The intersection of Quantum Computing and Distributed Systems...
summary
Argues that NISQ machines need runtime-based quantum execution pushed nearer hardware (co‑located container runtimes) instead of remote gate loops, reducing latency and enabling adaptive feedback but introducing CPU/memory and security limits. Reports thousands–tens of thousands of shots per circuit, a 2019 lithium‑hydride run needing over a billion circuit operations and taking days, and qubits kept near 15 millikelvin. Describes using Ray and cost‑based scheduling across superconducting and ion‑trap hardware and proposes a quantum MapReduce style decomposition for parallelizing larger simulations.
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chapters (13)
- 0:00Intro
- 0:38What is Quantum Computing
- 7:56Use Cases
- 13:32Classical vs Quantum Interface
- 16:17Runtime Based Quantum Execution
- 18:32Scheduling Multiple Quantum Systems
- 20:02Scheduling on Quantum Hardware
- 21:37Scheduling on Classical Resources
- 23:17Scheduling Across Multiple Systems
- 24:22Scheduling Execution
- 25:27Moores Law
- 27:57Quantum MapReduce
- 29:07Objectbased API
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