LONDON – Up to a million ARM processor cores are going to be linked together to simulate the workings of the human brain in a research project in the U.K. Chips, designed at Manchester University and manufactured in Taiwan, form the building blocks for a massively parallel computer called SpiNNaker (Spiking Neural Network architecture). The specialized chips, based on an old ARM instruction set architecture, were delivered to the university last month where they have subsequently passed functionality tests.
SpiNNaker is a joint project between the universities of Manchester, Southampton, Cambridge and Sheffield and has been funded with a £5 million (about $8 million) government grant. Professor Steve Furber of the University of Manchester has been studying brain function and architecture for several years, but is also well known as one of the co-designers of the Acorn RISC Machine, a microprocessor that is the forerunner of today's ARM processor cores.
"We have small simulations running now, and will be scaling up over the next 18 months," said Professor Furber.
There are about 100 billion neurons with 1,000 trillion connections in the human brain. Even a machine with one million of the specialized ARM processor cores developed at Manchester would only allow modeling of about 1 percent of the human brain, the researchers said.
Neurons in the brain transmit information as analog electrical spikes. In the SpiNNaker machine these will be modeled as packets of descriptive data. The neuronal processing of these spikes is then run as models or virtual neurons running on the ARM processors. The architecture and use of packetized digital data means that SpiNNaker can transmit spikes as quickly as the brain with many fewer physical connections.
An original test chip was designed by Professor Furber's team in 2009 but the latest implementation includes 18 ARM processors per silicon die which come packaged with a memory die and have a power budget of about one watt. The chip has been manufactured by UMC (Hsinchu, Taiwan) in 130-nm CMOS. It has a complexity of about 100 million transistors although this is mainly in 55 32-kbyte SRAM blocks distributed across the die, Professor Furber said.
The accompanying memory die is a 1-Gbit DDR SDRAM from Micron Technology Inc. (Boise, Idaho) that operates at up to 166-MHz. These were sourced as known good die and then had packaged with the SpiNNaker ARM die in a 300-BGA package, Professor Furber said.
"We don't know how the brain works as an information-processing system, and we do need to find out. We hope that our machine will enable significant progress towards achieving this understanding," said Professor Furber, in a statement.
ARM has been supporting the SpiNNaker project since it was approached in 2005 by providing its processor and physical IP to the team.
All this to attempt to replicate the functions of a 3-lb (1.4 kg) brain that dissipates 50 watts--think about that.
And it still won't be able to work out most things which the brain does.
"We don't know how the brain works as an information-processing system, and we do need to find out." Steve Furber could have reduced his ignorance by studying some of the research of Walter Freeman :
Dr Freeman's work does not support the view that the brain processes information.
1% of brain with 1 million ARM cores is good. But how about memory? Does human brain have much more memory? Also, other part is learning, decision making and various moods of human. That will be interesting part of it.
This simulation will find out how the brain processes the information. It will be also interesting how the memory works. Because the human memory also seems to have an unlimited capacity and almost instantaneous searching speed ( many times it will beat Google!)
David Patterson, known for his pioneering research that led to RAID, clusters and more, is part of a team at UC Berkeley that recently made its RISC-V processor architecture an open source hardware offering. We talk with Patterson and one of his colleagues behind the effort about the opportunities they see, what new kinds of designs they hope to enable and what it means for today’s commercial processor giants such as Intel, ARM and Imagination Technologies.