In a quest to make faster chips and deliver low-power computing, scientists have creating good-enough chips that instead of performing every calculation to its exact decimal point, are allowed to make mistakes. This field of computing could improve big data analysis, networking and even hearing aids.
2011 is shaping up to be a year when some long-running green IT assertions may finally face their chance to prove themselves. Here are a few of the question I’ll be asking this year as I track the green IT sector’s progress.
Want to know how one of the first Google TV devices looks like on the inside? Well, you’re in luck: iFixit just published a Logitech Revue teardown, revealing that the hardware that makes Google TV work isn’t really all that different from a plain old netbook.
If you want to find a Moore’s Law type improvement for batteries, “you’ve got to go to an asteroid and come back with some new materials,” says Quallion President Paul Beach.
With Super Bowl XLIV just hours away, it’s a little late to run out and take advantage of the insane sales on big-screen TVs. But prices have been heading steadily lower not just for displays, but all elements in the video value chain.
Few design trends for electronic devices have had such a seismic impact as the revolution of smallness. It’s not just that the sizes of devices have shrunk; the mindsets of designers and the whole culture of design have shifted toward all things Lilliputian.
A few months ago, 24/7 Wall Street, a New York-based blog, suggested that the sun was about to set on BusinessWeek, Forbes and Fortune — and that BusinessWeek would be the first to go. Well, they were right. McGraw-Hill Cos. (s mhp), the parent company of S&P and BusinessWeek, has reportedly hired boutique investment bank Evercore Partners to sell the venerable magazine that started in 1929. Fortune and Forbes are from that era of magazines as well.
We’re now entering what I call the “Industrial Revolution of Data,” where the majority of data will be stamped out by machines: software logs, cameras, microphones, RFID readers, wireless sensor networks and so on. These machines generate data a lot faster than people can, and their production rates will grow exponentially with Moore’s Law. Storing this data is cheap, and it can be mined for valuable information.
In this context, there is some good news for parallel programming. Data analysis software parallelizes fairly naturally. In fact, software written in SQL has been running in parallel for more than 20 years. But with “Big Data” now becoming a reality, more programmers are interested in building programs on the parallel model — and they often find SQL an unfamiliar and restrictive way to wrangle data and write code. The biggest game-changer to come along is MapReduce, the parallel programming framework that has gained prominence thanks to its use at web search companies. Read More about Parallel Programming in the Age of Big Data
Things change fast in computer science, but odds are that they will change especially fast in the next few years. Much of this change centers on the shift toward parallel computing. In the short term, parallelism will take hold in massive datasets and analytics, but longer term, the shift to parallelism will impact all software, because most existing systems are ill-equipped to handle this new reality.
Like many changes in computer science, the rapid shift toward parallel computing is a function of technology trends in hardware. Most technology watchers are familiar with Moore’s Law, and the more general notion that computing performance doubles about every 18-24 months. This continues to hold for disk and RAM storage sizes, but a very different story has unfolded for CPUs in recent years, and it is changing the balance of power in computing — probably for good.
Read More about Programming a Parallel Future
Hey Jeff, thanks for reminding me that on December 16th, 1947 William Shockley, John Bardeen & Walter Brattain created the first working transistor, the basic building block that helped build some nations and a few trillion dollar fortunes.
Six decades later, the computer business is facing a brand new set of challenges. Moore’s Law as we have known it is facing a ceiling, argues Associated Press.