19 research outputs found
Optimized Surface Code Communication in Superconducting Quantum Computers
Quantum computing (QC) is at the cusp of a revolution. Machines with 100
quantum bits (qubits) are anticipated to be operational by 2020
[googlemachine,gambetta2015building], and several-hundred-qubit machines are
around the corner. Machines of this scale have the capacity to demonstrate
quantum supremacy, the tipping point where QC is faster than the fastest
classical alternative for a particular problem. Because error correction
techniques will be central to QC and will be the most expensive component of
quantum computation, choosing the lowest-overhead error correction scheme is
critical to overall QC success. This paper evaluates two established quantum
error correction codes---planar and double-defect surface codes---using a set
of compilation, scheduling and network simulation tools. In considering
scalable methods for optimizing both codes, we do so in the context of a full
microarchitectural and compiler analysis. Contrary to previous predictions, we
find that the simpler planar codes are sometimes more favorable for
implementation on superconducting quantum computers, especially under
conditions of high communication congestion.Comment: 14 pages, 9 figures, The 50th Annual IEEE/ACM International Symposium
on Microarchitectur
Architecting Noisy Intermediate-Scale Trapped Ion Quantum Computers
Trapped ions (TI) are a leading candidate for building Noisy
Intermediate-Scale Quantum (NISQ) hardware. TI qubits have fundamental
advantages over other technologies such as superconducting qubits, including
high qubit quality, coherence and connectivity. However, current TI systems are
small in size, with 5-20 qubits and typically use a single trap architecture
which has fundamental scalability limitations. To progress towards the next
major milestone of 50-100 qubits, a modular architecture termed the Quantum
Charge Coupled Device (QCCD) has been proposed. In a QCCD-based TI device,
small traps are connected through ion shuttling. While the basic hardware
components for such devices have been demonstrated, building a 50-100 qubit
system is challenging because of a wide range of design possibilities for trap
sizing, communication topology and gate implementations and the need to match
diverse application resource requirements.
Towards realizing QCCD systems with 50-100 qubits, we perform an extensive
architectural study evaluating the key design choices of trap sizing,
communication topology and operation implementation methods. We built a design
toolflow which takes a QCCD architecture's parameters as input, along with a
set of applications and realistic hardware performance models. Our toolflow
maps the applications onto the target device and simulates their execution to
compute metrics such as application run time, reliability and device noise
rates. Using six applications and several hardware design points, we show that
trap sizing and communication topology choices can impact application
reliability by up to three orders of magnitude. Microarchitectural gate
implementation choices influence reliability by another order of magnitude.
From these studies, we provide concrete recommendations to tune these choices
to achieve highly reliable and performant application executions.Comment: Published in ISCA 2020 https://www.iscaconf.org/isca2020/program/
(please cite the ISCA version
Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions
Computational models are an essential tool for the design, characterization,
and discovery of novel materials. Hard computational tasks in materials science
stretch the limits of existing high-performance supercomputing centers,
consuming much of their simulation, analysis, and data resources. Quantum
computing, on the other hand, is an emerging technology with the potential to
accelerate many of the computational tasks needed for materials science. In
order to do that, the quantum technology must interact with conventional
high-performance computing in several ways: approximate results validation,
identification of hard problems, and synergies in quantum-centric
supercomputing. In this paper, we provide a perspective on how quantum-centric
supercomputing can help address critical computational problems in materials
science, the challenges to face in order to solve representative use cases, and
new suggested directions.Comment: 60 pages, 14 figures; comments welcom
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ScaffCC: Scalable compilation and analysis of quantum programs
Abstract We present ScaffCC, a scalable compilation and analysis framework based on LLVM (Lattner and Adve, 2004), which can be used for compiling quantum computing applications at the logical level. Drawing upon mature compiler technologies, we discuss similarities and differences between compilation of classical and quantum programs, and adapt our methods to optimizing the compilation time and output for the quantum case. Our work also integrates a reversible-logic synthesis tool in the compiler to facilitate coding of quantum circuits. Lastly, we present some useful quantum program analysis scenarios and discuss their implications, specifically with an elaborate discussion of timing analysis for critical path estimation. Our work focuses on bridging the gap between high-level quantum algorithm specifications and low-level physical implementations, while providing good scalability to larger and more interesting problem