New “Big Brain Computer” starts at only $30K, but can pack up to 4,096 cores, 64 TB of memory
Renowned physics supergenius and University of Cambridge research director Stephen W. Hawking said something about unlocking the secrets of the Universe as he received the first unit of a computer befitting his smarts — SGI’s “Big Brain Computer”.
I. Meet the “Big Brain Computer”
In an era where supercomputers are slowly gravitating towards brute-force machines pillared by specialized hardware, such as graphics processing unit (GPU) based designs or field-programmable gate arrays (FPGA), many top firms are still focusing a lot of time on a more traditional objective — specialty purpose-built scalable server blades, used to build such juggernauts as International Business Machines, Inc.’s (IBM) iconic Watson.
Another key entrant in this field is Silicon Graphics International Corp. (SGI). SGI was born out of the remains of Silicon Graphics, Inc. a defunct 1990s firm that pioneered the OpenGL standard and designed graphics cards. Today SGI is back at it and thriving, with its newly announced UV2 “Big Brain Computer” tower supercomputer.
Featuring custom-designed server blades, the server is powered by Intel Corp.’s (INTC) Xeon processor E5 line, but is also compatible with NVIDIA Corp.’s (NVDA) Quadro and Tesla cards for GPU computing.
Now the author of The New York Times bestselling A Brief History of Times is receiving the first unit of the new supercomputer. An ecstatic Professor Hawking stated, “I am very pleased to be receiving the first SGI UV 2 supercomputer in the world.
Prof. Hawking will use the UV2 to unlock science mysteries. [Image Source: Martin Pope]
New observations of our Universe, like the Planck satellite, are offering us exquisite new insights. In order to test our mathematical theories, we need to match this detail in our computer simulations. The flexible new UV 2 COSMOS system, soon to be supercharged with Intel’s MIC technology, will ensure that UK researchers remain at the forefront of fundamental and observational cosmology.”
II. Entry Cost of UV2 is “Only” $30K
SGI claims the UV2 has the world’s biggest shared memory system of any supercomputer. It’s scalable up to 4,096 cores and 64 terabytes of memory. The system has a ludicrous peak data rate of 4 terabytes per second. To put that in context, the entire contents of the U.S. Library of Congress only occupy 10 terabytes of space.
But the UV2 isn’t design for simple human literary ponderings. As Professor Hawking suggests, it’s the ideal tool to chew through terabytes of chemical or astrophysical data looking for key correlations, trends, and observed events.
While its specs are intimidating, the system starts at only $30,000 USD for a bare-bones configuration and can run standard desktop apps, in addition to its specialty — scalable multi-core/multi-GPU apps.
Writes SGI, “Users can focus on outcomes, not algorithms with the ability to rapidly innovate; taking analysis from a laptop, scaling up on SGI UV with no re-writing of code or additional data management required.”
Dr. Eng Lim Goh, chief technology officer of SGI, brags that the new system is not only a world-class design — it’s also far cheaper than its predecessor, the UV1. He remarks, “The technological advancement demonstrated in this next-generation SGI UV platform is not simply focused on increasing our lead in coherent memory size and corresponding core count.
We have been able to deliver all of this additional capability while driving down the cost of the system. In fact, the entry-level configuration of SGI UV 2 is 40 percent less expensive than SGI UV 1. This creates a new level of accessibility for large shared memory systems for researchers and the ‘missing middle’, providing an effective lower overall TCO alternative to clusters.”
Paired with genius algorithm and data-mining with scientific expertise like Professor Hawking, designs like the “Big Brain Computer” and “Watson” may indeed change our reality and prospective on the universe as we know it. And that’s good news for all of mankind.