Synthetic Cognition at Los Alamos
The synthetic cognition group at Los Alamos National Laboratory is building supercomputer simulations of the human visual system. They are using IBM Roadrunner - a petaflop supercomputer which was the world's fastest when built in 2008 - as well as various other GPU-accelerated multi-teraflop machines. The simulations are not highly biologically detailed, but nor are they as trivial as standard artificial neural networks. Instead they strike a balance at a level of complexity thought to be sufficient to reproduce the function and behaviour of natural nervous systems.
The simulations are built using custom software written in C, C++, and Python. Running at a peak of 1.14 PFLOPS they have simulated the primate visual system including the retina, LGN, and visual cortex areas V1, V2, and V4. The models are trained to visually recognise objects such as enemy vehicles on a battlefield - a possible application being their use in military UAVs. The research aims to prepare for the time when supercomputers become sufficiently powerful to simulate an entire human brain.
Research details
The goal of this resarch is to understand the computational principles of high-level sensory processing and cognition in the human brain. This is to be achieved by using a petascale supercomputer to create a synthetic cognition system that emulates the functional neural architecture of the primate visual cortex.
Complete physiological realism is not the goal. It is attempted only to the extent that is needed for understanding neural computation and for solving complex information processing tasks. The cortical models fall between the traditional (and over-simplified) artificial neural networks and biologically-inspired cellular and molecular descriptions.
A petascale supercomputer is considered sufficiently powerful based on the following calculation:
- There are ~10 billion neurons in the human visual cortex
- Each neuron recieves ~10,000 synaptic inputs
- Each synapse requires ~10 FLOPS based on a 1 Hz firing rate
- Thus: ~10 G neurons x 10 K synapses x 10 FLOPS = 1 PFLOP
The IBM Roadrunner supercomputer at LANL fullfills this requirement with its 1.7 PFLOP peak capability. The neural network model achieved computation speeds of 1.14 PFLOPS in 2008 - a world speed record for scientific computation at the time, and the first to break the petaflop barrier. In the future, when exascale supercomputers become available, it should be possible to build simulations that match the scale of the complete human brain.
The synthetic cognition team have developed a completely new methodology for neural computation and a novel software architecture for emulating cortical columns. It is not based on Michael Hines' NEURON, as is the case with many other biologically-inspired simulations. The model enables petascale simulation of the mammalian visual system, including the retina, LGN, and the visual cortex ventral pathway V1 -> V2 -> V4 -> IT. It uses a hierarchical feed-forward architecture in the family of Neocognitron and HMAX models.
The model implements the following features:- Spiking dynamics
- Conductance-based leaky integrate and fire neurons.
A neuron spikes when the membrane potential exceeds a threshold.
Excitatory and inhibitory synaptic input modifies the associated conductance.
- Lateral connectivity and feedback loops
- 80% of cortical synapses are lateral connections and feedback connections from higher visual cortex areas.
- Spike-timing-dependent plasticity (STDP) - Causal pairing of a pre- and post-synaptic spikes (i.e. input precedes output) strengthens synapses. Acausal pairing decreases it.
News / current status
Most recent research paper, published September 2011: Petascale visual cortex models and object detection
IBM Roadrunner
Roadrunner is a supercomputer built by IBM at the Los Alamos National Laboratory in New Mexico, USA. It was the world's fastest supercomputer when it first went live in mid-2008. As of November 2011 it is ranked the world's 10th fastest. It has a peak performance of 1.7 PFLOPS.
The supercomputer is one of a kind, custom built from off-the-shelf parts at a cost of $133 million. It occupies ~560 m2 of floor space. The hybrid design uses two different types of processors, as follows:
- 12,960 x IBM PowerXCell 8i CPUs (116,640 cores)
- 6,912 x AMD Opteron dual-core processors (13,824 cores)
- Total: 130,464 cores (both computing and operation nodes)
Roadrunner is used by the DOE to analyse the safety of the USA's aging arsenal of nuclear weapons. It is also by the science, financial, automotive, and aerospace industries.
- lanl.gov/roadrunner - the homepage
- IBM Roadrunner - info on Top500.org
- Look inside the world's fastest supercomputer - some photos
Los Alamos
Los Alamos National Laboratory (LANL) is a US Department of Energy (DOE) national laboratory, located in Los Alamos, New Mexico. It is one of the largest science and technology institutions in the world. The lab conducts multidisciplinary research in fields such as national security, space exploration, renewable energy, medicine, nanotechnology, and supercomputing. It receives $2.2 billion in annual funding and employs ~9,000 staff and ~700 students.
Funding
Funding for this research comes from a $6 million R&D investment made in ~2009 by DOE/LANL, NSF, and DARPA.
The National Science Foundation (NSF) awarded $1,168,982 (award no. NSF-OCI-0749348) in May 2008 with an estimated expiry date of April 2012.
Details of the DOE/LANL and DARPA awards are unknown.
People involved
Craig Rasmussen  Technical staff member | Cristina Rinauldo Student research assistant | Cyrus Omar   PhD student | ||
| Garrett Kenyon Co-principal investigator | Ilya Nemenman Collaborator | John George Co-principal investigator | ||
| Karissa Sanbonmatsu | Luís Bettencourt Principle investigator | Marian Anghel Technical staff member | ||
Melanie Mitchell  Collaborator | Michael Ham Postdoc research assistant | Mick Thomure PhD student | ||
| Peter Loxley Postdoc research assistant | Shawn Barr Student research assistant | Steven Brumby | ||
| Tsvi Achler Postdoc research assistant | Vadas Gintautas Collaborator | Will Landecker PhD student | ||
| Zhengping Ji Postdoc research assistant |
Research papers
- Petascale visual cortex models and object detection - published September 2011
- Cortical association fields and contour perception - submitted February 2011, published July 2011
- Visual cortex on a chip (slides) - poster displayed September 2010
- Further list of publications - from the synthetic cognition homepage
Weblinks
- Homepage: synthetic-cognition.lanl.gov
