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RT-NeRF: Real-Time On-Device Neural Radiance Fields Towards Immersive AR/VR Rendering by Li, Chaojian, Li, Sixu, Zhao, Yang, Zhu, Wenbo, Lin, Yingyan

“…Neural Radiance Field (NeRF) based rendering has attracted growing attention thanks to its state-of-the-art (SOTA) rendering quality and wide applications in…”
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Mars: A MapReduce Framework on graphics processors by He, Bingsheng, Fang, Wenbin, Luo, Qiong, Govindaraju, Naga K., Wang, Tuyong

“…We design and implement Mars, a MapReduce framework, on graphics processors (GPUs). MapReduce is a distributed programming framework originally proposed…”
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Instant-NeRF: Instant On-Device Neural Radiance Field Training via Algorithm-Accelerator Co-Designed Near-Memory Processing by Zhao, Yang Katie, Wu, Shang, Zhang, Jingqun, Li, Sixu, Li, Chaojian, Lin, Yingyan Celine

“… Our profiling analysis reveals a memory-bound inefficiency in NeRF training. To tackle this inefficiency, near-memory processing (NMP…”
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Harnessing Conventional Video Processing Insights for Emerging 3D Video Generation Models: A Comprehensive Attention-aware Way by Zhao, Tianlang, Liu, Jun, Li, Xingyang, Ding, Li, Li, Jinhao, Li, Shuaiheng, Hu, Jinbo, Dai, Guohao

“… Inspired by the success of conventional video processing, where video compression exploits similarities among patches, we point out that the attention mechanism can also harness the benefits…”
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GauRast: Enhancing GPU Triangle Rasterizers to Accelerate 3D Gaussian Splatting by Li, Sixu, Keller, Ben, Lin, Yingyan Celine, Khailany, Brucek

“… This work proposes an acceleration strategy that leverages the similarities between the 3DGS pipeline and the highly optimized conventional graphics pipeline in modern GPUs…”
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Vulkan-Sim: A GPU Architecture Simulator for Ray Tracing by Saed, Mohammadreza, Chou, Yuan Hsi, Liu, Lufei, Nowicki, Tyler, Aamodt, Tor M.

“… have started to make use of ray tracing APIs to bring more realistic graphics to their players…”
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Skywalker: Efficient Alias-Method-Based Graph Sampling and Random Walk on GPUs by Wang, Pengyu, Li, Chao, Wang, Jing, Wang, Taolei, Zhang, Lu, Leng, Jingwen, Chen, Quan, Guo, Minyi

“…Graph sampling and random walk operations, capturing the structural properties of graphs, are playing an important role today as we cannot directly adopt computing-intensive algorithms on large-scale graphs…”
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Trends in augmented reality tracking, interaction and display: A review of ten years of ISMAR by Feng Zhou, Duh, Henry Been-Lirn, Billinghurst, Mark

“…Although Augmented Reality technology was first developed over forty years ago, there has been little survey work giving an overview of recent research in the…”
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Local-GS: An Order-Independent Gaussian Splatting Training Accelerator Exploiting Splat Locality by Sun, Yiyang, Zhi, Qinzhe, Jing, Yiqi, Ye, Le, Huang, Ru, Jia, Tianyu

“…3D Gaussian Splatting has emerged as the SOTA approach for 3D representation and view synthesis. While Gaussian Splatting has demonstrated impressive…”
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SynGPU: Synergizing CUDA and Bit-Serial Tensor Cores for Vision Transformer Acceleration on GPU by Yao, Yuanzheng, Zhang, Chen, Qi, Chunyu, Chen, Ruiyang, Wang, Jun, Fu, Zhihui, Jing, Naifeng, Liang, Xiaoyao, Song, Zhuoran

“…Vision Transformers (ViTs) have demonstrated remarkable performance in computer vision tasks by effectively extracting global features…”
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SQ-DM: Accelerating Diffusion Models with Aggressive Quantization and Temporal Sparsity by Fan, Zichen, Dai, Steve, Venkatesan, Rangharajan, Sylvester, Dennis, Khailany, Brucek

“…Diffusion models have gained significant popularity in image generation tasks. However, generating high-quality content remains notably slow because it…”
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GSAcc: Accelerate 3D Gaussian Splatting via Depth Speculation and Gaussian-centric Rasterization by Yang, Mengtian, Wang, Yipeng, Lo, Chieh-Pu, Zhang, Xiuhao, Oruganti, Sirish, Kulkarni, Jaydeep P.

“…D Gaussian Splatting (3DGS) has emerged as a promising real-time photorealistic radiance field rendering technique. Existing GPU and hardware accelerators face…”
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Boustrophedonic Frames: Quasi-Optimal L2 Caching for Textures in GPUs by Joseph, Diya, Aragon, Juan L., Parcerisa, Joan-Manuel, Gonzalez, Antonio

“… In this paper, however, we surpass this exploration by fabricating a formal proof for a no-overhead quasi-optimal caching technique for caching textures in graphics workloads…”
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SFLU: Synchronization-Free Sparse LU Factorization for Fast Circuit Simulation on GPUs by Zhao, Jianqi, Wen, Yao, Luo, Yuchen, Jin, Zhou, Liu, Weifeng, Zhou, Zhenya

“…Sparse LU factorization is one of the key building blocks of sparse direct solvers and often dominates the computing time of circuit simulation programs…”
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Cambricon-D: Full-Network Differential Acceleration for Diffusion Models by Kong, Weihao, Hao, Yifan, Guo, Qi, Zhao, Yongwei, Song, Xinkai, Li, Xiaqing, Zou, Mo, Du, Zidong, Zhang, Rui, Liu, Chang, Wen, Yuanbo, Jin, Pengwei, Hu, Xing, Li, Wei, Xu, Zhiwei, Chen, Tianshi

“… computational redundancy and substantial hardware expenditures.Performing differential computing on input data seems to be a feasible approach for addressing such computational redundancy and improving hardware efficacy…”
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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

“…Diffusion models have demonstrated superior performance in image generation tasks, thus becoming the mainstream model for generative visual tasks. Diffusion…”
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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

“…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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Leveraging Difference Recurrence Relations for High-Performance GPU Genome Alignment by Zeni, Alberto, Onken, Seth, Santambrogio, Marco Domenico, Samadi, Mehrzad

“…Genome pairwise sequence alignment is one of the most computationally intensive workloads in many genomic pipelines, often accounting for over 90% of the…”
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PARO: Hardware-Software Co-design with Pattern-aware Reorder-based Attention Quantization in Video Generation Models by Yang, Xinhao, Zhao, Tianchen, Wang, Hongyi, Ma, Wenheng, Zeng, Shulin, Zhu, Zhenhua, Ning, Xuefei, Yang, Huazhong, Wang, Yu

“… while ensuring efficient hardware processing. To address these issues, we introduce PARO, a video generation accelerator with patternaware reorder-based attention quantization…”
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DARIS: An Oversubscribed Spatio-Temporal Scheduler for Real-Time DNN Inference on GPUs by Babaei, Amir Fakhim, Chantem, Thidapat

“… In particular, DARIS improves GPU utilization and uniquely analyzes GPU concurrency by oversubscribing computing resources…”
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