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The GreenDroid mobile application processor is a 45-nm multicore research prototype that targets the Android mobile-phone software stack. It can execute general-purpose mobile programs with 11 times ...

The GreenDroid mobile application processor is a 45-nm multicore research prototype that targets the Android mobile-phone software stack. It can execute general-purpose mobile programs with 11 times less energy than today’s most energy-efficient designs, at similar or better performance levels.

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Greendroid ppt Greendroid ppt Presentation Transcript

  • Visit www.seminarlinks.blogspot.com to download
  • Introduction • The GreenDroid mobile application processor is a 45-nm multicore research prototype that targets the Android mobile-phone software stack. • It can execute general-purpose mobile programs with 11 times less energy than today’s most energy-efficient designs, at similar or better performance levels.
  • Working It does this through the use of a hundred or so automatically generated, highly specialized, energy- reducing cores, called conservation cores.
  • Major technological problem for Microprocessor Architects
  • Necessity • A key technological problem for microprocessor architects is the utilization wall. • The utilization wall says that, with each process generation, the percentage of transistors that a chip design can switch at full frequency drops exponentially because of power constraints. • A direct consequence of this is Dark Silicon • Dark Silicon—large swaths of a chip’s silicon area that must remain mostly passive to stay within the chip’s power budget.
  • • Currently, only about 1 percent of a modest-sized 32-nm mobile chip can switch at full frequency within a 3-W power budget. • With each process generation, dark silicon gets exponentially cheaper, whereas the power budget is becoming exponentially more valuable.
  • What is Power Budget ?? • A power budget shows where all the possible power will be used by a device to by breaking it down into components and categories. • In some situations, you might be told up front that you will have 3W available to run your design. • However, sometimes as designers start by calculating the total power a system needs and then taking actions such as replacing parts or redesigning circuits to cut back power to an acceptable level.
  • The Utilization Wall • Scaling theory Transistor and power budgets no longer balanced Exponentially increasing problem! Classical scaling Device count S2 Device frequency S Device power (cap) 1/S Device power (Vdd) 1/S2 Utilization 1 Leakage limited scaling Device count S2 Device frequency S Device power (cap) 1/S Device power (Vdd) ~1 Utilization 1/S2 Expected utilization for fixed area and power budget 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 90nm 65nm 45nm 32nm
  • The Utilization Wall • Experimental results • Replicated small data path • More ‘Dark Silicon’ than active • Observations in the wild • Flat frequency curve • “Turbo Mode” • Increasing cache/processor ratio Utilization @ 300mm 2 & 80w 3.3% 6.5% 17.6% 0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 0.20 90nm TSMC 45nm TSMC 32nm ITRS
  • Utilization Wall: Dark Implications for Multicore 4 cores @ 3 GHz 4 cores @ 2x3 GHz (12 cores dark) 2x4 cores @ 3 GHz (8 cores dark) (Industry’s Choice) .… 65 nm 32 nm .… .… Spectrum of tradeoffs between # cores and frequency. e.g.; take 65 nm32 nm; i.e. (s =2)
  • Key Insights The research leverages two key insights: • First, it makes sense to find architectural techniques that trade this cheap resource, dark silicon, for the more valuable resource, energy efficiency. • Second, specialized logic can attain 10X to 1,000X better energy efficiency over general-purpose processors.
  • Approach • The approach is to fill a chip’s dark silicon area with specialized cores to save energy on common applications. • These cores are automatically generated from the code base that the processor is intended to run—that is, the Android mobile-phone software stack. • The cores feature a focused re-configurability so that they can remain useful even as the code they target evolves. Dark Silicon
  • The GreenDroid architecture • The GreenDroid architecture uses specialized, energy-efficient processors, called conservation cores, or c-cores to execute frequently used portions of the application code. • Collectively, the c-cores span approximately 95 percent of the execution time of team’s test Android-based workload.
  • The high-level architecture of a GreenDroid system
  • The system comprises an array of 16 non-identical tiles.
  • Each tile holds components common to every tile—the CPU, on-chip network (OCN), and shared Level 1 (L1) data cache—and provides space for multiple conservation cores (c-cores) of various sizes
  • The c-cores are tightly coupled to the host CPU via the L1 data cache and a specialized interface
  • Conservation Cores • Specialized cores for reducing energy • Automatically generated from hot regions of program source • Patching support future proofs HW • Fully automated toolchain • Drop-in replacements for code • Hot code implemented by C-Core, cold code runs on host CPU • HW generation/SW integration • Energy efficient • Up to 16x for targeted hot code D cache Host CPU (general purpose) I cache Hot code Cold code C-Core
  • Figure shows the projected energy savings in GreenDroid and the origin of these savings. The savings come from two sources • First, c-cores don’t require instruction fetch, instruction decode, a conventional register file, or any of the associated structures. Removing these reduces energy consumption by 56 percent. • The second source of savings (35 % of energy) comes from the specialization of the c-cores’ data path. • The result is that average per- instruction energy drops from 91 pJ per instruction to just 8 pJ per instruction.
  • Marching Toward Completion The toolchain automatically generates placed-and-routed c-core tiles, given the source code and information about execution properties. The cycle- and energy-accurate simulation tools have confirmed the energy savings provided by c-cores. The team is currently working on more detailed full-system Android emulation to improve our workload modeling so that they can finalize the selection of c-cores that will populate GreenDroid’s dark silicon. In parallel with this effort, they are working ontiming closure and physical design.
  • The Research Team The University of California,San Diego,USA. Assistant professors • Michael Bedford Taylor • Steven Swanson Postdoctoral scholar • Jack Sampson Massachusetts Institute of Technology (MIT),USA Postdoctoral Researcher • Jonathan Babb PhD students • Nathan Goulding-Hotta • Ganesh Venkatesh • Saturnino Garcia • Manish Arora • Siddhartha Nath Graduate Students • Vikram Bhatt • Joe Auricchio • Po-Chao Huang
  • 22 Conclusions • Over the next five to 10 years, the breakdown of conventional silicon scaling and the resulting utilization wall will exponentially increase the amount of dark silicon in both desktop and mobile processors. • The GreenDroid prototype demonstrates that c-cores offer a new technique to convert dark silicon into energy savings and increased parallel execution under strict power budgets. • The estimate that the prototype will reduce processor energy consumption by 91 percent for the code that c-cores target, and result in an overall savings of 7.4 X.
  • Reference Based on April 2011 IEEE Micro paper. THE GREENDROID MOBILE APPLICATION PROCESSOR: AN ARCHITECTURE FOR SILICON’S DARK FUTURE http://greendroid.ucsd.edu/
  • Visit www.seminarlinks.blogspot.com to download