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Researcher profile

Giovanni De Micheli

Giovanni De Micheli contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
Logic in Computer Sciencequant-phEmerging TechnologiesArtificial IntelligenceHardware ArchitectureMachine LearningMathematical SoftwareSoftware Engineering

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Published work

7 published item(s)

preprint2026arXiv

TRAM: Training Approximate Multiplier Structures for Low-Power AI Accelerators

Reducing power consumption in AI accelerators is increasingly important. Approximate computing can reduce power consumption while keeping the accuracy loss small. Since multipliers are power-hungry components in AI models, this paper focuses on synthesizing low-power approximate multipliers (AxMs). Unlike prior works that design AxMs separately from AI model training, we present TRAM, which jointly optimizes the AxM structure and AI model parameters to lower power with small accuracy loss. Experiments show that compared to state-of-the-art AxMs, TRAM achieves up to 25.05% AxM power reduction on CNNs with CIFAR-10, and reduces power by up to 27.09% on vision transformers with ImageNet.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

An Automated Testing and Debugging Toolkit for Gate-Level Logic Synthesis Applications

Correctness and robustness are essential for logic synthesis applications, but they are often only tested with a limited set of benchmarks. Moreover, when the application fails on a large benchmark, the debugging process may be tedious and time-consuming. In some fields such as compiler construction, automatic testing and debugging tools are well-developed to support developers and provide minimal guarantees on program quality. In this paper, we adapt fuzz testing and delta debugging techniques and specialize them for gate-level netlists commonly used in logic synthesis. Our toolkit improves over similar tools specialized for the AIGER format by supporting other gate-level netlist formats and by allowing a tight integration to provide 10x speed-up. Experimental results show that our fuzzer captures defects in mockturtle, ABC, and LSOracle with 10x smaller testcases and our testcase minimizer extracts minimal failure-inducing cores using 2x fewer oracle calls.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Efficient Deterministic Preparation of Quantum States Using Decision Diagrams

Loading classical data into quantum registers is one of the most important primitives of quantum computing. While the complexity of preparing a generic quantum state is exponential in the number of qubits, in many practical tasks the state to prepare has a certain structure that allows for faster preparation. In this paper, we consider quantum states that can be efficiently represented by (reduced) decision diagrams, a versatile data structure for the representation and analysis of Boolean functions. We design an algorithm that utilises the structure of decision diagrams to prepare their associated quantum states. Our algorithm has a circuit complexity that is linear in the number of paths in the decision diagram. Numerical experiments show that our algorithm reduces the circuit complexity by up to 31.85% compared to the state-of-the-art algorithm, when preparing generic $n$-qubit states with different degrees of non-zero amplitudes. Additionally, for states with sparse decision diagrams, including the initial state of the quantum Byzantine agreement protocol, our algorithm reduces the number of CNOTs by 86.61% $\sim$ 99.9%.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

The EPFL Logic Synthesis Libraries

We present a collection of modular open source C++ libraries for the development of logic synthesis applications. These libraries can be used to develop applications for the design of classical and emerging technologies, as well as for the implementation of quantum compilers. All libraries are well documented and well tested. Furthermore, being header-only, the libraries can be readily used as core components in complex logic synthesis systems.

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preprint2020arXiv

ROS: Resource-constrained Oracle Synthesis for Quantum Computers

We present a completely automatic synthesis framework for oracle functions, a central part in many quantum algorithms. The proposed framework for resource-constrained oracle synthesis (ROS) is a LUT-based hierarchical method in which every step is specifically tailored to address hardware resource constraints. ROS embeds a LUT mapper designed to simplify the successive synthesis steps, costing each LUT according to the resources used by its corresponding quantum circuit. In addition, the framework exploits a SAT-based quantum garbage management technique. Those two characteristics give ROS the ability to beat the state-of-the-art hierarchical method both in number of qubits and in number of operations. The efficiency of the framework is demonstrated by synthesizing quantum oracles for Grover's algorithm.

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preprint2020arXiv

Simulation-Guided Boolean Resubstitution

This paper proposes a new logic optimization paradigm based on circuit simulation, which reduces the need for Boolean computations such as SAT-solving or constructing BDDs. The paper develops a Boolean resubstitution framework to demonstrate the effectiveness of the proposed approach. Methods to generate highly expressive simulation patterns are developed, and the generated patterns are used in resubstitution for efficient filtering of potential resubstitution candidates to reduce the need for SAT validation. Experimental results show that improvements in circuit size reduction were achieved by up to 74%, compared to a state-of-the-art resubstitution algorithm.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Using ZDDs in the Mapping of Quantum Circuits

A critical step in quantum compilation is the transformation of a technology-independent quantum circuit into a technology-dependent form for a targeted device. In addition to mapping quantum gates into the supported gate set, it is necessary to map pseudo qubits in the technology-independent circuit into physical qubits of the technology-dependent circuit such that coupling constraints among qubits acting in multiple-qubit gates are satisfied. It is usually not possible to find such a mapping without adding SWAP gates into the circuit. To cope with the technical limitations of NISQ-era quantum devices, it is advantageous to find a mapping that requires as few additional gates as possible. The large search space of possible mappings makes this task a difficult combinatorial optimization problem. In this work, we demonstrate how zero-suppressed decision diagrams (ZDDs) can be used for typical implementation tasks in quantum mapping algorithms. We show how to maximally partition a quantum circuit into blocks of adjacent gates, and if adjacent gates within a circuit do not share common mapping permutations, we attempt to combine them using parallelized SWAP operations represented in a ZDD. Boundaries for the partitions are formed where adjacent gates are unable to be combined. Within each partition block, ZDDs represent all possible mappings of pseudo qubits to physical qubits.

0 citations0 reviewsNo code linkedOpen access