New HiPEAC Roadmaps · 2013. 6. 17. · Part of the HiPEAC roadmap is required reading for AVDARK...
Transcript of New HiPEAC Roadmaps · 2013. 6. 17. · Part of the HiPEAC roadmap is required reading for AVDARK...
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M. DURANTON, D. BLACK-SHAFFER, S. YEHIA, K. DE BOSSCHERE
http://www.hipeac.net/roadmap
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2009 20112008
http://www.hipeac.net/roadmap(these slides are a short version of the HiPEAC presentation)
HiPEAC Roadmaps
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Part of the HiPEAC roadmap is required reading for AVDARK
You will find it and other required reading in the ”Extra course papers” directory.
As specified in the ”Reading instructions”: page 2-33 are required reading page 34-40 read-through (RT)
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Impact on
Society
???7 HiPEACResearch objectives
HiPEACStrengths
???
HiPEACWeaknesses
Efficiency Complexity
Dependability
Technological constraints
???
Technological opportunities
Big data meets energy in an intelligent connected
physical world
Application pull
Business trends
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Trends influencing Computing Systems
Application Pull BusinessTrends
• Data Deluge• Intelligent Processing• Ubiquitous
Communication
• Convergence• Specialization• Post-PC Devices
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Data Deluge
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Growth of data storage in Exabytes
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Intelligent processing of “natural” data
Source: “The Landscape of Parallel Computing Research: A View from Berkeley”Krste Asanovic et all.
More and more applications are not only “number crunching”Recognition, Mining, Synthesis
Posture: Lying Down
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Implicit and natural computing
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Ubiquitous computing in a connected world
Courtesy Jan M. Rabaey, UC Berkeley, updated for this HiPEAC vision
Sensory swarm, actuators and real world data
InfrastructureCore (cloud)
Mobileaccess
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Smart housecities, …
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Trends influencing Computing Systems
Application Pull BusinessTrends
• Data Deluge• Intelligent Processing• Ubiquitous
Communication
• Convergence/standards• Specialization• Post-PC Devices
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Convergence
Broadcast
Telecom
11MacBook image © Jared C. BenedictPhone, TV images © LG Electronics
IP, Internet•Business models• Standard(s)• Interoperability• …
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Post-PC devices
Ubiquitous access
Personalized services
Delocalized computing and data
Massive data processing systems • Cloud• Peer to peer• Personalized
12iPad image © Apple, IncMP3 player image © J A S P E R@flickriPhone image © K!T@flickr
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PC Market
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Computing Systems: Drivers
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Big data meets energy
in an intelligent connected
physical world
Application pull
Business trends
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Efficiency Complexity
Dependability
Technological constraints
???
Technological opportunities
Big data meets energy
in an intelligent connected
physical world
Technology push
Application pull
Business trends
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Technological trends influencing Computing Systems
Constraints Opportunities• Frequency Limits• Power Limits• Dark Silicon
• CMOS Phonotic• Non-volatile memories• 3D Stacking• New paradigms
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Technological constraintsWe are at a turning point
Dark silicon
Continuation of Moore’s Law Power limits
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Moore’s law: increase in transistor density
Data from Kunle Olukotun, Lance Hammond, Herb Sutter, Burton Smith, Chris Batten, and Krste Asanovic
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Limited frequency increase more cores
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Data from Kunle Olukotun, Lance Hammond, Herb Sutter, Burton Smith, Chris Batten, and Krste Asanovic
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Limitation by power density and dissipation
2009: GP CPU = 130 W (45 nm)2009: Consumer SoC = 10W2009: Mobile SoC = 1 W
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Data from Kunle Olukotun, Lance Hammond, Herb Sutter, Burton Smith, Chris Batten, and Krste Asanovic
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Dark Silicon
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Source: Krisztián Flautner “From niche to mainstream:can critical systems make the transition?”
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Specialization leads to more efficiency
Source: Bill Dally, « To ExaScale and Beyond »
www.nvidia.com/content/PDF/sc_2010/theater/Dally_SC10.pdf 22
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In 22 nm, swapping 1 bit in a transistor has an energy cost:
~ 1 attojoule (10-18 J)
Moving a 1-bit data on the silicon cost:
~1 picojoule/mm (10-12 j/mm)
Moving a data 109 per second (1 GHz) in silicon has a cost:
1 pJ/mm x 109 s-1 = ~1 milliwatt/mm
64 bit bus @ 1 GHz: ~64 milliwatts/mm (with 100% activity)
For 1 cm of 64 bit bus @ 1 GHz : 0,64 W/cm
On modern chips, there are about several km of wires on chip, even
with low toggle rate, this leads to several Watt/cm2
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Locality and communications management
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Technological consequences
Efficiency localityFrequency limit
parallelismEnergy efficiency
specialization
Ease of programming
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Technological trends influencing Computing Systems
Constraints Opportunities• Frequency Limits• Power Limits• Dark Silicon
• CMOS Phonotic• Non-volatile memories• 3D Stacking• New paradigms
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Optical interconnectsCMOS photonic is the integration of a photonic layer with an electronic
circuit.Advantages of CMOS photonic are:
Use of standard tools and foundry, wafer scale co-integration Lower energy (~100 fJ/bit), (wire: ~1 pJ/mm) High bandwidth (10 Gbps), Low latency (~10 ps/mm)
Silicon modulator
SOI wave guideI
2D networkInversed taper
Germanium photdetector
LASER
Source: CEA, Ahmed Jerraya26
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Example: Memristive Devices Principle
1 L. Chua and S. Kang, Proceedings of the IEEE, 19762 D. Strukov et al., Nature, 2008
Metal (Mx+1 layer)
Metal (Mx layer)
Insulator• Oxide• Solid electrolytic• Organic material
ElectrodesMIM
V
VdRdt
R
Vth
-Vth’
Nonlinear characteristic
iixRv ).,(= ),( ixfdtdx =
Crossbar(University of Michigan)
Source: CEA, C. Gamrat
Non-volatile memories….
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3D stacking
Multiple integration with 3D stacking…Source: STMicroelectronics & CEA 28
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Technology also drives us to think differently…
Technology
System
Prog. Model
• Stochastic computing• Biologically inspired computing• Organic Computing• Autonomous computing, Self-*
• Smart spaces (smart house, town, building, rooms,…)
• Intelligent dust (smart sensors)
• 3D stacking• Photonic interconnect• Non-volatile memories• Molecular computing• More-than-Moore• Spintronics• Chemical computing• Biologically inspired cells• Memristors• ...• Also silicon based!
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Efficiency Complexity
Dependability
Technological constraints
???
Technological opportunities
Big data meets energy
in an intelligent connected
physical world
Technology push
Application pull
Business trends
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Core Computing Systems Challenges
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Improving efficiency Multiple performance metrics Power defines performance Communication defines performance Heterogeneity and accelerators to the
rescue
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Managing complexity The reign of legacy code Parallelism seems to be too complex for
humans Hardware complexity
(4G is 500x more complex than 2G)
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Improving dependability Worst case design is not an option
anymore Systems must be built from unreliable
components Safety and security!
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Impact on
Society
???7 HiPEACResearch objectives
HiPEACStrengths
???
HiPEACWeaknesses
Efficiency Complexity
Dependability
Technological constraints
???
Technological opportunities
Big data meets energy in an intelligent connected
physical world
Application pull
Business trends
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Impact on
Society
???7 HiPEACResearch objectives
HiPEACStrengths
???
HiPEACWeaknesses
Efficiency Complexity
Dependability
Technological constraints
???
Technological opportunities
Big data meets energy in an intelligent connected
physical world
Application pull
Business trends
![Page 37: New HiPEAC Roadmaps · 2013. 6. 17. · Part of the HiPEAC roadmap is required reading for AVDARK You will find it and other required reading in the ”Extra course papers” directory.](https://reader036.fdocuments.net/reader036/viewer/2022081600/604e7d306a755c17eb0b9f33/html5/thumbnails/37.jpg)
Derived HiPEAC Research ObjectivesC
ompu
ting
syst
ems
System complexity
• Heterogeneous computing systems
• Locality and communications management
• Cost-effective software for heterogeneous multicores
• Cross-component/cross-layer optimization for design integration
• Next-generation processor cores
• Architectures for the Data Deluge• Reliable systems for Ubiquitous
Computing37
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Frequency limit parallelism
Energy efficiency heterogeneity
Ease of programming
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Cost-effective software for heterogeneous multicores
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Detailed HiPEAC Research areas
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Global optimization
Technology and new devices
Efficiency System Complexity Dependability
Data DelugeEnergy Wall, Connected, Real world dataTurning point for Moore’s law
Het
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Conclusion
Exiting new opportunities are ahead of us!