Abstract:

Quantum computing promises exponential speedups for an important class of problems. While quantum computers with few dozens of qubits have been demonstrated, these machines suffer from high rate of gate errors. Such machines are operated in the Noisy Intermediate Scale Quantum (NISQ) mode of computing where the output of the machine can be erroneous. In this talk, I will discuss some of our recent work that aims to improve the reliability of NISQ computers by developing software techniques to mitigate the hardware errors. Our first= work (ASPLOS 2019) exploits the variability in the error rates of qubits to steer more operations towards qubits with lower error rates and avoid qubits that are error-prone. Our second work (MICRO 2019) looks at executing different versions of the programs each crafted to cause diverse mistakes so that the machine becomes less vulnerable to correlated errors. Our third work (MICRO 2019) looks at exploiting the state-dependent bias in measurement errors (state 1 is more error prone than state 0) and dynamically flips the state of the qubit to perform the measurement in the stronger state. We perform our evaluations on real quantum machines from IBM and demonstrate significant improvement in the overall system reliability. If time permits, I will also briefly discuss the hardware aspect of designing quantum computers, including cryogenic processor and cryogenic memory system.