EPiQC: Enabling Practical-scale Quantum Computing Fred Chong Seymour Goodman Professor Department of Computer Science University of Chicago
Lead PI, the EPiQC Project, an NSF Expedition in Computing (1730449)
With Ken Brown, Ike Chuang, Diana Franklin, Danielle Harlow, Aram Harrow, Andrew Houck, Margaret Martonosi, John Reppy, David Schuster, & Peter Shor (UChicago, MIT, Princeton, Duke, UCSB) The Algorithms to Machines Gap
1000000 Grovers Algorithm (Database search) 100000 #Qubits Needed Shor’s Factoring Alg. (Crypto) 10000
#Qubits 1000 #Qubits Buildable 100 Gap!
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1 1995 2000 2005 2010 2015 2020 2025 Year
2 The Algorithms to Machines Gap
1000000 Grovers Algorithm (Database search) 100000 #Qubits Needed Shor’s Factoring Alg. (Crypto) 10000 Quantum Sim, Q Chem, #Qubits 1000 QAOA #Qubits Buildable 100 Gap!
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1 1995 2000 2005 2010 2015 2020 2025 Year
3 The Algorithms to Machines Gap
1000000 Grovers Algorithm (Database search) 100000 #Qubits Needed Shor’s Factoring Alg. (Crypto) 10000 Quantum Sim, Q Chem, Co-Design #Qubits 1000 QAOA #Qubits Buildable 100 Gap!
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1 1995 2000 2005 2010 2015 2020 2025 Year
4 Closing the Gap: Software-Enabled Vertical Integration and Co-Design
1000000 Grovers Algorithm (Database search) Algorithms 100000 Shor’s Factoring Alg. (Crypto) Prog Lang 10000 Quantum Sim, Compiler Q Chem, Co-Design 1000 QAOA Architecture
100 Gap! Modeling Devices 10
1 1995 2000 2005 2010 2015 2020 2025 Year Goal Develop co-designed algorithms, SW, and HW to close the gap between algorithms and devices by 100-1000X, accelerating QC by 10-20 years.
1000000 Grovers Algorithm (Database search) Algorithms 100000
Shor’s Factoring Alg. (Crypto) Prog Lang Co
10000 - Quantum Sim, Result: Compiler Design Q Chem, Crossover 1000 QAOA by 2023! Architecture
100 Gap! Modeling Devices 10
1 1995 2000 2005 2010 2015 2020 2025 Year Research Thrusts and Outcomes
Thrust Tasks and Topics Outcomes
Algorithms and Theory Minimizing measurements for quantum chemistry 8-30X fewer measurements Simulating large circuits on a small quantum computer Trade time for qubits
Quantum supremacy, no go results Guide Benchmarks
Technology-Aware Direct-to-pulse compilation (ASPLOS19) Up to 10X lower time Programming Environment Noise-adaptive mapping and scheduling (ASPLOS19, ISCA19) Up to 28X reliability Qutrit circuits (QIP19 best poster, ISCA19) Up to 70X fewer devices
Technology Aware Error Correction (stabilizer slicing, PRL18) ~90X reliability Verification and Quantum statistical assertion checking (ISCA19) Support QC SW and Modeling Systems development at Best practices in QC programming (Plateau18) practical scales. Compression for QC simulations (59 qubit Grover’s, SC19) Education and Book and upcoming MITx course Create a QC CS Outreach Discipline. Knowledge Industry summit upcoming in June 2019 (FCRC); algorithms in IBM QISKit and Intel QS transfer to companies Simulator and other universities. Open-source SW and Tutorials (100’s participants, 1000’s downloads, 1000’s youtube views) Zines, Museum collaborations, K-12 Learning Trajectories 7 Research Thrusts and Outcomes
Thrust Tasks and Topics Outcomes
Algorithms and Theory Minimizing measurements for quantum chemistry 8-30X fewer measurements Simulating large circuits on a small quantum computer Trade time for qubits
Quantum supremacy, no go results Guide Benchmarks
Technology-Aware Direct-to-pulse compilation (ASPLOS19) Up to 10X lower time Programming Environment Noise-adaptive mapping and scheduling (ASPLOS19, ISCA19) Up to 28X reliability Qutrit circuits (QIP19 best poster, ISCA19) Up to 70X fewer devices
Technology Aware Error Correction (stabilizer slicing, PRL18) ~90X reliability Verification and Quantum statistical assertion checking (ISCA19) Support QC SW and Modeling Systems development at Best practices in QC programming (Plateau18) practical scales. Data compression for QC simulations (61 qubit Grover’s, SC19) Education and Book and upcoming MITx course Create a QC CS Outreach Discipline. Knowledge Industry summit upcoming in June 2019 (FCRC); algorithms in IBM QISKit and Intel QS transfer to companies Simulator and other universities. Open-source SW and Tutorials (100’s participants, 1000’s downloads, 1000’s youtube views) Zines, Museum collaborations, K-12 Learning Trajectories 8 Direct-to-Pulse Compilation
n Optimized Compilation of Aggregated Instructions for Realistic Quantum Computers, Yunong Shi, Nelson Leung, Pranav Gokhale, Zane Rossi, David I. Schuster, Henry Hoffman, Frederic T. Chong, 24th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS '19)
11:31 9 Aggregated Instructions for Optimal Control QAOA Example More Parallel More Serial Aggregation Summary
n Breaks ISA abstraction n Up to 10X latency reduction, mean 6X n Especially useful for swaps n Future work:
q Alternatives to GRAPE to allow larger aggregates
q Better noise models
q Better calibration methods
q Experimental demonstrations Noise-Adaptive Compilation
n Noise-Adaptive Compiler Mappings for Noisy Intermediate-Scale Quantum Computers, Prakash Murali, Jonathan M. Baker, Ali Javadi- Abhari, Frederic T. Chong, and Margaret Martonosi. 24th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS '19) n Full-Stack, Real-System Quantum Computer Studies: Technology Comparisons and Architectural Insights, Prakash Murali, Norbert Matthias Linke, Margaret Martonosi, Ali Javadi-Abhari, Nhung Hong Nguyen, Cinthia Huerta Alderete, 46th Annual International Symposium on Computer Architecture (ISCA), Phoenix, AZ, 2019
14 Noise-Adaptive Compiler Mappings
n SMT solver optimization for qubit and link variations in physical machines n IBM Q Experience machines Example: Avoid Error-Prone Links Success Rate Improvement on IBMQ14 Real-system runs with 8192 trials per run
IBMQ14 1 0.8 0.6 0.4 0.2 0 BV4 BV6 BV8 HS2 HS4 HS6 Toffoli Fredkin Or Peres QFT Adder
MeasuredRate Success Qiskit TriQ-1QOptC TriQ-1QOptCN • IBM Qiskit v0.7: lexicographic qubit mapping, randomized swapping heuristic • TriQ-1QOptC = optimize communication + 1Q gates • TriQ-1QOptCN = optimize noise + communication + 1Q gates • Geomean 3X, up to 28X improvement in measured success rate Noise-Adaptive Summary
n Up to 28X better reliability (2.9X mean) n Improves compile time by optimizing independent gate rather than total reliability n Better than native IBM, Rigetti, and UMD SW
q Allows comparison of machines n Future work: integrate pulse optimization, other optimizations Qutrits instead of Ancilla
n Asymptotic Improvements to Quantum Circuits via Qutrits, Pranav Gokhale, Jonathan Baker, Casey Duckering, Natalie Brown, Ken Brown, and Frederic T. Chong. International Symposium on Computer Architecture (ISCA19) (QIP Best Poster)
19 Qutrits Instead of Ancilla
• Uses qutrit |2> state instead of external ancilla • Input and output are binary—|2> state is only intermediary • Asymptotically lower depth. Large constant advantage for gate count.
15-control Toffoli U applied to target iff all controls are 1 Fidelity Results Qutrit Summary n Fewer qubits needed
q Up to 70X reduction in ancilla n Plus better reliability
q Substantially better for superconducting qubits
q Slightly better for trapped ions n Future work:
q Better noise simulations
q Pulse implementations of more efficient qutrit operators
q High-level synthesis of qutrit circuits with algorithm restructuring
q Experimental demonstrations and noise charactrization
22 Quantum Circuit Simulation using Data Compression
n Full-state quantum circuit simulation by using data compression, Xin-Chuan Wu, Sheng Di, Emma Maitreyee Dasgupta, Franck Cappello, Hal Finkel, Yuri Alexeev, and Frederic T. Chong. SC 2019.
23 Simulations on ANL Theta 4392 64-core Xeon Phi
24 Simulation Summary
n Compression ratio: 4.85x ~ 82,600x
q Increasing the number of qubits in the simulation: log2(4.85) ~ log2(82600) q +2 ~ 16 qubits n Future work:
q Add noise simulation
q Combine with other techniques
11:31 25 OPEN PROBLEMS
26 How do I know if my QC program is correct?
n Check implementation against a formal specification n Checks based on programmer assertions (on HW or simulation) n Provably correct compilation
q Contract-based verification of QISkit n Can we check useful properties in polynomial time for programs with quantum supremacy? Program Synthesis by Sketching
[Solar-Lezama ASPLOS 06]
11:31 29 What are the right abstractions?
n Specification Languages Algorithms
q Coq, Hamiltonians Prog Lang n Programming Languages Compiler q Scaffold, Quipper, Q#, Quil … n Instruction-Set Architectures Architecture q OpenQASM Modeling n Physical Control Devices q OpenPulse
30 Specialization vs Abstraction
Gap? Short-term SW Long-term SW
100 1000 10000 100000
qubits
11:31 31 STAQ: Software-Tailored Architecture for Quantum co-design
Ken Brown, Lead PI Fred Chong Jungsang Kim Akimasa Miyake Software Stack Peter Love Alexey Gorshkov Aram Harrow Chris Monroe Harmut Haeffner
Applications Hardware Summary n Compiler techniques will be critical to QC progress n Need to expose and model physical properties n Need your help! n More info: epiqc.cs.uchicago.edu
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