Shedding light on the era of 'dark silicon'

September 7, 2015, Lancaster University

Researchers at Lancaster University are racing against time to find smart solutions to the rapidly advancing era of 'dark silicon'.

We will soon live in an era where perhaps more than 80 per cent of computer processors' transistors must be powered off  and 'remain dark' at any time to prevent the chip from overheating.

Hardware design is rapidly evolving to prevent this need to 'power down' transistors and coming up with innovative solutions. But these improvements at level bring with them complexities which are tricky for compilers to contend with. Unless we can find ways of helping compilers keep pace with these hardware changes they will no longer be able to efficiently translate high-level programming language or source code used by into the machine code that computer hardware understands.

Until this problem is solved, the software industry will stagnate; software will no longer be able to communicate efficiently with hardware and efforts to resolve the dark silicone problem will have been in vein.

Thanks to a £98,000 Engineering and Physical Sciences Research council grant, researchers at Lancaster University are now working on new 'smart' compilers which use machine learning to self-educate and find more efficient ways of doing their job as the middle man between software and hardware.  

Zheng Wang, Lecturer at Lancaster University's School of Computing and Communications, said: "Software developers are struggling to cope with this dramatic increase in hardware complexity and the current tools are simply inadequate to the task.  If we are unable to solve these problems then for the first time in decades, progress in the software industries will stagnate.

"Our project aims to provide enabling techniques at compiler-level using machine learning.

"Traditional compiler construction approaches that rely on human experts to spend many years on building an efficient compiler are no longer feasible. The new, emerging complex architecture of the hardware means it will take much longer time to build a decent compiler

"For the first time, will live in the application environment, learning how to optimise programs for individual computing devices. Our smart compilation system will acquire knowledge each time a program is compiled and run, and use the knowledge to learn how to optimise programs for each hardware platform and for each user. The more our system learns, the more it knows what works. Over time, programs will run faster and the entire computing system will become more energy efficient."

Explore further: Machine-learning revolutionises software development

Related Stories

Better software cuts computer energy use

December 18, 2014

An EU research project is developing tools to help software engineers create energy-efficient code, which could reduce electricity consumption at data centres by up to 50% and improve battery life in smart devices.

Software tool helps tap into the power of graphics processing

May 17, 2010

Today's computers rely on powerful graphics processing units (GPUs) to create the spectacular graphics in video games. In fact, these GPUs are now more powerful than the traditional central processing units (CPUs) - or brains ...

Massive chip design savings to be realized

January 22, 2015

IT researchers working at the University of Twente have developed a programming language making the massive costs associated with designing hardware more manageable. Chip manufacturers have been using the same chip design ...

Recommended for you

Electrode shape improves neurostimulation for small targets

April 24, 2018

A cross-like shape helps the electrodes of implantable neurostimulation devices to deliver more charge to specific areas of the nervous system, possibly prolonging device life span, says research published in March in Scientific ...

China auto show highlights industry's electric ambitions

April 22, 2018

The biggest global auto show of the year showcases China's ambitions to become a leader in electric cars and the industry's multibillion-dollar scramble to roll out models that appeal to price-conscious but demanding Chinese ...

After Facebook scrutiny, is Google next?

April 21, 2018

Facebook has taken the lion's share of scrutiny from Congress and the media about data-handling practices that allow savvy marketers and political agents to target specific audiences, but it's far from alone. YouTube, Google ...

Robot designed for faster, safer uranium plant pipe cleanup

April 21, 2018

Ohio crews cleaning up a massive former Cold War-era uranium enrichment plant in Ohio plan this summer to deploy a high-tech helper: an autonomous, radiation-measuring robot that will roll through miles of large overhead ...

How social networking sites may discriminate against women

April 20, 2018

Social media and the sharing economy have created new opportunities by leveraging online networks to build trust and remove marketplace barriers. But a growing body of research suggests that old gender and racial biases persist, ...

0 comments

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.