brain simulation
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project report tiger
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Joined: Feb 2010
01-03-2010, 10:43 PM

(1)Relevance of Seminar:
Scientists and engineers at IBMâ„¢s Almaden Research Center, in San Jose, Calif., announced at the Supercomputing Conference (SC09) in Portland, Ore., that they have created the largest brain simulation to date on a supercomputer. The number of neurons and synapses in the simulation exceed those in a catâ„¢s brain; previous simulations have reached only the level of mouse and rat brains. Experts predict that the simulation will have profound effects in two arenas: It will lead to a better understanding of how the brainâ„¢s architecture leads to cognition, and it should inspire the design of electronics that mimic the brainâ„¢s as-yet-unmatched ability to do complex computation and learn using a small volume of hardware that consumes little power.
The cortical simulator, called C2, integrates research from the fields of computation, computer memory, communication, and neuroscience to re-create 1 billion neurons connected by 10 trillion individual synapses. C2 runs on Dawn, a BlueGene/P supercomputer at Lawrence Livermore National Laboratory, in Livermore, Calif.
The research was funded by the U.S. Defense Advanced Research Projects Agency (DARPA), which is spending at least US $40 million to develop an electronic processor that mimics the mammalian brainâ„¢s function, size, and power consumption. The DARPA project and implimentation, called Systems of Neuromorphic Adaptive Plastic Scalable Electronics, or SyNAPSE, is an applied physics endeavor that seeks to cherry-pick only the most useful elements of the brain, was launched late last year and will continue until 2015 with a goal of a prototype chip simulating 10 billion neurons connected via 1 trillion synapses. The device must use 1 kilowatt or less (about what a space heater uses) and take up less than 2 liters in volume. IBM is one of three groups involved in the project and implimentation.
Real brains are so impressive to computer scientists, says Jim Olds, a neuroscientist who directs George Mason Universityâ„¢s Krasnow Institute. Instead of banging our heads against Mooreâ„¢s Law, why not build computers more like the brain and get them to solve problems the way the brain does? Right now, Roadrunner, the supercomputer that comes closest to replicating a humanâ„¢s ability to drive in rush-hour traffic, weighs 227 metric tons and requires a diet of about 3 megawatts. By contrast, the brain regularly handles rush-hour driving on 20 watts, and its 1.5 kilograms fit neatly into a handbag.IBMâ„¢s principal investigator for SyNAPSE, Dharmendra Modha, likens the C2 cortical simulator to an electron microscope or a linear accelerator. Itâ„¢s a tool that other scientists can now use to better understand how cognition works, he says.Each neuron in the network is a faithful reproduction of what we now know about neurons. This in itself is an enormous step forward for neuroscience, but it also allows neuroscientists to do what they have not previously been able to do: rapidly test their own hypotheses on an accurate replica of the brain.
The IBM research shows that a model of the human brain”which has 20 billion neurons connected by about 200 trillion synapses”could be reached by 2019, given enough processing power. But Johns Hopkins University electrical and computer engineering professor Andreas Andreou says the C2 simulator underscores an undeniable fact”to better understand the brain, we™re going to need a better computer.
A major problem is power consumption. Dawn is one of the most powerful and power-efficient supercomputers in the world, but it takes 500 seconds for it to simulate 5 seconds of brain activity, and it consumes 1.4 MW. Extrapolating from todayâ„¢s technology trends, IBM project and implimentations that the 2019 human-scale simulation, running in real time, would require a dedicated nuclear power plant.
The human brain offers tantalizing clues to a better computer architecture. For example, today™s microprocessors separate memory and computation. The brain has no such constraints, and its circuits are reconfigurable, specialized, and fault tolerant, too. This makes the human brain much better at recognizing faces and driving a car, to take two examples, than the world™s most sophisticated supercomputers. DARPA™s Urban Challenge, which required contestants to develop an autonomous vehicle control system, proved this point. The Urban Challenge went off the rails faster than anyone expected, with cars idling indefinitely at stop signs or becoming paralyzed by large rocks.While Andreou, who studies chip architectures for specialized problems, is generally a skeptic about efforts to reverse engineer the brain, what Modha and his team have done is quite good, he says. The most interesting thing about the IBM research, Andreou says, is what it bodes for computer architecture”it points to a future of far more specialized electronics.
The way to get to large-scale computing”like a brain simulation or genomics”is to use a specialized chip that will solve a specific class of problems very well. That™s why this work is exciting: It gives a lot of really scientific data to actually design such processors.Modha says the next step is to demonstrate brainlike visual perception, decision making, planning, and navigation in virtual environments by mimicking how the brain interfaces with sensory organs and with muscles.In the final phase, it plans to build a system of 100 such chips simulating 100 million neurons and 1 trillion synapses.

(2)Idea of the Seminar:
IBM Biggest Brain Simulator consists of following features:
1.Uses Dawn, BlueGene/P supercomputer
2.Uses C2 cortical simulator
3.Funded by DARPA (U.S. Defense Advanced Research Projects Agency)
spended 40 million US dollars
4.Consumes 1.4 MW
5.Uses 10 rows of racks (and miles of cables)
6.Uses 6,675 tons of air-conditioning equipment spouting 2.7 million cubic feet of chilled air
7.Uses a universal neural circuit called a microcolumn to mimic a single neuron.
8.Exceed cat's brain capability
9.Can simulate only human visual cortex capability
10.Takes 500 seconds to simulate 5 seconds of real mammal's brain activity (in average).

(3)Innovative Points in the Seminar:
(a) With this technology, to exceed human brain, the supercomputer will need between 100 MW and 1 GW. It takes a nuclear power plant for simulating only a single human brain. The real human brain takes only 20 watts.
(b)Brainlike chips are to be created for the purpose of brain simulation which can manage in thinking power.
©The brain simulator consists of 147,456 processors and 147TB of RAM which determines the tremendous speed of the supercomputer to solve any complex problems.
1.Brain simulation can increase the thinking power of computers and can search for the various technologies without taking any commands from human.
2.Various machines can be produced at the faster speed without any bugs in them.The efficiency of these machine will be extremely good as it is created by the thinking power of human and computers.
3.The stress created on human brain due many of the technical creations can be reduced to the great extent.No one can challenge the computers because they will be humans in the machine form.

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