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Energy-Efficient Computing: Emerging Technologies. Fred Chong Director, Computer Engineering Director, Greenscale Center for Energy-Efficient Computing University of California at Santa Barbara. It's not all Hype…. EPA report, Public Law 109-231, 2007. Maybe a little Hype …. =.

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energy efficient computing emerging technologies

Energy-Efficient Computing: Emerging Technologies

Fred Chong

Director, Computer Engineering

Director, Greenscale Center for Energy-Efficient Computing

University of California at Santa Barbara

it s not all hype
It's not all Hype…

EPA report, Public Law 109-231, 2007

maybe a little hype
Maybe a little Hype…

=

Server

SUV

  • More precisely:
    • 80 billion terawatt-hr / yr = 6 million SUVs in carbon production (10 mpg, 11K miles/yr)
  • Computing is the fastest growing segment of carbon production
  • But actually an issue of energy productivity
the first steps have been taken
The First Steps Have Been Taken
  • Google reports infrastructure (PUE) and server (SPUE) efficiencies close to practical optimal (within 20%)
  • Remaining gains in more:
    • Efficient computation
    • Energy proportionality

[Barroso and Hoetzle 2009]

Google Cooling Tower

what s left
What's Left?
  • More efficient computation
    • Parallelism
    • Communication
    • Storage hierarchy
  • Energy proportionality
    • Infrastructure, power delivery, storage, networks, servers

[Barroso and Hoetzle 2009]

persistent memory
Persistent Memory
  • Substantially better energy proportionality
    • But distributed system software/protocols must be restructured
  • FLASH
    • 2.5X server performance/watt [Swanson ASPLOS09]
    • Lots of work on durability
    • Optically-assisted FLASH?
  • Phase-change memory
    • Same active energy, 20% slower than DRAM [Lee ISCA 09]
3d integration
3D Integration
  • Through-Silicon Vias (TSVs)
  • 3D DRAM
    • 2X performance [Loh ISCA08]
    • 10X capacity?
  • Power dissipation?
    • Vapor / liquid cooling
    • Superlatticemicrorefrigeration (600 W/cm2, 35% efficiency)
    • Carbon nanotube thermal routing
  • Combine different technologies
    • Logic, DRAM, Optics
silicon photonics
Silicon Photonics
  • Server backplane
    • 10 Tbit/s [Beals Appl. Phys A 2009]
  • On-chip or on-wafer [Vantrease ISCA08] [Krishnamoorthy Proc IEEE 2009]
    • 1 Tbit/s per frequency per link
    • 100s of frequencies
    • 10-100s Tbytes/s bisection
changing the game
Changing the Game
  • Energy-efficient computation
    • Will likely exploit parallelism
    • Will need game-changing communication support
    • Will need game-changing storage technologies