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Yuan Ruan

Publications and source records attributed to Yuan Ruan.

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CtrlFuse: Mask-Prompt Guided Controllable Infrared and Visible Image Fusion

Infrared and visible image fusion generates all-weather perception-capable images by combining complementary modalities, enhancing environmental awareness for intelligent unmanned systems. Existing methods either focus on pixel-level fusion while overlooking downstream task adaptability or implicitly learn rigid semantics through cascaded detection/segmentation models, unable to interactively address diverse semantic target perception needs. We propose CtrlFuse, a controllable image fusion framework that enables interactive dynamic fusion guided by mask prompts. The model integrates a multi-modal feature extractor, a reference prompt encoder (RPE), and a prompt-semantic fusion module (PSFM). The RPE dynamically encodes task-specific semantic prompts by fine-tuning pre-trained segmentation models with input mask guidance, while the PSFM explicitly injects these semantics into fusion features. Through synergistic optimization of parallel segmentation and fusion branches, our method achieves mutual enhancement between task performance and fusion quality. Experiments demonstrate state-of-the-art results in both fusion controllability and segmentation accuracy, with the adapted task branch even outperforming the original segmentation model.

cs.CV

MIMS: Towards a Message Interface based Memory System

Memory system is often the main bottleneck in chipmultiprocessor (CMP) systems in terms of latency, bandwidth and efficiency, and recently additionally facing capacity and power problems in an era of big data. A lot of research works have been done to address part of these problems, such as photonics technology for bandwidth, 3D stacking for capacity, and NVM for power as well as many micro-architecture level innovations. Many of them need a modification of current memory architecture, since the decades-old synchronous memory architecture (SDRAM) has become an obstacle to adopt those advances. However, to the best of our knowledge, none of them is able to provide a universal memory interface that is scalable enough to cover all these problems. In this paper, we argue that a message-based interface should be adopted to replace the traditional bus-based interface in memory system. A novel message interface based memory system (MIMS) is proposed. The key innovation of MIMS is that processor and memory system communicate through a universal and flexible message interface. Each message packet could contain multiple memory requests or commands along with various semantic information. The memory system is more intelligent and active by equipping with a local buffer scheduler, which is responsible to process packet, schedule memory requests, and execute specific commands with the help of semantic information. The experimental results by simulator show that, with accurate granularity message, the MIMS would improve performance by 53.21%, while reducing energy delay product (EDP) by 55.90%, the effective bandwidth utilization is improving by 62.42%. Furthermore, combining multiple requests in a packet would reduce link overhead and provide opportunity for address compression.

cs.AR

HMTT: A Hybrid Hardware/Software Tracing System for Bridging Memory Trace's Semantic Gap

Memory trace analysis is an important technology for architecture research, system software (i.e., OS, compiler) optimization, and application performance improvements. Hardware-snooping is an effective and efficient approach to monitor and collect memory traces. Compared with software-based approaches, memory traces collected by hardware-based approaches are usually lack of semantic information, such as process/function/loop identifiers, virtual address and I/O access. In this paper we propose a hybrid hardware/software mechanism which is able to collect memory reference trace as well as semantic information. Based on this mechanism, we designed and implemented a prototype system called HMTT (Hybrid Memory Trace Tool) which adopts a DIMMsnooping mechanism to snoop on memory bus and a software-controlled tracing mechanism to inject semantic information into normal memory trace. To the best of our knowledge, the HMTT system is the first hardware tracing system capable of correlating memory trace with high-level events. Comprehensive validations and evaluations show that the HMTT system has both hardware's (e.g., no distortion or pollution) and software's advantages (e.g., flexibility and more information).

cs.AR