“experiences with the adoption of disruptive technologies craig … · 2015-06-09 ·...
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“Experiences with the adoption of disruptive technologies”
Craig Mudge PhD 1973
Founder and CEO of Austek Microsystems Ltd.Computer Science Lab Director, Xerox PARC
Research Fellow,CSIRO, Australia’s national science agency
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Grace Hopper
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Outline
1.Early adopters
2.Three cases of disruptive technologies1. Cache memories2. End-user chip design and the WiFi patent
3. Data-driven modelling
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Crossing the chasm
Everett Rogers: Technology Diffusion Geoffrey Moore: Crossing the chasm
Enthusiasts/visionaries
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Cache memories
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Cache memories
Caches work because programs exhibit memory localityspatial localityandtemporal locality
in their references to memory.
processor cache
Primary memory
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Cache parameters: size, associativity, block size, replacement algorithm, and write strategy.
size associativity
PDP-11/70 2Kbytes Multiple S-TTL chips Set size 2
PDP-11/60 2Kbytes Multiple S-TTL chips Direct mapped
VAX-11/780 8Kbytes
Austek A38502 32Kbytes Single-chip controller;Multiple data chips
4-way set associative
Austek Level 2 128Kbytes Single-chip controller;Multiple data chips
Data centre Intel Haswell -E
20 MbytesLevel 3
32-way
IBM Z13 uP chip 64 Mbytes Level 3
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Simulating cache parameters and miss ratio
(Strecker, 1976)
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(Sites, 2015)
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End-user chip design
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Mead Conway Chip design
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AUSMPC 5/82
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Correlator chip
FFT Chip
WLAN patent
FFT ChipFast Fourier Transform
Applications: audio processing,video processing, medical imaging, wireless communication, radio astronomy
www.pacific-challenge.com 14
AUSMPC5/82 test Correlator
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WLAN innovation story …contdHigh-speed wireless communication: -
reflections multi-path
solution:- send with different frequencies and recombine at the receiver -- requires many FFTs
1991 PLANS workshop – high speed untethered, mobile local networks
1992 – 1996 Patent then part of 802.11 international standard
2009 Prime Minister’s Prize for Science
2012 European Inventor Award
2009 Licensing revenues began
www.pacific-challenge.com 15
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Data-driven modelling
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Data vs algorithms
1. Machine translation of language
2. Driverless vehicle1. 2005 ARPA Grand Challenge 7 miles, 7 hours
2. 2011 hundreds of thousands of miles
“We don’t have better algorithms, we just have more data”-- Peter Norvig, Google
www.pacific-challenge.com 17
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Google-style computing
Google, Dalles Oregon Microsoft Azure, Chicago
50,000 computers in each warehouse-sized data centreSpread across the globe, linked by the InternetServices (compute and storage offered over the Web
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Statistical modelling of Power Usage Efficiency (PUE) in massive data centres
(Gao, 2013)
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Copyright © 2009 Rio Tinto
Global miner
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Conclusion
Three cases of disruptive technologies1. Cache memories2. End-user chip design and the WiFi patent
3. Data-driven modelling
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Thank you
+61 417 679 266
www.pacific-challenge.com
www.cloudinnovation.com.au
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www.pacific-challenge.com 22/8/2008 27
Background: three of my fun projects
1. VAX minicomputer 1975
3. Internet phone
(VoIP 1995)
Austek
Microsystems
DEC
2. Bionic ear
1985
XEROX PARC