Paintable Computer Ting Yan CS 851 Bio-Inspired Computing Presentation March 25, 2003.
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Transcript of Paintable Computer Ting Yan CS 851 Bio-Inspired Computing Presentation March 25, 2003.
![Page 1: Paintable Computer Ting Yan CS 851 Bio-Inspired Computing Presentation March 25, 2003.](https://reader035.fdocuments.net/reader035/viewer/2022062322/5697c0071a28abf838cc631f/html5/thumbnails/1.jpg)
Paintable Computer
Ting YanCS 851 Bio-Inspired Computing Presentation
March 25, 2003
![Page 2: Paintable Computer Ting Yan CS 851 Bio-Inspired Computing Presentation March 25, 2003.](https://reader035.fdocuments.net/reader035/viewer/2022062322/5697c0071a28abf838cc631f/html5/thumbnails/2.jpg)
Butera’s Dissertation
• Introduction
• Background - Cost Analysis, Self-Assembly
• System Architecture - HW, PM, Simulator
• Essential Process Fragments
• Applications
• Wrap-Up
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What is a paintable?
• … particles … suspended into a viscous medium and deposited it on surfaces like paint
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Characteristics
• Sand size, limited resource
• Ability to harvest power from environment
• Arbitrary topology, no localization
• Wireless local communication
• Single particle failure
• Asynchrony
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Motivation and Difficulty
• Economics– Computing power for a whole wafer constant– The larger the dies, the lower the yield– Cost-effective to use dense ensembles of dust size computing
elements instead of centralized architectures
• Difficult for people to structure– If we can not get a human to structure the procedures, we are
going to have to get the procedures to structure themselves.– Self-Assembly, Autonomic Computing, e.g., self-
organization, self-management
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Comparison with SensorNets
• Sizes - dust-size vs. coin-size
• Power - environment harvesting vs. battery
• Purpose - computing vs. computing + sensing + actuating
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Hardware Platform
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Memory Organization
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Self-contained Executables
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Interactions
• pFrags read/write tagged data from/to homepage
• When a pFrag posts tagged data to the homepage of its own particle, copies of the post appear at all mirror sites
• pFrags propagate and migrate among particles
• Errors, packet losses should be handled
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Self-Assembly
• Categories– Scaffolded: shape lock-and-key
– Thermodynamic: minimum free energy
– Code: guided by coded instructions
• Arbitrarily complex system behavior can be created from large numbers of simple processing elements (pFrags).
• Global reliable computation can be obtained from aggregate statistics on a large set of local interactions.
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BreadCrumb pFrag
• Purpose - monotonically ascending addresses• Update behaviors
– propagation, adaptation or removal
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NearSightedMailMan
• Purpose - routing• based on BreadCrumb• by HomePage posts
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Gradient pFrag
• Basically, hop counts from a external device
• Stages– installation, propagation, adaptation, removal
• Adaptation formula 1min1 HCHCt
N
HCHCD
t
N
ii
t
11
1
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Gradient Effect
• When stabilized, HC is the minimum hop count to the reference point• Common problems: How long does it take? Race conditions? pFrag
always takes place in memory
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Gradient Adaptation
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Get Location with Gradient
Precision proportional to communication radius, affected by node density.
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MultiGrad - vFrag
- One virtual pFrag emulating multiple pFrags- Save memory space- Any pFrag can issue a request for Gradient
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Tessellation Operator
• Purpose: group the particles into the Voronoi regions about a uniformly distributed set of anchor points
• MultiGrads used to obtain distance to a certain particle
• Centroid - minimize potential energy for a spring force like field
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Tessellation - Details
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Tessellation - Issues
• Time issues - settling time, randomness, large moves
• Precision
• Initial field strength - neither too low nor too high would work
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Tessellation Adaptation
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Channel Operator
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Channel Operator
• End-to-End communication
• Gradient, Tracers and Halos
• Gradient issued at the destination
• Gradient - a waste of bandwidth?
• Cross-traffic prohibited?
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Coordination Operator
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Coordination - Example
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Diffusion
• Diffuse a stream of data “fairly” in the ensemble - time and space
• Rule - the pFrag with the maximum Timer count searches the I/O space for the neighboring particle with the smallest number of Diffusion posts.
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Diffusion - Result