arXiv subjects

Nikola Vuk Maruszewski

Publications and source records attributed to Nikola Vuk Maruszewski.

3 recordsLinked to original sources

arXiv2026

SEQC: Stratify-Elaborate Quantum Compilation Towards Modular Hybrid Architectures

As quantum computing technology matures, the pursuit of performance and scalability has led to the widespread adoption of modular quantum architectures. We expect that the next stage of technological evolution will integrate multiple qubit modalities into these systems, producing hybrid, modular quantum architectures. However, the complexity of hybrid, modular quantum devices, coupled with their growing sizes, presents an imminent scalability challenge for quantum compilation. Existing qubit allocation methods are often unable to contend with inter-module links, which do not necessarily support a universal basis gate set. Furthermore, these algorithms are typically not designed for qubit links of significantly varying latency or fidelity. In this work, we propose SEQC, a hierarchical parallelized compilation pipeline optimized for modular quantum systems, including several novel methods for qubit placement, qubit routing, and circuit optimization. SEQC attains a 9.3-32.3% average increase in circuit fidelity (49.99-63.36% max), depending on the chiplet size and topology. Additionally, owing to its ability to parallelize compilation, SEQC achieves 1.34-3.27$\times$ faster compilation on average (3.37-6.74$\times$ max) over a chiplet-unaware Qiskit baseline.

quant-ph↗

arXiv2026

Magnetic Tunnel Junctions for Timekeeping in Intermittent Computing Systems

Batteryless intermittent systems run unattended for years, but power failures erase timekeeping state, corrupting sensing, scheduling, and coordination. State-of-the-art timekeepers infer elapsed time from capacitor discharge; however, the capacitor must be sized for the longest interval measured (so range, energy, and area grow together), and repeated charge-discharge cycling lowers capacitance over time, biasing every estimate further as the deployment ages. We present FLINT, a timekeeper that reads elapsed time from the stochastic retention loss of an array of "broken" Magnetic Tunnel Junctions (MTJs)---spintronic memory cells engineered to lose state predictably. Because the decay timescale is fixed by device geometry, the energy to read it is independent of the interval measured and does not drift with device age. We validate FLINT's array model against 21 fabricated MTJs, then evaluate the full timekeeper in real-device-trace-driven simulation, showing that it tracks over 15 minutes of off-time within 10% error while consuming only 1.03 $μJ$ and occupying under 0.1 $mm^2$---$9.2\times$ the range at $11\times$ lower energy than prior work. It extends to longer intervals at no added cost, and makes $16-52\times$ fewer scheduling errors than an aging capacitor clock over a one-year deployment.

cs.AR↗

arXiv2025

Improved Prefetching Techniques for Linked Data Structures

With ever-increasing main memory stall times, we need novel techniques to reduce effective memory access latencies. Prefetching has been shown to be an effective solution, especially with contiguous data structures that follow the traditional principles of spatial and temporal locality. However, on linked data structures$-$made up of many nodes linked together with pointers$-$typical prefetchers struggle, failing to predict accesses as elements are arbitrarily scattered throughout memory and access patters are arbitrarily complex and hence difficult to predict. To remedy these issues, we introduce $\textit{Linkey}$, a novel prefetcher that utilizes hints from the programmer/compiler to cache layout information and accurately prefetch linked data structures. $\textit{Linkey}$ obtains substantial performance improvements over a striding baseline. We achieve a geomean 13% reduction in miss rate with a maximum improvement of 58.8%, and a 65.4% geomean increase in accuracy, with many benchmarks improving from 0%. On benchmarks where $\textit{Linkey}$ is applicable, we observe a geomean IPC improvement of 1.40%, up to 12.1%.

cs.AR↗