1 / 34

Paintable Computing

A Presentation of: “Programming A Paintable Computer” William Butera PhD Thesis, MIT 2002. Paintable Computing. all images (c) their respective owners. The Goal. Computing by the Liter. The Big Idea. The Superlative Multi-Processor Inverse of Current Architecture Paradigm

pules
Download Presentation

Paintable Computing

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. A Presentation of: “Programming A Paintable Computer” William Butera PhD Thesis, MIT 2002 Paintable Computing all images (c) their respective owners

  2. The Goal • Computing by the Liter

  3. The Big Idea • The Superlative Multi-Processor • Inverse of Current Architecture Paradigm • What are the hard problems? • Are they worse than what has already been solved?

  4. Architecture Problems • Asynchronous devices • No easy way to make synchronous • Highly Unreliable Processors

  5. Architecture Problems • No Global Communication • Unknown (and Unknowable) Topology

  6. Architecture Problems • Code must be compact • Nodes cannot support large processes • Working sets must be small • Infinitely many paths to failure

  7. The Solution • New Architecture => New Solution • Out with the old assumptions • Self Assembly • Better paradigm • Redefines “success”

  8. Complex Adaptive Systems • Aggregate Behavior • simple parts => arbitrarily complex systems • Statistical Output • Local Interactions => Global State

  9. Implementing a Solution • What sort of hardware is a good target? • Cannot be too small • Must be able to do useful work • Cannot be too large • Must be hard enough

  10. Reference Standard “Paintable” Computer-- Processing -- • Really tiny “traditional” architecture • CPU: 10-200Mhz • RAM: 50K words • Bus: 16+ bit • Programmable in traditional languages • C, Java, etc

  11. Reference Standard “Paintable” Computer-- Power -- • Unspecified interface • Does not impinge on the architecture • Examples • Batteries • Chemical substrate • Photo-cell • Structural power routing • Fuel Cells

  12. Reference Standard “Paintable” Computer-- Networking -- • Directionless • Bandwidth: 100kbps Full Duplex • Radius: ~8 particles • Gaussian Random distribution of connectivity • Example Technologies: • luminescence • electrostatic • near-field RF

  13. The Pushpin Computer • A real system • An example of a paintable computer • Model architecture • 330 nodes

  14. System Layout • Separate communication, ground, and power • Planes separated by flexible silicon insulation

  15. Programming Model • Program Fragments (PFrag's) • Computational Elements • Shared Memory Partitions • Inter Process Communication • Embedded OS • Local Resource Control • Special PFrag Services

  16. Shared Memory Layout

  17. Shared Memory Layout • PFrag I/O • Bassinet: Pre-Load Store • Launch Pad: Post-Unload Store • Data I/O • Home Page: Output to Neighbors • Mirrored Home Pages: Input From Neighbors • Organized as a key value pairs

  18. OS Services 1 and 2 of 4 • Housekeeping • Defragmenting Memory • Resizing I/O Zone • Network Access • Inter Processor Communication • Manages Access I/O Regions • Manages Joins/Leaves • Mediates PFrag Access to I/O Regions

  19. OS Services 3 and 4 of 4 • Running PFrags • Installs / Uninstalls the PFrag • Runs the PFrag • PFrag Services • Mathematics • Random Numbers • Access to Memory • Transit Request Messages • etc.

  20. PFrag Implementation • Implements Five Functions • Install • Moves Self From Bassinet to Main Memory • DeInstall • Cleans Up and Erases Self • Update • Runs the process

  21. PFrag Transit • Transfer-Granted • Cleans Up and Moves to Launch Pad for Transit • Transfer-Refused • Allows PFrag to Dequeue Transfer Request

  22. Does It Work? • Need to prove Viability • Simple Applications that we can use to: • Test • Validate • Butera Implements • BreadCrumbs • Near Sighted Mailman • Knitting Club

  23. What Is It Good For? • What software will Motivate? • Need a “Killer App” • Only works well on a Paintable Architecture • Butera Implements • Gradient • MultiGrad • Tessellation Operator • Diffusion • Channel Operator • Coordinate Operator

  24. Can It Do What I Want It To? • Need to Prove Utility • Simple Applications that do something Useful • Traditional Service We Cannot Live Without • Butera Implements: • Streaming Audio • Holistic Data Storage • Surface Bus • Image Segmentation

  25. Where do we go from here? • AMD and Intel • 2-4 on core processors • cannot go faster • go wider! • How far can we expand sideways? • A job for Architecture!

  26. How Good Is It? • Can We Compare to Traditional? • Apples = Oranges? • Consider Two Cases • Serial Operation • Embarrassingly Parallel Operation

  27. The Worst Case: Serial • Cannot “optimize away” all serial operations • Interactive Programs • Shells will work • low system requirements • low communication overhead • Will need a new device to do graphics • Build output into paintable? • Integrate a larger processor for graphics? • Can still do Mulitprocessing • Can make it massively fault tolerant

  28. The Best Case: Parallel • Where is our overhead? • Getting the problem to the device • Getting the problem off the device • Sharing intermediates • The Computation Scales • with number of units • Cost is critical

  29. How Does Cost Scale? • Butera's Die Assumptions: • Large Die = 100 mm2 • Medium Die = 25 mm2 • Small Die = 1 mm2 • Current Processor Dies • Pentium M = 84 mm2 • Pentium 4 = 131 mm2 • “Smithfield” Dual Core = 206 mm2 • Opteron Dual Core = 199 mm2

  30. Peering Into the Process • Butera's Defect Rate Analysis • 200, 500, 1000 defects • Class 1 Cleanroom • 1 particle per ft3 • 30cm (diameter) wafers = 0.785 ft2 • 250 to 1270 ft of linear air motion • If process takes 5 days: • 2 to 10.5 ft per hour air motion • Assumptions are reasonable, even optimistic

  31. How Does Cost Scale? • Butera's Calculations

  32. Why is this relevant? • Yield Ratio is ~ 200 : 1 • As much as 20,000% greater yield

  33. How Can This Help? • Consider a motivating problem • Embarrassingly Parallel • O(n2) computation • O(n) input • O(n) output • No inter-node communication • Only Need to Consider Problem Input/Output • O( n * log8(n) )

  34. How Does It Scale?

More Related