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    StocHD: Stochastic Hyperdimensional System for Efficient and Robust Learning from Raw Data by Poduval, Prathyush, Zou, Zhuowen, Najafi, Hassan, Homayoun, Houman, Imani, Mohsen

    Published: IEEE 05.12.2021
    “…Hyperdimensional Computing (HDC) is a neurally-inspired computation model working based on the observation that the human brain operates on high-dimensional representations of data, called hypervector…”
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    Conference Proceeding
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    MHDiff: Memory- and Hardware-Efficient Diffusion Acceleration via Focal Pixel Aware Quantization by Qi, Chunyu, Wang, Xuhang, Chen, Ruiyang, Yao, Yuanzheng, Jing, Naifeng, Zhang, Chen, Wang, Jun, Fu, Zhihui, Liang, Xiaoyao, Song, Zhuoran

    Published: IEEE 22.06.2025
    “…Diffusion models have demonstrated superior performance in image generation tasks, thus becoming the mainstream model for generative visual tasks. Diffusion…”
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    Conference Proceeding
  13. 13

    BEVSA: A Real-Time Bird's-Eye-View Semantic Segmentation Accelerator for Multi-Camera System by Lee, Sangho, Jung, Jueung, Jang, Wuyoung, Hwang, Jihyeon, Lee, Kyuho

    Published: IEEE 22.06.2025
    “…A bird's-eye-view (BEV) semantic segmentation accelerator (BEVSA) is proposed for real-time 3D space perception in multi-camera system (MCS…”
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  14. 14

    A Framework for Fine-Grained Synchronization of Dependent GPU Kernels by Jangda, Abhinav, Maleki, Saeed, Dehnavi, Maryam Mehri, Musuvathi, Madan, Saarikivi, Olli

    ISSN: 2643-2838
    Published: IEEE 02.03.2024
    “… These computations are commonly executed on Graphics Processing Units (GPUs), by dividing the computation into independent processing blocks, known as tiles…”
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  15. 15

    VISTA: Optimizing GPU Scheduling through Versatile Locality-Aware Data Sharing by Falahati, Hajar, Mahani, Negin, Cristal, Adrian, Unsal, Osman

    Published: IEEE 22.06.2025
    “…Graphics Processing Units (GPUs) play a pivotal role in high-performance computing by utilizing the massive parallelism of concurrent thread execution to enhance processing efficiency, known as thread-level parallelism (TLP…”
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    Conference Proceeding
  16. 16

    Efficient Edge Vision Transformer Accelerator with Decoupled Chunk Attention and Hybrid Computing-In-Memory by Li, Yi, Ye, Zijian, Fu, Xiangqu, Wang, Songqi, Du, Shucheng, Lin, Ning, Shang, Dashan, Yue, Jinshan, Wang, Zhongrui, Qi, Xiaojuan, Zhang, Feng, Wang, Han

    Published: IEEE 22.06.2025
    “…Vision Transformers (ViTs) are new foundation models for vision applications. Edge-deploying ViTs to realize energy-saving, low-latency, and high-performance…”
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    GEM: GPU-Accelerated Emulator-Inspired RTL Simulation by Guo, Zizheng, Zhang, Yanqing, Wang, Runsheng, Lin, Yibo, Ren, Haoxing

    Published: IEEE 22.06.2025
    “…) architecture, designed for efficient CUDA execution. We also design a flow that maps circuit logic to the architecture in a process analogous to the FPGA CAD flow…”
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    Heterogeneous Acceleration Pipeline for Recommendation System Training by Adnan, Muhammad, Maboud, Yassaman Ebrahimzadeh, Mahajan, Divya, Nair, Prashant J.

    Published: IEEE 29.06.2024
    “…Recommendation models rely on deep learning networks and large embedding tables, resulting in computationally and memory-intensive processes…”
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  19. 19

    RADiT: Redundancy-Aware Diffusion Transformer Acceleration Leveraging Timestep Similarity by Park, Youngjun, Kim, Sangyeon, Kim, Yeonggeon, Ji, Gisan, Ryu, Sungju

    Published: IEEE 22.06.2025
    “… However, a large amount of computations on the inference process and iterative sampling steps in the DiT models result in high computational costs, leading to substantial latency and energy consumption challenges…”
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    Espresso: Exploiting the Sparsity Property in Event Sensors with Spatiotemporal Ordering by Li, Leshan, Li, Hongyi, Yang, Qingyuan, Ou, Mingtao, Zhao, Rong, Ji, Xinglong

    Published: IEEE 22.06.2025
    “… However, it is challenging to efficiently stream process event data without demolishing its sparsity…”
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    Conference Proceeding