Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric

Dousti, Mohammad Javad; Pedram, Massoud

doi:10.1109/date.2012.6176612

Cited by 25 publications

(37 citation statements)

References 11 publications

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“…The MITAB uses a modified version of QPOS [34] to schedule the netlist on the layout. It outperforms other tools such as QUFD [36] and QSPR [35] in terms of latency.…”

Section: Scheduled Layout Generationmentioning

confidence: 94%

“…Metodi et al [34] presented a physical operations scheduler (QPOS) which takes a description of a circuit and a definite physical layout and produces a sequence of operations which indicates the required communication and possible parallelism in the circuit. Dousti et al [35] presented an algorithm for scheduling, placement of qubits and routing of a quantum circuit which decreases the circuit latency. They developed an iterative heuristic approach for placement based on forward and backward computations in a quantum instruction dependency graph (QIDG).…”

Section: Physical Design In Ion Trap Technologymentioning

confidence: 99%

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Physical synthesis of quantum circuits using templates

Mirkhani

Mohammadzadeh

2016

Quantum Inf Process

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Similar to traditional CMOS circuits, quantum circuit design flow is divided into two main processes: logic synthesis and physical design. Addressing the limitations imposed on optimization of the quantum circuit metrics because of no information sharing between logic synthesis and physical design processes, the concept of "physical synthesis" was introduced for quantum circuit flow, and a few techniques were proposed for it. Following that concept, in this paper a new approach for physical synthesis inspired by template matching idea in quantum logic synthesis is proposed to improve the latency of quantum circuits. Experiments show that by using template matching as a physical synthesis approach, the latency of quantum circuits can be improved by more than 23.55 % on average.

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“…The MITAB uses a modified version of QPOS [34] to schedule the netlist on the layout. It outperforms other tools such as QUFD [36] and QSPR [35] in terms of latency.…”

Section: Scheduled Layout Generationmentioning

confidence: 94%

Section: Physical Design In Ion Trap Technologymentioning

confidence: 99%

Physical synthesis of quantum circuits using templates

Mirkhani

Mohammadzadeh

2016

Quantum Inf Process

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“…Chisel-Q performs simple optimizations to reduce the number of generated ancillas, as detailed below. In addition, we assume that the generated QASM will be subsequently fed through synthesis tools [17], physical design tools [18,19], or other optimization tools since it is in a standard format.…”

Section: Chisel-q Optimization Approachmentioning

confidence: 99%

Chisel-Q: Designing quantum circuits with a scala embedded language

Liu

Kubiatowicz

2013

2013 IEEE 31st International Conference on Computer Design (ICCD)

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Abstract-We introduce Chisel-Q, a high-level functional language for generating quantum circuits. Chisel-Q permits quantum computing algorithms to be constructed using the metalanguage features of Scala and its embedded DSL Chisel. With Chisel-Q, designers of quantum computing algorithms gain access to high-level, modern language features and abstractions. We describe a synthesis flow that transforms Chisel-Q into an explicit quantum circuit in the Quantum Assembly Language (QASM) format. We also discuss several optimizations to reduce the generated hardware cost. The Chisel-Q tool includes resource and performance estimation which can be used to compare different implementations of the same functionality. We compare the output of the generic Chisel-Q synthesis flow with hand-tuned versions of well-known quantum circuits. . Although practical quantum computers are still on the horizon, research progress is steady: over the last decade, physicists have investigated a number of approaches to implementing quantum circuits [5,6], computer architects have investigated architectures for quantum computers [7,8], and mathematicians have explored how to express difficult computational problems as instances of quantum computing [9,10]. Unfortunately, techniques for expressing quantum algorithms are mostly limited to high-level mathematical expressions or low-level sequences of quantum gates [11]. More traditional programming languages have not yet surfaced that are capable of expressing and handling the idiosyncrasies of quantum computing. As a result, many of the time-honored techniques for abstraction, design, and debugging of classical algorithms are not available to the writer of quantum algorithms.

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“…For the baseline, a quantum scheduling, placement, and routing tool (called QSPR) [20] was used. QSPR was minimally modified to work on the tile-based architecture of Figure 1.…”

Section: Simulation Setupmentioning

confidence: 99%

Leqa

Dousti

Pedram

2013

Proceedings of the 50th Annual Design Automation Conference

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This paper presents LEQA, a fast latency estimation tool for evaluating the performance of a quantum algorithm mapped to a quantum fabric. The actual quantum algorithm latency can be computed by performing detailed scheduling, placement and routing of the quantum instructions and qubits in a quantum operation dependency graph on a quantum circuit fabric. This is, however, a very expensive proposition that requires large amounts of processing time. Instead, LEQA, which is based on computing the neighborhood population counts of qubits, can produce estimates of the circuit latency with good accuracy (i.e., an average of less than 3% error) with up to two orders of magnitude speedup for mid-size benchmarks. This speedup is expected to increase superlinearly as a function of circuit size (operation count).

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Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric

Cited by 25 publications

References 11 publications

Physical synthesis of quantum circuits using templates

Physical synthesis of quantum circuits using templates

Chisel-Q: Designing quantum circuits with a scala embedded language

Leqa

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