Saturday, May 26, 2018
Search
  
Submit your own News for
inclusion in our Site.
Click here...
Breaking News
Google Takes The Lead Over Amazon in Smart Speaker Market
FBI Says Reboot Your Router to Stop Malware Infecting 500k Devices
ASUS Chromebox 3 Series Coming in July
U.S. to Impose Fine, New Management to ZTE to Keep it in Business
Facebook Keeps Working on In-house Chip Designs
AMD Increased GPU Market Share in Q1
Seagate's New VR Power Drive Adds Capacity and Extends Battery Life of the HTC VIVE Focus VR Headset
Samsung Should Pay Apple $539 million in Patent Retrial
Active Discussions
Which of these DVD media are the best, most durable?
How to back up a PS2 DL game
Copy a protected DVD?
roxio issues with xp pro
Help make DVDInfoPro better with dvdinfomantis!!!
menu making
Optiarc AD-7260S review
cdrw trouble
 Home > News > PC Parts > Nvidia:...
Last 7 Days News : SU MO TU WE TH FR SA All News

Friday, April 30, 2010
Nvidia: Moore's Law is Dead


Since we have reached the limit of what is possible with one or more traditional CPUs, the computing industry needs to take the leap into parallel processing, says Bill Dally, chief scientist and senior vice president of research at NVIDIA.

Forty-five years ago this month, Intel co-founder Gordon Moore predicted that the number of transistors on an integrated circuit would double each year (later revised to every 18 months). This laid the groundwork for another prediction: that doubling the number of transistors would also double the performance of CPUs every 18 months.

This bold prediction, known as Moore?s Law, long held true. But we have reached the limit of what is possible with one or more traditional CPUs. The computing industry - and everyone who relies on it for continued improvements in productivity - needs to take the leap into parallel processing. The CPU scaling predicted by Moore?s Law is now dead, according to Nvidia's researcher.

Moore's paper also contained another prediction that has received far less attention over the years. He projected that the amount of energy consumed by each unit of computing would decrease as the number of transistors increased. This enabled computing performance to scale up while the electrical power consumed remained constant. This power scaling, in addition to transistor scaling, is needed to scale CPU performance.

"However, this power scaling has ended. And as a result, the CPU scaling predicted by Moore's Law is now dead. CPU performance no longer doubles every 18 months. And that poses a grave threat to the many industries that rely on the historic growth in computing performance," Dally added.

Dally believes that that there are specific needs that won't be met unless there is a fundamental change in our approach to computing, and identifies parallel computing as the solution. Parallel computing can resurrect Moore's Law and provide a platform for future economic growth and commercial innovation, Dally says.

In parrallel computers, many processing cores, each optimized for efficiency, not serial speed, work together on the solution of a problem.

"A fundamental advantage of parallel computers is that they efficiently turn more transistors into more performance," Dally says. "Doubling the number of processors causes many programs to go twice as fast. In contrast, doubling the number of transistors in a serial CPU results in a very modest increase in performance--at a tremendous expense in energy," he adds.

Nvidia's scientist also underlined the importance of graphics processing units, which enable continued scaling of computing performance in today's energy-constrained environment.

"Every three years we can increase the number of transistors (and cores) by a factor of four. By running each core slightly slower, and hence more efficiently, we can more than triple performance at the same total power. This approach returns us to near historical scaling of computing performance," he says.

To continue scaling computer performance, it is essential that we build parallel machines using cores optimized for energy efficiency, not serial performance.

"Building a parallel computer by connecting two to 12 conventional CPUs optimized for serial performance, an approach often called multi-core, will not work. This approach is analogous to trying to build an airplane by putting wings on a train. Conventional serial CPUs are simply too heavy (consume too much energy per instruction) to fly on parallel programs and to continue historic scaling of performance," Dallly added.

"Parallel computing is the only way to maintain the growth in computing performance that has transformed industries, economies, and human welfare throughout the world. The computing industry must seize this opportunity and avoid stagnation, by focusing software development and training on throughput computers - not on multi-core CPUs," said Dally.

Forbes.com has published Bill Dally's complete article.


Previous
Next
Sony's Dash On Sale        All News        Europe's First All Digital, 3D Multiplex Cinema Opens
ASUS Launches the EeeKeyboard PC     PC Parts News      LaCie Announces LaCie Rugged USB 3.0

Get RSS feed Easy Print E-Mail this Message

Related News
AMD Increased GPU Market Share in Q1
Nvidia Releases the 3GB GeForce GTX 1050 to Attract More PC Gamers
Data Center and Gaming Business Boost Nvidia's Revenue
Nvidia Kills the GeForce Partner Program
Nvidia Climbs Top 10 List of Chip Sellers
Nvidia Boosts GPU Performance in training Neural Networks, Partners With Arm Partner to Bring Deep Learning to IoT
NVIDIA Quadro GV100 GPU Announced for the Age of Deep Learning
GPU Market Declined seasonally in Q4, Despite Interest in Cryptocurrency Mining
Nvidia Reports High Revenue on High GPU Demand
Nvidia to Work With Continental on Robocars
Chinese Automaker Chery to Use NVIDIA SoC for Level 3 Autonomous Cars
Nvidia Patches Graphics Cards For Spectre Flaw

Most Popular News
 
Home | News | All News | Reviews | Articles | Guides | Download | Expert Area | Forum | Site Info
Site best viewed at 1024x768+ - CDRINFO.COM 1998-2018 - All rights reserved -
Privacy policy - Contact Us .