Más contenido relacionado Más de inside-BigData.com (20) D-Wave Systems Podcast2. What I’ll Talk About
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D-Wave Systems Inc.
What are quantum computers?
D-Wave’s approach & rationale for it
Our current product: The D-Wave TwoTM Quantum Computer
• Integrating QC into HPC
© 2013 D-Wave Systems Inc. All Rights Reserved
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3. D-Wave Systems Inc.
• Privately owned based in Vancouver, Palo Alto & Washington D.C.
– Investors: DFJ, Goldman Sachs, In-Q-Tel, Jeff Bezos, et al
• Offering
quantum computing systems
– Built from superconducting processors
• ~100 employees (27Ph.D., 18 B.Eng. 11 M.Sc.)
• 100+ patents / 60+ peer reviewed papers
• Unique infrastructure (design, fab, test, systems, software)
© 2013 D-Wave Systems Inc. All Rights Reserved
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4. Ranked 4th in Patent Power for Computer Systems
© 2013 D-Wave Systems Inc. All Rights Reserved
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7. What are Quantum Computers?
• Computers that harness quantum physical
phenomena not available to conventional
computers, e.g.,
– Superposition
– Entanglement
– Co-tunneling
– Non-determinism
© 2013 D-Wave Systems Inc. All Rights Reserved
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8. Why are they Interesting?
• Pragmatically
– Allows us to solve problems in new ways to beat the best
we can do classically in many cases
– Exponential speedups
• Factoring
• Simulating quantum systems
• Quantum chemistry
– Polynomial speedups
• Unstructured search
• Structured search (NP-complete & NP-hard problems)
• Philosophically
– As Prof. David Deutsch of Oxford University says …
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9. “Quantum computation … will be the first
technology that allows useful tasks to be
performed in collaboration between
parallel universes”
Prof. David Deutsch – The Fabric of Reality
© 2013 D-Wave Systems Inc. All Rights Reserved
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10. Significance to HPC
of harnessing quantum mechanics
Metric
High Performance Computer
Quantum Computer
One 512-qubit core has ~10154 “virtual
threads” in superposition, but quantum
mechanics limits our ability to read them
Concurrency
108 cores & 1010 threads
Robustness
Reduced operating voltages & channel Naturally probabilistic programming.
widths, will make devices less reliable.
Quantum annealing degrades gracefully to
Need new programming style that is
errors
intrinsically probabilistic and tolerant to
errors
Power
Expect 25-100MW systems. Few
locations can support this demand.
Fewer data centers can afford it. Power
demand dominated by data movement
15kW for cooling & ~0kW for computation.
Cooling power will stay constant up to
thousands of qubits! Almost no energy to
compute. No data movement needed
Storage
Needs to be 100PB capacity but will be
constrained by physical & economic
limits (density, power, cost)
Memory exploits parallel universes. Create &
process superposition of all 2N configurations
at once. N > 300 qubits provide more storage
than there are particles in the known Universe
Speed
1018 FLOPS
Potential to be fast but runs at 0 FLOPS
© 2013 D-Wave Systems Inc. All Rights Reserved
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11. Will QCs Make HPCs Obsolete?
• Probably not . . .
• They’re suited to different tasks
– HPCs: Computational fluid dynamics, molecular
simulation, weather forecasting, nuclear weapons
modeling, etc.
– QCs: discrete combinatorial optimization, artificial
intelligence, machine learning, sampling
• But together they can enhance each other
© 2013 D-Wave Systems Inc. All Rights Reserved
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13. How Quantum Annealing Works
• Space of solutions
defines and energy
landscape & best
solution is lowest valley
• Classical algorithms can
only walk over this
landscape
• Quantum annealing can
tunnel through the
landscape
© 2013 D-Wave Systems Inc. All Rights Reserved
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16. Cooling
• Closed cycle dilution
refrigerator (“fridge”)
• Fridge + servers
consume 15.5kW
• Power demand will
remain constant as we
scale up to thousands of
qubits
© 2013 D-Wave Systems Inc. All Rights Reserved
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17. Processor Environment
• 192 lines from room
temperature to chip
• 10kg cooled to 0.02K
• 150x colder than
interstellar space
• Shielded room excludes
external RF
• Magnetic field < 10−9 Tesla
across chip
• 50,000x weaker than
Earth’s field
• Isolated from vibrations
© 2013 D-Wave Systems Inc. All Rights Reserved
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20. Processor Architecture
Physical Layout
Physical Unit Cell
Wiring layout
• 8 8 array of 8-qubit unit cells
• Within each unit cell each
vertical qubit is coupled to
each horizontal qubit
• Vertical (horizontal) qubit
coupled to corresponding
qubit in vertical (horizontal)
neighboring cells
Logical Layout
Logical Unit Cell
q1
q2
q5
q6
q3
q7
q4
q8
Topology of interconnect network
© 2013 D-Wave Systems Inc. All Rights Reserved
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• Non-planarity of interconnect
network makes the problem of
finding the lowest energy state
of the qubits NP-hard
• NP-Hardness guarantees you
can map many practical
problems to the architecture
21. Programming Languages
• User does not need to know anything
about quantum physics
– Just pass a matrix of hi’s and Jij’s to the machine
• Currently have interfaces for:
– Python
– Matlab
– C/C++
© 2013 D-Wave Systems Inc. All Rights Reserved
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23. A Strategy for Integrating QC with HPC
• HPCs excel at large scale numerical simulations
• QCs excel at discrete combinatorial optimization
• Can we use a HPC + QC for engineering design optimization?
• Problem setup …
– Suppose engineering design is specified by a bit string
– Various designs can be “scored” by running some HPC simulation
– Goal is to find the bit string whose score meets design criteria
© 2013 D-Wave Systems Inc. All Rights Reserved
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24. Division of Labor
• HPC’s job
– Map bit string to design; simulate design; score the result; send score to QC
• QC’s job
– use sequence of bit string/score pairs to tweak the h’s and J’s in the QMI so
that it will yield samples that correctly mimic the ordering of energies of
solutions in the neighborhood of the highest scoring bit string
– Yields a new QMI
– Run new QMI many times to yield new candidates (~104 solutions/sec)
– HPC scores the candidate solutions and returns scores to QC
– Iterate until design meets desired criteria
© 2013 D-Wave Systems Inc. All Rights Reserved
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25. Quantum-Accelerated HPC
• Using the QC + HPC together allows faster convergence on
optimal design than is attainable by using HPC alone
• Avoids unnecessary HPC cycles & power consumption
– Increases availability of HPC for running other computations
– Works best when cost of running the HPC simulator is high
• Supercomputer + quantum computer
Better “guesses”
“Scores” for the guesses
Quantum-Accelerated HPC
© 2013 D-Wave Systems Inc. All Rights Reserved
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26. Why Does it Work?
• Imagine you’ve reached an intermediate point in design space
and want to pick the next bit string to try
• Classical methods only sense the local neighborhood
• Quantum methods have potential for greater horizon
• Make a better next move possibly leading in different direction
Quantum
Discrepancy
Discrepancy
Classical
Design Parameter
© 2013 D-Wave Systems Inc. All Rights Reserved
Design Parameter
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28. Another Example: Radiotherapy Optimization
PROBLEM:
Deliver lethal dose to tumor whilst
minimizing damage to healthy
tissues
APPROACH:
Hybrid: QC + Conventional Computer
• Design = bit string
• Quality = result of running extensive
radiation transport simulation
• D-Wave system learns from
simulations to predict better designs
IMPACT:
• Hybrid quantum-classical design found a radiation
therapy treatment that minimized the objective
function to 70.7 c.f. 120.0 for tabu, and ran in 1/3
the time making fewer calls to radiation transport
© 2013 D-Wave Systems Inc. All Rights Reserved
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simulation
29. Conclusions
• We see quantum computing as a new
resource for HPC
• Technology scaling faster than Moore’s Law
• 1,024-qubit quantum computer by mid-2014
• Performance is encouraging
• Many potential uses in combinatorial optimization, engineering
design optimization, A.I., machine learning & sampling
• Seeking early adopters to explore QC-HPC synergy
Email: cpwilliams@dwavesys.com
© 2013 D-Wave Systems Inc. All Rights Reserved
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