Datamation content and product recommendations are
            editorially independent. We may make money when you click on links
            to our partners.  
 
Learn More
   
With the interest in using supercomputing to advance medical science still
on the rise, IBM  said a Japanese research laboratory will
use its Blue Gene/L machine to study proteins, hoping to create better drugs
to treat human diseases.
Big Blue Tuesday said the Tokyo-based Computational Biology Research Center
(CBRC) of The National Institute of Advanced Industrial Science and
Technology (AIST) will use Blue Gene/L to map out 3-D protein structures.
IBM declined to list financial terms of the contract. However, such
supercomputing pacts generally run in the millions of dollars.
William Pulleyblank, director of exploratory server systems at IBM Research,
said his group and AIST are also exploring possible areas for joint research
using software IBM has designed to tackle protein simulations on Blue
Gene/L.
“We launched the Blue Gene project in 1999. At that time if we look at
the challenges of some of these things like protein folding in life
sciences, you’re going to have to do something different with a computer if
you want to attack these, Pulleyblank
told internetnews.com. “We set out to build Blue Gene/L.”
Pulleyblank said when Blue Gene/L is installed in February 2005, the system
will consist of four rack machines, with 1,024 nodes per rack.
It will be based on IBM’s Power architecture and will
run at a peak processing speed of 22.8 teraflops, or trillions of
calculations per second. As of today, this would put it at No. 3 on the Top
500 supercomputing list.
Calling AIST’s choice of Blue Gene/L over other systems “validation that we
are getting this right,” Pulleyblank said the supercomputer will be 24 times
more powerful compared to the CBRC’s current computer systems.
Moreover, it uses about 1/10th the power per computation of and only
about 1/16th the floor space of most systems on the vaunted Top 500 list,
where IBM regularly butts heads with such rivals as SGI ,
Cray , HP , Sun Microsystems  and Dell .
The AIST scientists are also creating high-performance computer applications for
molecular simulation, mass spectrometry analysis, and cell simulation.
Pulleyblank said that to make Blue Gene effective for disease research,
IBM’s researchers became well-versed in how genomes work, as well as the
complex topic of protein folding.
“What happens with proteins is you get things interacting in odd ways or not
behaving properly,” Pulleyblank said. “The first thing researchers try to figure out is why,
and the second thing they try to figure out is how to intervene to make it
stop misbehaving. With machines like Blue Gene we can do
that by studying the atoms that make up these molecules and do a custom
design of a drug that will respond to a specific mutation of a disease.”
IBM Research is getting a lot of mileage out of the Blue Gene project.
Pulleyblank said the Argonne National Laboratory in the United States and Dutch
astronomical group ASTRON will also be installing Blue Gene/L supercomputers
in 2005 to tackle scientific challenges.
Blue Gene/L is also part of the U.S. National Nuclear Security Administration
(NNSA)’s Advanced Simulation and Computing (ASC) Program, which IBM has been a partner of
since 2001. The NNSA will be installing a very large Blue
Gene/L system in 2005 at the Lawrence Livermore National Laboratory to advance understanding
of the behavior of materials.
- 
Ethics and Artificial Intelligence: Driving Greater Equality FEATURE |  By James Maguire,
 December 16, 2020
 
- 
AI vs. Machine Learning vs. Deep Learning FEATURE |  By Cynthia Harvey,
 December 11, 2020
 
- 
Huawei’s AI Update: Things Are Moving Faster Than We Think FEATURE |  By Rob Enderle,
 December 04, 2020
 
- 
Keeping Machine Learning Algorithms Honest in the ‘Ethics-First’ Era ARTIFICIAL INTELLIGENCE |  By Guest Author,
 November 18, 2020
 
- 
Key Trends in Chatbots and RPA FEATURE |  By Guest Author,
 November 10, 2020
 
- 
Top 10 AIOps Companies FEATURE |  By Samuel Greengard,
 November 05, 2020
 
- 
What is Text Analysis? ARTIFICIAL INTELLIGENCE |  By Guest Author,
 November 02, 2020
 
- 
How Intel’s Work With Autonomous Cars Could Redefine General Purpose AI ARTIFICIAL INTELLIGENCE |  By Rob Enderle,
 October 29, 2020
 
- 
Dell Technologies World:  Weaving Together Human And Machine Interaction For AI And Robotics ARTIFICIAL INTELLIGENCE |  By Rob Enderle,
 October 23, 2020
 
- 
The Super Moderator, or How IBM Project Debater Could Save Social Media FEATURE |  By Rob Enderle,
 October 16, 2020
 
- 
Top 10 Chatbot Platforms FEATURE |  By Cynthia Harvey,
 October 07, 2020
 
- 
Finding a Career Path in AI ARTIFICIAL INTELLIGENCE |  By Guest Author,
 October 05, 2020
 
- 
CIOs Discuss the Promise of AI and Data Science FEATURE |  By Guest Author,
 September 25, 2020
 
- 
Microsoft Is Building An AI Product That Could Predict The Future FEATURE |  By Rob Enderle,
 September 25, 2020
 
- 
Top 10 Machine Learning Companies 2021 FEATURE |  By Cynthia Harvey,
 September 22, 2020
 
- 
NVIDIA and ARM: Massively Changing The AI Landscape ARTIFICIAL INTELLIGENCE |  By Rob Enderle,
 September 18, 2020
 
- 
Continuous Intelligence: Expert Discussion [Video and Podcast] ARTIFICIAL INTELLIGENCE |  By James Maguire,
 September 14, 2020
 
- 
Artificial Intelligence: Governance and Ethics [Video] ARTIFICIAL INTELLIGENCE |  By James Maguire,
 September 13, 2020
 
- 
IBM Watson At The US Open: Showcasing The Power Of A Mature Enterprise-Class AI FEATURE |  By Rob Enderle,
 September 11, 2020
 
- 
Artificial Intelligence: Perception vs. Reality FEATURE |  By James Maguire,
 September 09, 2020
 
SEE ALL
ARTICLES