ACM Transactions on Graphics最新文献_第7页

GPU Coroutines for Flexible Splitting and Scheduling of Rendering Tasks 用于灵活拆分和调度渲染任务的 GPU 例行程序

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-11-19 DOI: 10.1145/3687766

Shaokun Zheng, Xin Chen, Zhong Shi, Ling-Qi Yan, Kun Xu

{"title":"GPU Coroutines for Flexible Splitting and Scheduling of Rendering Tasks","authors":"Shaokun Zheng, Xin Chen, Zhong Shi, Ling-Qi Yan, Kun Xu","doi":"10.1145/3687766","DOIUrl":"https://doi.org/10.1145/3687766","url":null,"abstract":"We introduce coroutines into GPU kernel programming, providing an automated solution for flexible splitting and scheduling of rendering tasks. This approach addresses a prevalent challenge in harnessing the power of modern GPUs for complex, imbalanced graphics workloads like path tracing. Usually, to accommodate the SIMT execution model and latency-hiding architecture, developers have to decompose a monolithic mega-kernel into smaller sub-tasks for improved thread coherence and reduced register pressure. However, involving the handling of intricate nested control flows and numerous interdependent program states, this process can be exceedingly tedious and error-prone when performed manually. Coroutines, a building block for asynchronous programming in many high-level CPU languages, exhibit untapped potential for restructuring GPU kernels due to their versatility in control representation. By extending Luisa [Zheng et al. 2022], we implement an asymmetric, stackless coroutine model with programming language support and multiple built-in schedulers for modern GPUs. To showcase the effectiveness of our model and implementation, we examine them in different application scenarios, including path tracing, SDF rendering, and incorporation with custom passes.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"22 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142673037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Real-time Large-scale Deformation of Gaussian Splatting 高斯拼接的实时大尺度变形

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-11-19 DOI: 10.1145/3687756

Lin Gao, Jie Yang, Bo-Tao Zhang, Jia-Mu Sun, Yu-Jie Yuan, Hongbo Fu, Yu-Kun Lai

{"title":"Real-time Large-scale Deformation of Gaussian Splatting","authors":"Lin Gao, Jie Yang, Bo-Tao Zhang, Jia-Mu Sun, Yu-Jie Yuan, Hongbo Fu, Yu-Kun Lai","doi":"10.1145/3687756","DOIUrl":"https://doi.org/10.1145/3687756","url":null,"abstract":"Neural implicit representations, including Neural Distance Fields and Neural Radiance Fields, have demonstrated significant capabilities for reconstructing surfaces with complicated geometry and topology, and generating novel views of a scene. Nevertheless, it is challenging for users to directly deform or manipulate these implicit representations with large deformations in a real-time fashion. Gaussian Splatting (GS) has recently become a promising method with explicit geometry for representing static scenes and facilitating high-quality and real-time synthesis of novel views. However, it cannot be easily deformed due to the use of discrete Gaussians and the lack of explicit topology. To address this, we develop a novel GS-based method (GaussianMesh) that enables interactive deformation. Our key idea is to design an innovative mesh-based GS representation, which is integrated into Gaussian learning and manipulation. 3D Gaussians are defined over an explicit mesh, and they are bound with each other: the rendering of 3D Gaussians guides the mesh face split for adaptive refinement, and the mesh face split directs the splitting of 3D Gaussians. Moreover, the explicit mesh constraints help regularize the Gaussian distribution, suppressing poor-quality Gaussians ( e.g. , misaligned Gaussians, long-narrow shaped Gaussians), thus enhancing visual quality and reducing artifacts during deformation. Based on this representation, we further introduce a large-scale Gaussian deformation technique to enable deformable GS, which alters the parameters of 3D Gaussians according to the manipulation of the associated mesh. Our method benefits from existing mesh deformation datasets for more realistic data-driven Gaussian deformation. Extensive experiments show that our approach achieves high-quality reconstruction and effective deformation, while maintaining the promising rendering results at a high frame rate (65 FPS on average on a single commodity GPU).","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"64 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142673086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Trading Spaces: Adaptive Subspace Time Integration for Contacting Elastodynamics 交易空间：用于接触弹性力学的自适应子空间时间积分法

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-11-19 DOI: 10.1145/3687946

Ty Trusty, Yun (Raymond) Fei, David Levin, Danny Kaufman

{"title":"Trading Spaces: Adaptive Subspace Time Integration for Contacting Elastodynamics","authors":"Ty Trusty, Yun (Raymond) Fei, David Levin, Danny Kaufman","doi":"10.1145/3687946","DOIUrl":"https://doi.org/10.1145/3687946","url":null,"abstract":"We construct a subspace simulator that adaptively balances solution improvement against system size. The core components of our simulator are an adaptive subspace oracle, model, and parallel time-step solver algorithm. Our in-time-step adaptivity oracle continually assesses subspace solution quality and candidate update proposals while accounting for temporal variations in deformation and spatial variations in material. In turn our adaptivity model is subspace agnostic. It allows application across subspace representations and expresses unrestricted deformations independent of subspace choice. We couple our oracle and model with a custom-constructed parallel time-step solver for our enriched systems that exposes a pair of user tolerances which provide controllable simulation quality. As tolerances are tightened our model converges to full-space solutions (with expected cost increases). On the other hand, as tolerances are relaxed we obtain output-bound simulation costs. We demonstrate the efficacy of our approach across a wide range of challenging nonlinear materials models, material stiffnesses, heterogeneities, dynamic behaviors, and frictionally contacting conditions, obtaining scalable and efficient simulations of complex elastodynamic scenarios.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"69 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142673091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SGEdit: Bridging LLM with Text2Image Generative Model for Scene Graph-based Image Editing SGEdit：连接 LLM 与 Text2Image 生成模型，实现基于场景图的图像编辑

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-11-19 DOI: 10.1145/3687957

Zhiyuan Zhang, DongDong Chen, Jing Liao

{"title":"SGEdit: Bridging LLM with Text2Image Generative Model for Scene Graph-based Image Editing","authors":"Zhiyuan Zhang, DongDong Chen, Jing Liao","doi":"10.1145/3687957","DOIUrl":"https://doi.org/10.1145/3687957","url":null,"abstract":"Scene graphs offer a structured, hierarchical representation of images, with nodes and edges symbolizing objects and the relationships among them. It can serve as a natural interface for image editing, dramatically improving precision and flexibility. Leveraging this benefit, we introduce a new framework that integrates large language model (LLM) with Text2Image generative model for scene graph-based image editing. This integration enables precise modifications at the object level and creative recomposition of scenes without compromising overall image integrity. Our approach involves two primary stages: 1) Utilizing a LLM-driven scene parser, we construct an image's scene graph, capturing key objects and their interrelationships, as well as parsing fine-grained attributes such as object masks and descriptions. These annotations facilitate concept learning with a fine-tuned diffusion model, representing each object with an optimized token and detailed description prompt. 2) During the image editing phase, a LLM editing controller guides the edits towards specific areas. These edits are then implemented by an attention-modulated diffusion editor, utilizing the fine-tuned model to perform object additions, deletions, replacements, and adjustments. Through extensive experiments, we demonstrate that our framework significantly outperforms existing image editing methods in terms of editing precision and scene aesthetics. Our code is available at https://bestzzhang.github.io/SGEdit.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"69 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142672834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Designing triangle meshes with controlled roughness 设计具有可控粗糙度的三角形网格

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-11-19 DOI: 10.1145/3687940

Victor Ceballos Inza, Panagiotis Fykouras, Florian Rist, Daniel Häseker, Majid Hojjat, Christian Müller, Helmut Pottmann

引用次数: 0

GFFE: G-buffer Free Frame Extrapolation for Low-latency Real-time Rendering GFFE：用于低延迟实时渲染的无 G 缓冲区帧外推法

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-11-19 DOI: 10.1145/3687923

Songyin Wu, Deepak Vembar, Anton Sochenov, Selvakumar Panneer, Sungye Kim, Anton Kaplanyan, Ling-Qi Yan

{"title":"GFFE: G-buffer Free Frame Extrapolation for Low-latency Real-time Rendering","authors":"Songyin Wu, Deepak Vembar, Anton Sochenov, Selvakumar Panneer, Sungye Kim, Anton Kaplanyan, Ling-Qi Yan","doi":"10.1145/3687923","DOIUrl":"https://doi.org/10.1145/3687923","url":null,"abstract":"Real-time rendering has been embracing ever-demanding effects, such as ray tracing. However, rendering such effects in high resolution and high frame rate remains challenging. Frame extrapolation methods, which do not introduce additional latency as opposed to frame interpolation methods such as DLSS 3 and FSR 3, boost the frame rate by generating future frames based on previous frames. However, it is a more challenging task because of the lack of information in the disocclusion regions and complex future motions, and recent methods also have a high engine integration cost due to requiring G-buffers as input. We propose a G-buffer free frame extrapolation method, GFFE, with a novel heuristic framework and an efficient neural network, to plausibly generate new frames in real time without introducing additional latency. We analyze the motion of dynamic fragments and different types of disocclusions, and design the corresponding modules of the extrapolation block to handle them. After that, a light-weight shading correction network is used to correct shading and improve overall quality. GFFE achieves comparable or better results than previous interpolation and G-buffer dependent extrapolation methods, with more efficient performance and easier integration.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"99 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142673051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dense Server Design for Immersion Cooling 浸入式冷却的密集服务器设计

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-11-19 DOI: 10.1145/3687965

Milin Kodnongbua, Zachary Englhardt, Ricardo Bianchini, Rodrigo Fonseca, Alvin Lebeck, Daniel S. Berger, Vikram Iyer, Fiodar Kazhamiaka, Adriana Schulz

{"title":"Dense Server Design for Immersion Cooling","authors":"Milin Kodnongbua, Zachary Englhardt, Ricardo Bianchini, Rodrigo Fonseca, Alvin Lebeck, Daniel S. Berger, Vikram Iyer, Fiodar Kazhamiaka, Adriana Schulz","doi":"10.1145/3687965","DOIUrl":"https://doi.org/10.1145/3687965","url":null,"abstract":"The growing demands for computational power in cloud computing have led to a significant increase in the deployment of high-performance servers. The growing power consumption of servers and the heat they produce is on track to outpace the capacity of conventional air cooling systems, necessitating more efficient cooling solutions such as liquid immersion cooling. The superior heat exchange capabilities of immersion cooling both eliminates the need for bulky heat sinks, fans, and air flow channels while also unlocking the potential go beyond conventional 2D blade servers to three-dimensional designs. In this work, we present a computational framework to explore designs of servers in three-dimensional space, specifically targeting the maximization of server density within immersion cooling tanks. Our tool is designed to handle a variety of physical and electrical server design constraints. We demonstrate our optimized designs can reduce server volume by 25--52% compared to traditional flat server designs. This increased density reduces land usage as well as the amount of liquid used for immersion, with significant reduction in the carbon emissions embodied in datacenter buildings. We further create physical prototypes to simulate dense server designs and perform real-world experiments in an immersion cooling tank demonstrating they operate at safe temperatures. This approach marks a critical step forward in sustainable and efficient datacenter management.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"22 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142673088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Impulse Ghost Fluid Method for Simulating Two-Phase Flows 模拟两相流体的脉冲幽灵流体法

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-11-19 DOI: 10.1145/3687963

Yuchen Sun, Linglai Chen, Weiyuan Zeng, Tao Du, Shiying Xiong, Bo Zhu

引用次数: 0

Computational Biomimetics of Winged Seeds 有翼种子的计算仿生学

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-11-19 DOI: 10.1145/3687899

Qiqin Le, Jiamu Bu, Yanke Qu, Bo Zhu, Tao Du

引用次数: 0

Online Neural Denoising with Cross-Regression for Interactive Rendering 用于交互式渲染的交叉回归在线去噪神经技术

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-11-19 DOI: 10.1145/3687938

Hajin Choi, Seokpyo Hong, Inwoo Ha, Nahyup Kang, Bochang Moon

{"title":"Online Neural Denoising with Cross-Regression for Interactive Rendering","authors":"Hajin Choi, Seokpyo Hong, Inwoo Ha, Nahyup Kang, Bochang Moon","doi":"10.1145/3687938","DOIUrl":"https://doi.org/10.1145/3687938","url":null,"abstract":"Generating a rendered image sequence through Monte Carlo ray tracing is an appealing option when one aims to accurately simulate various lighting effects. Unfortunately, interactive rendering scenarios limit the allowable sample size for such sampling-based light transport algorithms, resulting in an unbiased but noisy image sequence. Image denoising has been widely adopted as a post-sampling process to convert such noisy image sequences into biased but temporally stable ones. The state-of-the-art strategy for interactive image denoising involves devising a deep neural network and training this network via supervised learning, i.e., optimizing the network parameters using training datasets that include an extensive set of image pairs (noisy and ground truth images). This paper adopts the prevalent approach for interactive image denoising, which relies on a neural network. However, instead of supervised learning, we propose a different learning strategy that trains our network parameters on the fly, i.e., updating them online using runtime image sequences. To achieve our denoising objective with online learning, we tailor local regression to a cross-regression form that can guide robust training of our denoising neural network. We demonstrate that our denoising framework effectively reduces noise in input image sequences while robustly preserving both geometric and non-geometric edges, without requiring the manual effort involved in preparing an external dataset.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"18 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142673093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0