arXiv subjects

Yutao Xu

Publications and source records attributed to Yutao Xu.

3 recordsLinked to original sources

arXiv2026

Real-space imaging reveals symmetry-selected nonlinear energy routing in a mechanical resonator

Nonlinear energy routing among modes underlies phenomena ranging from internal resonance and wave mixing to frequency-comb generation in micro- and nanoelectromechanical resonators, yet modal interactions are typically inferred from spectra rather than imaged in real space. This leaves unresolved how energy is spatially routed and what determines which pathways are selected. Here, we use phase-locked multi-harmonic stroboscopic interferometry to reconstruct harmonic-resolved differential displacement maps in a nearly mirror-symmetric microelectromechanical resonator. These maps reveal that harmonics generated by a driven mode can be carried by distinct spatial eigenmodes, directly resolving pathways of nonlinear energy transfer. We further show that such mode-selective routing occurs even away from integer frequency matching: generated harmonics are dominated by eigenmodes sharing the driven mode's mirror parity, whereas spectrally closer opposite-parity modes remain strongly suppressed. A nonlinear modal framework links this hierarchy to symmetry-dependent modal-overlap integrals. These results identify spatial symmetry as a selection rule for nonlinear energy routing.

physics.optics↗

arXiv2024

Efficient LLM inference solution on Intel GPU

Transformer based Large Language Models (LLMs) have been widely used in many fields, and the efficiency of LLM inference becomes hot topic in real applications. However, LLMs are usually complicatedly designed in model structure with massive operations and perform inference in the auto-regressive mode, making it a challenging task to design a system with high efficiency. In this paper, we propose an efficient LLM inference solution with low latency and high throughput. Firstly, we simplify the LLM decoder layer by fusing data movement and element-wise operations to reduce the memory access frequency and lower system latency. We also propose a segment KV cache policy to keep key/value of the request and response tokens in separate physical memory for effective device memory management, helping enlarge the runtime batch size and improve system throughput. A customized Scaled-Dot-Product-Attention kernel is designed to match our fusion policy based on the segment KV cache solution. We implement our LLM inference solution on Intel GPU and publish it publicly. Compared with the standard HuggingFace implementation, the proposed solution achieves up to 7x lower token latency and 27x higher throughput for some popular LLMs on Intel GPU.

cs.AR↗

arXiv2022

Test Case Prioritization Using Partial Attention

Test case prioritization (TCP) aims to reorder the regression test suite with a goal of increasing the fault detection rate. Various TCP techniques have been proposed based on different prioritization strategies. Among them, the greedy-based techniques are the most widely-used TCP techniques. However, existing greedy-based techniques usually reorder all candidate test cases in prioritization iterations, resulting in both efficiency and effectiveness problems. In this paper, we propose a generic partial attention mechanism, which adopts the previous priority values (i.e., the number of additionally-covered code units) to avoid considering all candidate test cases. Incorporating the mechanism with the additional-greedy strategy, we implement a novel coverage-based TCP technique based on partition ordering (OCP). OCP first groups the candidate test cases into different partitions and updates the partitions on the descending order. We conduct a comprehensive experiment on 19 versions of Java programs and 30 versions of C programs to compare the effectiveness and efficiency of OCP with six state-of-the-art TCP techniques: total-greedy, additional-greedy, lexicographical-greedy, unify-greedy, art-based, and search-based. The experimental results show that OCP achieves a better fault detection rate than the state-of-the-arts. Moreover, the time costs of OCP are found to achieve 85%-99% improvement than most state-of-the-arts.

cs.SE↗