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Green Computing for a Clean Tomorrow
• Improve efficiency, reliability, availability, and usability of computing systems.
Sacrifice a bit of raw speed to reduce power & energy consumption.
Improve overall throughput as the system will always be available, i.e., effectively no downtime.
• Reduce total cost of ownership & increase return on investment.
Crude Analogy• Formula One Race Car: Wins raw performance but reliability is so poor that
it requires frequent maintenance. Throughput low.• Honda S2000: Loses raw performance but high reliability results in high
throughput (i.e., miles driven/month answers/month).
1. Power Consumption & Heat Generation Hurt Reliability, Availability, & Total Cost of Ownership
2. Electrical Power for Computing Costs $$$• Earth Simulator: 12 MW/year $10M/year• World’s Processors: 1.3 GW/year
$1B/year• “Hiding in Plain Sight, Google Seeks More
Power,” The New York Times, June 14, 2006.
3. Computing “Contributes” to Global Warming
Motivation
Goal: Deliver high performance while reducing power & energy consumption and improving reliability.
Prof. Wu FENG, [email protected] of Engineering, Depts. of CS & ECE
Just the processors (i.e., CPUs) in PCs ≈ 40 Hoover Dams(Estimated power consumption of PCs ≈ 120 Hoover
Dams)
2001 to 2006
1
10
100
1000
1.5 1 0.7 0.5 0.35 0.25 0.18 0.13 0.1 0.07
I386 – 1 wattI486 – 2 watts
Pentium – 14 watts
Pentium Pro – 30 wattsPentium II – 35 watts
Pentium III – 35 watts
Chip Maximum Power in watts/cm2
SurpassedHeating Plate
Not too long to reach
Nuclear Reactor
Year
Pentium 4 – 75 watts
1985 1995 2001
Itanium – 130 watts
Source: Fred Pollack, Intel. New Microprocessor Challenges in the Coming Generations of CMOS Technologies, MICRO32 and Transmeta
Systems Processors Reliability & Availability
ASCI Q 8,192 MTBI: 6.5 hrs. 114 unplanned outages/month.– Outage sources: storage, CPU, memory.
ASCI White
8,192 MTBF: 5 hrs. (2001) and 40 hrs. (2003).– Outage sources: storage, CPU, 3rd-party HW.
NERSC Seaborg
6,656 MTBI: 14 days. MTTR: 3.3 hrs.– SW is the main outage source.
Availability: 98.74%.
PSC Lemieux
3,016 MTBI: 9.7 hrs.Availability: 98.33%.
Google ~450,000 550+ reboots/day; 2-3% machines replaced/yr.– Outage sources: storage, memory.
Availability: ~100%.
MTBI: mean time between interrupt; MTBF: mean time between failure; MTTR: mean time to restore
• “Making a Case for a Green500 List,” 20th IEEE Int’l Parallel & Distributed Processing Symp., Apr. 2006.• “A Power-Aware Run-Time System for High-Performance Computing,” SC|05, Nov. 2005. • “The Importance of Being Low Power in High-Performance Computing,” CTWatch Quarterly (NSF), 1(3):12-20, Aug. 2005. • “Green Destiny and Its Evolving Parts,” Innovative Supercomputer Architecture Award, 19th Int’l Supercomputer Conf.,
Jun. 2004. • “Green Destiny + mpiBLAST = Bioinfomagic,” 10th Int’l Conf. on Parallel Computing (ParCo), Sept. 2003.• “Honey, I Shrunk the Beowulf!” 31st Int’l Conf. on Parallel Processing, Aug. 2002.
Self-Adapting Software for Energy Efficiency Conserve power & energy WHILE programs run.
Sequ
en
tial C
od
es
Para
llel C
odes
Energy savings and performance improvement!
relative time / relative energy with respect to total execution time and system energy usage
1. Low-Power, High-Performance Computing Green Destiny : A 240-Node Supercomputer in 5 Sq. Ft. with a 3.2-kW Power
Envelope
Reliability Operating Environment: A dusty 85°-90° F warehouse. No machine room. No unscheduled downtime in its 24-month lifetime.
Performance: A Top500 Supercomputer (circa March 2002). Linpack: 101 Gflops.
4
40
Arrenhius Equation (applied to microelectronics) & Twenty Years of Empirical Data
For every 10°C increase in temperature, the failure rate of the system doubles.
Reduce power consumption Reduce system temperature Reduce failure rate
Observation
The Project:Supercomputing in Small Spaces
Green Destiny : A 240-node Supercomputer in Five Sq. Ft.
2. Power-Aware, High-Performance Computing
Only Difference? The Processors
Green Destiny: Low-Power Supercomputer
Green Destiny “Replica”: Traditional Supercomputer
3.2
kW
30
.0 k
W
Hypothesis
Selected Publications
Many commodity technologies support dynamic voltage & frequency scaling (DVFS), which allows changes to the processor voltage and frequency at run time.
A computing system can trade off processor performance for power reduction. Power V2f, where V is the supply voltage of the processor and f is its
frequency. Processor performance frequency.
Approach: Intelligent DVFS Scheduling Determine when to adjust the voltage-frequency setting and what to adjust it to.
Approaches
Results
Laboratory
NAS/NPB 3.2 – MPI, C.16
Featured in The New York Times, CNN, and BBC NewsNow in The Computer History Museum