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Information Technology News In the beginning was the Apple...and the Acorn
Information Technology News In the beginning was the Apple...and the Acorn | In the beginning was the Apple...and the Acorn |
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| by Stuart Corner | |
| Wednesday, 12 September 2007 | |
  
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Announcing the award, the IET said: "For many people across the English speaking world, their first experience of a computer was through the BBC Microcomputer, including the vast majority of pupils in the UK, who first used BBC Microcomputers to learn computer literacy and information technology skills. The computer, which was developed by Furber and colleagues in 1981, was particularly successful as an educational tool." Furber was also a lead player, at Acorn in the development of the ARM 32-bit RISC microprocessor, starting in 1983. According to the IET, "The team, in which Steve Furber played a leading role, developed the technology that formed the basis for the world's most successful SoC (System-on-Chip) processor licensing company. Because of initial benefits of high performance with power efficiency and cost effectiveness, ARM processors have become the most prolific in mobile and consumer electronics applications across the globe. "The processors are now found in all corners of consumer electronics worldwide, from portable devices which include PDAs, mobile phones, media players, handheld gaming units, automotive applications, digital set-top boxes, high-definition TV, to computer peripherals such as hard drives and desktop routers. In 2006, almost 2.5 billion ARM processors were shipped around the globe by ARM's semiconductor partners." Sir Robin Saxby, president of the IET and chairman emeritus, ARM Holdings plc, said: "Professor Furber is a great example of someone in the UK who bridges the gap between academic excellence and commercial success." Furber is currently the ICL Professor of Computer Engineering within the School of Computer Science at the University of Manchester. His current research interests include: Neural systems Engineering, which is using engineering systems to understand the architecture of the brain; also research that is looking at ways to reduce the power requirement of small sensor systems to the point where they can run from scavenged energy that has been derived from their environment in the form of light, vibration, body heat or similar resources.{moscomment} |
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