A team of
international scientists have found a way to make memory chips perform
computing tasks, which is traditionally done by computer processors like those
made by Intel and Qualcomm.
This means data
could now be processed in the same spot where it is stored, leading to much
faster and thinner mobile devices and computers.
This new computing
circuit was developed by Nanyang Technological University, Singapore (NTU
Singapore) in collaboration with Germany's RWTH Aachen University and
Forschungszentrum Juelich, one of the largest interdisciplinary research centers
in Europe.
It is built using
state-of-the-art memory chips known as Redox-based resistive switching random
access memory (ReRAM). Developed by global chipmakers such as SanDisk and
Panasonic, this type of chip is one of the fastest memory modules that will
soon be available commercially.
However, instead of
storing information, NTU Assistant Professor Anupam Chattopadhyay in
collaboration with Professor Rainer Waser from RWTH Aachen University and Dr
Vikas Rana from Forschungszentrum Juelich showed how ReRAM can also be used to
process data.
This discovery was
published recently in Scientific Reports.
Current devices and
computers have to transfer data from the memory storage to the processor unit for
computation, while the new NTU circuit saves time and energy by eliminating
these data transfers.
It can also boost
the speed of current processors found in laptops and mobile devices by at least
two times or more.
By making the memory
chip perform computing tasks, space can be saved by eliminating the processor,
leading to thinner, smaller and lighter electronics. The discovery could also
lead to new design possibilities for consumer electronics and wearable
technology.
How the new circuit
works
Currently, all
computer processors in the market are using the binary system, which is
composed of two states -- either 0 or 1. For example, the letter A will be
processed and stored as 01000001, an 8-bit character.
However, the
prototype ReRAM circuit built by Asst Prof Chattopadhyay and his collaborators
processes data in more than just two states. For example, it can store and
process data as 0, 1, or 2, known as a ternary number system.
Because ReRAM uses
different electrical resistance to store information, it could be possible to
store the data in an even higher number of states, hence speeding up computing
tasks beyond current limitations.
Asst Prof
Chattopadhyay who is from NTU's School of Computer Science and Engineering,
said in current computer systems, all information has to be translated into a
string of zeros and ones before it can be processed.
"This is like
having a long conversation with someone through a tiny translator, which is a
time-consuming and effort-intensive process," he explained. "We are
now able to increase the capacity of the translator, so it can process data
more efficiently."
The quest for faster
processing is one of the most pressing needs for industries worldwide, as
computer software is getting increasingly complex while data centres have to
deal with more information than ever.
The researchers said
that using ReRAM for computing will be more cost-effective than other computing
technologies on the horizon, since ReRAMs will be available in the market soon.
The excellent
properties of ReRAM like its long-term storage capacity, low energy usage and
ability to be produced at the nanoscale level have drawn many semiconductor
companies to invest in researching this promising technology.
The research team is
now looking to engage industry partners to leverage this important advance of
ReRAM-based ternary computing.
Moving forward, the
researchers will also work on developing the ReRAM to process more than its
current four states, which will lead to great improvements of computing speeds
as well as to test its performance in actual computing scenarios.
Journal Reference:
1.
Wonjoo Kim, Anupam
Chattopadhyay, Anne Siemon, Eike Linn, Rainer Waser, Vikas Rana. Multistate
Memristive Tantalum Oxide Devices for Ternary Arithmetic. Scientific
Reports, 2016; 6: 36652 DOI: 10.1038/srep36652
No comments:
Post a Comment