Scientists squeeze more than 1,000 cores on to computer chip
(PhysOrg.com) -- Scientists at the University of Glasgow have created an ultra-fast 1,000-core computer processor.
The core is the part of a computers central processing unit (CPU) which reads and executes instructions. Originally, computers were developed with only one core processor but, today, processors with two, four or even sixteen cores are commonplace.
However, Dr Wim Vanderbauwhede and colleagues at the University of Massachusetts Lowell have created a processor which effectively contains more than a thousand cores on a single chip.
To do this, the scientists used a chip called a Field Programmable Gate Array (FPGA) which like all microchips contains millions of transistors the tiny on-off switches which are the foundation of any electronic circuit.
FPGAs can be configured into specific circuits by the user, rather than their function being set at a factory, which enabled Dr Vanderbauwhede to divide up the transistors within the chip into small groups and ask each to perform a different task.
By creating more than 1,000 mini-circuits within the FPGA chip, the researchers effectively turned the chip into a 1,000-core processor each core working on its own instructions.
The researchers then used the chip to process an algorithm which is central to the MPEG movie format used in YouTube videos at a speed of five gigabytes per second: around 20 times faster than current top-end desktop computers.
Dr Vanderbauwhede said: FPGAs are not used within standard computers because they are fairly difficult to program, but their processing power is huge while their energy consumption is very small because they are so much quicker so they are also a greener option.
While most computers sold today now contain more than one processing core, which allows them to carry out different processes simultaneously, traditional multi-core processors must share access to one memory source, which slows the system down.
The scientists in this research were able to make the processor faster by giving each core a certain amount of dedicated memory.
Dr Vanderbauwhede, who hopes to present his research at the International Symposium on Applied Reconfigurable Computing in March 2011, added: This is very early proof-of-concept work where were trying to demonstrate a convenient way to program FPGAs so that their potential to provide very fast processing power could be used much more widely in future computing and electronics.
While many existing technologies currently make use of FPGAs, including plasma and LCD televisions and computer network routers, their use in standard desk-top computers is limited.
However, we are already seeing some microchips which combine traditional CPUs with FPGA chips being announced by developers, including Intel and ARM.
I believe these kinds of processors will only become more common and help to speed up computers even further over the next few years.
Provided by University of Glasgow
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Jan 04, 2011
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Jan 04, 2011
Rank: 5 / 5 (2)
Multithreaded programming often addresses this by using mutexes, but the mutex itself is only necessary if your code is not properly designed. This really just means that people will have to think about their software a bit more and do more planning, at least until an abstraction language like java is created to handle and verify integrity for the programmer.
I can definitely see fpga programming being handled in a more automated and emergent manner, possibly even modeled after how neurons in the brain program themselves. Neurons and fpga's do have some striking similarities depending on how you are using the fpga.
Jan 04, 2011
Rank: 1.8 / 5 (4)
When I was discussing A.I. with FBM, I described a concept of having a multi-core network capable of re-configuring it's own connectivity among the cores facilitated by nano-scale robotic arms to re-work wiring, etc.
Of course, true to form, FBM insisted nothing like this would ever be possible.
Jan 04, 2011
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Jan 04, 2011
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Jan 04, 2011
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The reason why we generally don't use FPGAs for general purpose computing is that you rarely need to re-configure a chip in a product. They're mainly used for research and developement, and one-off special products like in industrial automation where making just one regular ASIC chip would cost too much (because you need to make ten thousand of them to turn a profit).
In a product like a set-top-box, you can take the circuit that was put into the FPGA and remove all the scaffolding required for programmability and turn it into an ASIC. That makes it even faster and even more energy-efficient, and cheaper.
(ASIC= Application Specific Integrated Circuit)
Jan 04, 2011
Rank: 5 / 5 (3)
So you have a limited number of times that you can re-draw the circuit that the chip is emulating. After that it bricks.
Jan 04, 2011
Rank: 5 / 5 (3)
FPGA's are cheaper that ASIC's for small to medium quantities (up to runs of about 100k parts). This is because ASIC's cost millions in up front cost, while FPGA's do not. However ASIC's are much cheaper to produce once they are designed, have far more gates, and run up to 10x faster (or 10x less power). So...
FPGA's are perfect for proof of concept. ASIC's are better for mass produced consumer products. This is an example where FPGA's absolutely have the advantage.
Jan 04, 2011
Rank: 4 / 5 (1)
See "The surprising usefulness of sloppy arithmetic"
And the post that I made several hours ago (awaiting moderation for that link) was essentially Parsec's points, in somewhat less detail :)
Jan 04, 2011
Rank: 4.5 / 5 (2)
The point being, that if you imagine a computer that reconfigures its circuitry to suit the task, you will quickly run out of erase cycles on a typical FPGA chip.
A modern multitasking processor changes "context", i.e. the program it operates on, several hundred or thousand times a second, and there's a hundred different programs running at any given time. Even if you didn't have the erase cycle limitations of flash memory, the FPGA circuitry can't keep up re-programming to optimize itself for different tasks, and that will negate the benefit of being able to change the circuitry.
It only works if you're running one program at a time, but in such cases you almost never have to change the program.
Jan 04, 2011
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Jan 05, 2011
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The issue with large FPGAs is cost. 75% of the die area in an FPGA is dedicated to programmed connections, so a hard-wired ASIC will always be smaller, faster, and consume less power. The ASIC will also be cheaper *IF* the production run is large enough to offset the custom design cost.
Jan 05, 2011
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Jan 07, 2011
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I don't know, I can imagine an FPGA being used in small devices to decode video, then maybe reconfigure to do some UI processing, then maybe reconfigure to do so BOINC computing while your device charges, then maybe reconfigure to do some 3D computations for a game.