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Designing Tomorrow’s Computing Platforms
Challenges, Solutions, and Tools
Sudhanva Gurumurthie-mail: [email protected]
Talk Outline
• Modern Computer Architecture– The Good– The Bad– The Ugly
• My Previous Work
• Current and Future Research
The Good
Source: http://www.intel.com/technology/silicon/mooreslaw/
Microprocessor Technology Advancement
• Plentiful Transistors– Superscalar, SMT, CMP– Larger caches, deeper memory-hierarchy– High-bandwidth access to memory
• Simultaneously, clock frequencies have grown tremendously
Storage Has Become Ubiquitous
Density
Speed
Source: Hitachi GST Technology Overview Charts, http://www.hitachigst.com/hdd/technolo/overview/storagetechchart.html
Growth in Drive Performance
The Bad
Power Dissipation
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Po
we
r (W
)
8086 286 386 486 Pentium PentiumIII
Pentium4
Particle Induced Soft-Errors
01
Source: FACT Group, Intel
Are you kidding me?
• No!!– In 2000, Sun Microsystems reported random crashes
in one of its server products due to no parity-protection in the caches.
– Eugene Normand’s study of the error-logs of large systems indicated several such errors
– There are conference sessions and even full conferences/workshops devoted to this problem
– Have personal experience collecting and analyzing soft-error data
Where Do These Particles Come From?
• Neutrons– Terrestrial cosmic rays
• Alpha particles– Packaging
Should we worry?
• Yes!!– Thanks to Moore’s Law
• Lower operating voltages• Exponential increase transistor integration density• Power management (voltage-scaling)
– Larger systems
• Impractical to shield against cosmic rays– Need several feet of concrete– Radiation-hardening hurts performance, area, and
cost
Redundant Multi-Threading
InputReplicator
OutputComparator
Rest of the System
Source: Mukherjee et al, “Detailed Design and Evaluation of Redundant Multithreading Alternatives”, ISCA’02
Performance of Redundant Multi-Threading
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Pe
rce
nta
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of
IPC
Lo
st
gzip swim vpr gcc mesa art mcf equake parser vortex bzip2
Temperature Affects Disk Drive Reliability
• Heat-Related Problems– Data corruption– Higher off-track errors– Head-crashes
Disk drive design constrained by the thermal-envelope• Puts a limit on drive performance
Source: D. Anderson et al, “More than an Interface – SCSI vs. ATA”, FAST 2003.
Power =~ (# Platters)*(RPM)2.8(Diameter)4.6
Increase RPM
Thermal-Constrained Design
Increase RPM
Lower Capacity
Shrink Platter
1 platterData Rate =~ (Linear-Density)*(RPM)*(Diameter)
(RPM)2.8 (Dia)4.6 (# Platters)
Lower Data Rate
Data-Rate Capacity
Temperature
40% AnnualIDR Growth
The BadDrive Temperature
10
100
1000
Year
Tem
pera
ture
(C
)
2.6" 2.1" 1.6"
Thermal-Envelope
The BadData Rate
30-60% Performance Boostfor 10,000 RPM Increase
Search-Engine Thermal Behavior
Thermal Envelope = 45.22 C
The Ugly
Design Tools
• Designing complex systems requires extensive simulation
• Need to model all aspects of the system– Software layers– Power– Temperature– Effect of faults
Simulation Problems
• Painfully slow– Speed vs. Accuracy
• No good support available for modeling effects like temperature and reliability
• Can themselves be hard to write
• Buggy
My Previous Work
Thesis Work:Power Management of
Enterprise Storage Systems
Enterprise Storage Market Growth
• Storage demand growing at annual rate of 60%– By 2008, a company would manage 10 times the
storage it has today.Sources:
1. “Enterprise Storage: A Look into the Future”, TNM Seminar Series, Oct. 31, 2000
2. “More Power Needed”, Energy User News, Nov. 2002
Power Demands of Data Centers“What matters most to the computer designers at Google is not speed but
power – low-power – because data centers can consume as much electricity as a city”, Eric Schmidt, CEO, Google
• Data centers consume several Megawatts of power
• Electricity bill– $4 billion/year– Disks account
for 27% of computing-load costs
• Difficult to cool at high power-densities
Sources:
1. “Intel’s Huge Bet Turns Iffy”, New York Times article, September 29, 2002
2. “Power, Heat, and Sledgehammer, Apr. 2002.
3. “Heat Density Trends in Data Processing, Computer Systems, and Telecommunications Equipment”, 2000.
Data Center Cooling Costs
• Data center of a large financial institution in New York City– Power consumption ~ 4.8 MW
Source: “Energy Benchmarking and Case Study – NY Data Center No. 2”, Lawrence Berkeley National Lab, July 2003.
51%42%
7%
Servers Air-Conditioning Other
Where Does Power Go?
Spindle Motor(SPM)
Voice-Coil Motor(VCM)
Idle = 9 W
Seek = 13 W
Standby = 1 W
4 W
Active = 11 W
Traditional Power Management (TPM)
Disk Active
Spindown
Standby Mode
Spinup
Disk Request
Time
Disk Active
Idleness
Detected
Idle
I/O Characteristics of Server Systems
• Large number of disks– RAID arrays
• Heavier I/O loads sustained over long periods.• Stringent performance requirements.• Server disks physically different
– Not made to use spindowns.– Longer spindown/spinup latencies
• Server Disk - Hitachi Ultrastar – 15 seconds/26 seconds• Laptop Disk - Hitachi Travelstar – 4.5 seconds
Feasibility of Applying TPM
• No prior study on how to tackle this problem systematically.
• Questions1. Is there idleness?2. Can we do TPM?
• Answers1. Yes2. No! Why??
• Large number of very short duration (few ms) idle-periods
The Solution
• Traditional Power Management– Not effective for server workloads
• Power =~ (# Platters)*(RPM)2.8(Diameter)4.6
– All three can be varied at design-time to meet the power budget
• Laptop vs. Server disk
– RPM could be varied dynamically
• Dynamic RPM (DRPM)
Potential Benefits of DRPM
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% S
av
ing
s in
E idle
10 100 500 1000 10000 100000
Mean Inter-Arrival Time (ms)
TPMperf DRPMperf Combined
Control-Policy Performance
Research Impact
• The feasibility study [ISPASS’03] started off new research in server disk power management– Active groups: UIUC, Rutgers, UMass, UArizona,
Rochester
• DRPM paper [ISCA’03] widely cited in architecture and systems conferences like ISCA, HPCA, ASPLOS, SOSP, OSDI
• Multi-speed drives starting to appear in the market– Hitachi Deskstar 7K400
My Other Work
• Microarchitectural Techniques to Enhance Redundant Multi-Threading Performance– Instruction Reuse [ISCA’04]
• Soft-Error Data Collection and Analysis from Actual Systems (Intel)
• Soft-Error Tolerant Cache Coherence-Protocols (Intel)
• Simulator Design– SoftWatt [HPCA’02]
– MEMSIM (IBM Research)
More Details About My Work
• Papers:– S. Gurumurthi et al., Disk Drive Roadmap from the Thermal
Perspective: A Case for Dynamic Thermal Management, ISCA 2005.
– A. Parashar et al., A Complexity-Effective Approach to ALU Bandwidth Enhancement for Instruction-Level Temporal Redundancy, ISCA 2004.
– S. Gurumurthi et al., DRPM: Dynamic Speed Control for Power Management in Server Class Disks, ISCA 2003.
– S. Gurumurthi et al., Using Complete Machine Simulation for Software Power Estimation: The SoftWatt Approach, HPCA 2002.
• Available via my CS Department homepage.
Some Research Directions
• Temperature-Aware Storage Systems– Devices– Systems issues
• Multi-Dimensional Approach to Fault Tolerance– Tradeoffs between performance, power, reliability– Dynamic adaptation
• Microarchitectural Support for Security• Design of accurate and fast simulation tools
Research Directions in Storage
• Storage architecture is still quite a nascent field
• Plenty of research opportunities:– Emerging technologies
• MEMS, holographic, molecular storage
– New Research Avenues• Security• Application/Content-Awareness• Active disks• Long-term and survivable storage
Looking for Students!
• Shall be offering a research course in Spring 2006.– Many project opportunities
• Contact Information:– E-mail: gurumurthi@cs– Office: 236B, Olsson Hall
Divider Slide
Approach 1:Seek Throttling
T
E
M
P
E
R
A
T
U
R
E
TIME
Thermal-Envelope
VCM On
VCM Off
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
Benchmark
Perc
en
tag
e o
f IP
C G
ap
(S
IE-D
IE)
reco
vere
d
DIE-IRB-1K-sat
DIE-2xALU
DIE-IRB-ideal
Results2-42% reduction in IPC
gap (avg. 23%)
