genome from about $1 billion a decade ago to $1,000 in the near future.
"GPU acceleration and other advanced Ion Proton features enable every laboratory in the world to take advantage of human genome sequencing quickly and easily, without costly IT investments," said Alan Williams, vice president of software and engineering in the Ion Torrent unit at Life Technologies Corporation. "By democratizing genome sequencing, we expect to see an unprecedented wave of innovation in life sciences and the advancement of clinical research."
The Ion Proton System's technology builds on the rapid advances in increasing throughput, accuracy and read-length achieved with the Life Technologies Ion Personal Genome Machine (PGM) Sequencer, which also uses GPUs to accelerate primary analysis. The Ion PGM sequencer was the first to decode the deadly 2011 E. coli bacteria outbreak in Germany because of its exceptional speed.
Setting new standards for performance, ease of use and affordability, the Ion Proton System enables researchers to rapidly go from multiplex sample sequencing to genome-scale sequencing on a single platform. At one-fifth the cost of light-based genome-scale sequencing systems, it can save researchers hundreds of thousands of dollars.
"GPU acceleration has become pervasive in all aspects of computing for life science applications and will enable research to push the envelope of scientific discovery," said Sumit Gupta, general manager of the Tesla accelerated computing business unit at NVIDIA. "The pace of research has fundamentally been accelerated by the use of GPUs for everything from gene sequencers and sequence analysis to molecular modeling and diagnostic imaging."