Story image

Toshiba develops a high-speed algorithm for deep learning processors

07 Nov 2018

Toshiba Memory Corporation announced the development of a high-speed and high-energy-efficiency algorithm and hardware architecture for deep learning processing with fewer degradations of recognition accuracy. 

The new processor for deep learning implemented on an FPGA achieves four times energy efficiency compared to conventional ones. 

Deep learning calculations generally require large amounts of multiply-accumulate (MAC) operations, and it has resulted in issues of long calculation time and large energy consumption. 

Although techniques reducing the number of bits to represent parameters (bit precision) have been proposed to reduce the total calculation amount, one of proposed algorithm reduces the bit precision down to one or two bit, those techniques cause degraded recognition accuracy. 

Toshiba Memory developed the new algorithm reducing MAC operations by optimising the bit precision of MAC operations for individual filters in each layer of a neural network. 

By using the new algorithm, the MAC operations can be reduced with less degradation of recognition accuracy.

Furthermore, Toshiba Memory developed a new hardware architecture, called the bit-parallel method, which is suitable for MAC operations with different bit precision. 

This method divides each various bit precision into a bit one by one and can execute 1-bit operation in numerous MAC units in parallel. 

It significantly improves the utilisation efficiency of the MAC units in the processor compared to conventional MAC architectures that execute in series.

Toshiba Memory implemented ResNet50, a deep neural network, on an FPGA using the various bit precision and bit-parallel MAC architecture. 

In the case of image recognition for the image dataset of ImageNet, the above technique supports that both operation time and energy consumption for recognising image data are reduced to 25 % with less recognition accuracy degradation, compared to conventional method.

Artificial intelligence (AI) is forecasted to be implemented in various devices. The developed high-speed and low-energy-consumption techniques for deep-learning processors are expected to be utilised for various edge devices like smartphones and HMDs and data centres which require low energy consumption. 

High-performance processors like GPU are important devices for high-speed operation of AI. 

Memories and storages are also one of the most important devices for AI which inevitably use big data. 

Toshiba Memory Corporation is continuously focusing on research and development of AI technologies as well as innovating memories and storages to lead data-oriented computing.

How Renesas aims to simplify building automation
“With the trend toward energy efficiency and green design of commercial buildings, the challenge of renovating existing facilities is growing."
Katalyst to build new subsurface data centre in Malaysia
The company plans to open a subsurface data centre in Kuala Lumpur to support its oil and gas customers.
Infinera launches new ‘disruptive’ network architecture
The new end-to-end network architecture is said to enable instantly scalable, self-optimizing networks that adapt to the demands of specific users and applications.
Survey finds DC managers want more efficiency, not horsepower
More servers and more CPU power used to be the answer to boosting data centre performance, but it appears this is no longer the case.
NEC to build submarine cable connecting Japan prefectures
NEC Corporation announced that it has been awarded a major new submarine cable contract.
DOCOMO ranked world's top mobile operator in 5G SEP applications
NTT DOCOMO has been ranked the world's leading mobile operator in terms of applications for candidate standard-essential patents.
Exclusive: Ping Identity on security risk mitigation
“Effective security controls are measured and defined by the direct mitigation of inherent and residual risk.”
Nlyte celebrates record year and new board chairman
The company recently announced a strong 2018 calendar year after adding more new customers than any other year in its 15-year history.