Chinese Lab Speeds Through Genome Processing With GPUs

Eric Smalley writes "The world's largest genome sequencing center once needed four days to analyze data describing a human genome. Now it needs just six hours. The trick is servers built with graphics chips — the sort of processors that were originally designed to draw images on your personal computer. They're called graphics processing units, or GPUs — a term coined by chip giant Nvidia. This fall, BGI — a mega lab headquartered in Shenzhen, China — switched to servers that use GPUs built by Nvidia, and this slashed its genome analysis time by more than an order of magnitude."

Comments

The Future Is Here!!

[mastershake82]

Sounds like these newfangled "GPUs" are gonna change the world.

Re:The Future Is Here!!

[MollyB]

If one reads to page 2 of tfa, they only claim the technique works well in this instance. They go on:

Even for computer-intensive aspects of analysis pipelines, GPUs aren’t necessarily the answer. “Not everything will accelerate well on a GPU, but enough will that this is a technology that cannot be ignored,” says Gollery. “The system of the future will not be some one-size-fits-all type of box, but rather a heterogeneous mix of CPUs, GPUs and FPGAs depending on the applications and the needs of the researcher.”

and

GPUs have cranked up the speed of genome sequencing analysis, but in the complicated and fast-moving field of genomics that doesn’t necessarily count as a breakthrough. “The game changing stuff,” says Trunnell, “is still on the horizon for this field.”

So yes, the article is a bit breathless, but if utilizing GPUs helps cure my potentially impending genetic disorder, I'm all for it.

News for nerds

[Anonymous Coward]

I always wondered what GPUs are. Thanks Slashdot!

Re:News for nerds

[galanom]

No, it's "Guinea Pig Units"

A reminder

[Mannfred]

It's hardly news that GPUs can be used to speed up parallel tasks/computations, but even so this article is a useful reminder of two things; 1) there are still many important processes that can be sped up by using GPUs, and 2) this can be achieved pretty much anywhere in the world.

A better article

[arielCo]

http://hpcwire.com/hpcwire/2011-12-15/bgi_speeds_genome_analysis_with_gpus.html

Excerpt:

At BGI, he says, they are currently able to sequence 6 trillion base pairs per day and have a stored database totaling 20 PB.

The data deluge problem stems from an imbalance between the DNA sequencing technology and computer technology. According to Dr. Wang, using second-generation sequencing machines, genomes can now be mapped 50,000 times faster than just a decade ago. The technology on track to increase approximately 10-fold every 18 months. That is 5 times the rate of Moore's Law, and therein lies the problem.

Obviously it would be impractical to upgrade one's computational infrastructure at that rate, so BGI has turned to NVIDIA GPUs to accelerate the analytics end of the workflow. The architecture of the GPU is particularly suitable for DNA data crunching, thanks to its many simple cores and its high memory bandwidth.

Re:A better article

[Samantha Wright]

...countering this stunning and exciting revelation is BGI's stunning and exciting reputation for producing stunningly and excitingly low-quality raw data from said stunning and exciting second-generation sequencing machines. This is a little like the biology equivalent of being told that your least-favourite Slashdot editor (please pick just one) has just gotten a brain implant so he can spam the front page with dupes, typo-ridden summaries, and fallacy-laden opinion pieces ten times an hour.

Re:This article is almost painfully dumbed down...

[Zakabog]

The summary is pulled directly from the top of the article.

Here's the article from HPC Wire and some details from nvidia as well as the nvidia press release

Re:first

[Pieroxy]

So, a site dedicated to nerds needs to explain what a GPU is? Are we not nerds anymore?

For the curious...

[Cow Jones]

... this is what a Chinese lab looks like.