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RWKV is a modern RNN architecture that approaches the performance of Transformers, with the advantage of processing long contexts at a linear memory cost. However, its sequential computation pattern struggles to efficiently leverage GPU…
This paper presents a novel load frequency control (LFC) design using integral-based decentralize fixed-order perturbed dynamic output tracking scheme in a delay dependent nonlinear interconnected multi-area power system via LMI approach.…
The European XFEL is a new research facility currently under construction at DESY in the Hamburg area in Germany. From 2015 on, it will generate extremely intense X-ray flashes that will be used by researchers from all over the world. The…
The commissioning and operation of future large-scale scientific experiments will challenge current tuning and control methods. Reinforcement learning (RL) algorithms are a promising solution thanks to their capability of autonomously…
To improve the control efficiency of Superconducting Electron Cyclotron Resonance Ion source(SECRAL) for Heavy Ion Research Facility in Lanzhou(HIRFL), a upgrade version of control system for SECRAL is designed and set up. The control…
Reinforcement learning (RL) has emerged as the de-facto paradigm for improving the reasoning capabilities of large language models (LLMs). We have developed RLAX, a scalable RL framework on TPUs. RLAX employs a parameter-server…
In this work, we demonstrate the deployment of a hardware-accelerated machine learning (ML) inference system integrated into a real-time processing at the DIII-D tokamak fusion reactor. The team has successfully deployed an AMD/Xilinx…
By using the dynamic reconfigurable transceiver in high speed interface design, designer can solve critical technology problems such as ensuring signal integrity conveniently, with lower error binary rate. In this paper, we designed a high…
The control of beam phase relative to the accelerating RF field within a superconducting cavity is important in many accelerator applications and is of particular importance for a free electron laser facility. As standard practice, the…
Measuring a qubit state is a fundamental yet error-prone operation in quantum computing. These errors can arise from various sources, such as crosstalk, spontaneous state transitions, and excitations caused by the readout pulse. Here, we…
Interferometric techniques are crucial for space-based gravitational wave detection, requiring a picometer-level stable optical bench, precise phasemeter, interstellar transponder low-light phase locking, and laser sideband communication.…
This work presents the design and preliminary performance of a highly-multiplexed superconducting detector readout. The readout system is implemented on the Xilinx ZCU111 RFSoC Evaluation Board. The current design uses 12% of the DSPs, 60%…
Superconducting radio-frequency (SRF) cavities coupled to transmon circuits have proven to be a promising platform for building high-coherence quantum information processors. An essential aspect of this realization involves designing high…
Large language model (LLM) serving faces the dual challenge of meeting strict user-specific service-level objectives (SLOs) while minimizing computational cost under dynamic, multi-task workloads. Existing approaches either rely on static…
The `Laser-hybrid Accelerator for Radiobiological Applications', LhARA, is conceived as a novel, uniquely-flexible facility dedicated to the study of radiobiology. The technologies demonstrated in LhARA, which have wide application, will be…
Atomic ions confined in multi-electrode traps have been proposed as a basis for scalable quantum information processing. This scheme involves transporting ions between spatially distinct locations by use of time-varying electric potentials…
Reinforcement Learning (RL) has become the most effective post-training approach for improving the capabilities of Large Language Models (LLMs). In practice, because of the high demands on latency and memory, it is particularly challenging…
One path to realizing systems of trapped atomic ions suitable for large-scale quantum computing and simulation is to create a two-dimensional array of ion traps. Interactions between nearest-neighbouring ions could then be turned on and off…
Machine learning model deployment for training and execution has been an important topic for industry and academic research in the last decade. Much of the attention has been focused on developing specific toolchains to support acceleration…
The evolution of wireless mobile networks towards cloudification, where Radio Access Network (RAN) functions can be hosted at either a central or distributed locations, offers many benefits like low cost deployment, higher capacity, and…