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"title": "2017 50th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO)",
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"doi": null,
"title": "Unleashing the Power of GPU for Physically-Based Rendering via Dynamic Ray Shuffling",
"normalizedTitle": "Unleashing the Power of GPU for Physically-Based Rendering via Dynamic Ray Shuffling",
"abstract": "Computer graphics is generally divided into two branches: real-time rendering and physically-based rendering. Conventional graphics processing units (GPUs) were designed to accelerate the former which is based on the standard Z-buffer algorithm. However, many applications in entertainment, science, and industry require high quality visual effects such as soft-shadows, reflections, and diffuse lighting interactions which are difficult to achieve with the Z-buffer algorithm, but are straightforward to implement using physically-based rendering methods. Physically-based rendering can already be implemented on present programmable GPUs. However, for physically-based rendering on GPUs, a large portion of the processing power is wasted due to low utilization of SIMD units. This is because the core algorithm of physically-based rendering, ray tracing, suffers from Single Instruction, Multiple Thread (SIMT) control flow divergences. In this paper, we propose the Dynamic Ray Shuffling (DRS) architecture for GPUs to address this problem. Our key insight is that the primary control flow divergences are caused by inconsistent ray traversal states of a warp, and can be eliminated by dynamically shuffling rays. Experimental results show that, for an estimated 0.11% area cost, DRS significantly improves the SIMD efficiency for the tested benchmarks from 41.06% to 81.04% on average. With this, the performance of a physically-based rendering method such as path tracing can be improved by 1.67×-1.92×, and 1.79× on average.",
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"content": "Computer graphics is generally divided into two branches: real-time rendering and physically-based rendering. Conventional graphics processing units (GPUs) were designed to accelerate the former which is based on the standard Z-buffer algorithm. However, many applications in entertainment, science, and industry require high quality visual effects such as soft-shadows, reflections, and diffuse lighting interactions which are difficult to achieve with the Z-buffer algorithm, but are straightforward to implement using physically-based rendering methods. Physically-based rendering can already be implemented on present programmable GPUs. However, for physically-based rendering on GPUs, a large portion of the processing power is wasted due to low utilization of SIMD units. This is because the core algorithm of physically-based rendering, ray tracing, suffers from Single Instruction, Multiple Thread (SIMT) control flow divergences. In this paper, we propose the Dynamic Ray Shuffling (DRS) architecture for GPUs to address this problem. Our key insight is that the primary control flow divergences are caused by inconsistent ray traversal states of a warp, and can be eliminated by dynamically shuffling rays. Experimental results show that, for an estimated 0.11% area cost, DRS significantly improves the SIMD efficiency for the tested benchmarks from 41.06% to 81.04% on average. With this, the performance of a physically-based rendering method such as path tracing can be improved by 1.67×-1.92×, and 1.79× on average.",
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"normalizedAbstract": "Computer graphics is generally divided into two branches: real-time rendering and physically-based rendering. Conventional graphics processing units (GPUs) were designed to accelerate the former which is based on the standard Z-buffer algorithm. However, many applications in entertainment, science, and industry require high quality visual effects such as soft-shadows, reflections, and diffuse lighting interactions which are difficult to achieve with the Z-buffer algorithm, but are straightforward to implement using physically-based rendering methods. Physically-based rendering can already be implemented on present programmable GPUs. However, for physically-based rendering on GPUs, a large portion of the processing power is wasted due to low utilization of SIMD units. This is because the core algorithm of physically-based rendering, ray tracing, suffers from Single Instruction, Multiple Thread (SIMT) control flow divergences. In this paper, we propose the Dynamic Ray Shuffling (DRS) architecture for GPUs to address this problem. Our key insight is that the primary control flow divergences are caused by inconsistent ray traversal states of a warp, and can be eliminated by dynamically shuffling rays. Experimental results show that, for an estimated 0.11% area cost, DRS significantly improves the SIMD efficiency for the tested benchmarks from 41.06% to 81.04% on average. With this, the performance of a physically-based rendering method such as path tracing can be improved by 1.67×-1.92×, and 1.79× on average.",
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"affiliation": "Key Laboratory, Astronautical Engineering University, Beijing, China",
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"affiliation": "State Key Laboratory of High Performance Computing and School of Computer, National University of Defense Technology, Changsha, China",
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{
"affiliation": "State Key Laboratory of High Performance Computing and School of Computer, National University of Defense Technology, Changsha, China",
"fullName": "Li Shen",
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{
"affiliation": "State Key Laboratory of High Performance Computing and School of Computer, National University of Defense Technology, Changsha, China",
"fullName": "Zhiying Wang",
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"abstract": "The appetite for higher and higher 3D graphics quality continues to drive GPU computing requirements. To satisfy these demands, GPU vendors are moving towards new architectures, such as MCM-GPU and multi-GPUs, that connect multiple chip modules or GPUs with high-speed links (e.g., NVLink and XGMI) to provide higher computing capability. Unfortunately, it is not clear how to adequately parallelize the rendering pipeline to take advantage of these resources while maintaining low rendering latencies. Current implementations of Split Frame Rendering (SFR) are bottlenecked by redundant computations and sequential inter-GPU synchronization, and fail to scale as the GPU count increases. In this paper, we propose CHOPIN, a novel SFR scheme for multi-GPU systems that exploits the parallelism available in image composition to eliminate the bottlenecks inherent to existing solutions. CHOPIN composes opaque sub-images out-of order, and leverages the associativity of image composition to compose adjacent sub-images of transparent objects asynchronously. To mitigate load imbalance across GPUs and avoid inter-GPU network congestion, CHOPIN includes two new scheduling mechanisms: a draw-command scheduler and an image composition scheduler. Detailed cycle-level simulations on eight real-world game traces show that, in an 8-GPU system, CHOPIN offers speedups of up to 1.56× (1.25× gmean) compared to the best prior SFR implementation.",
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"content": "The appetite for higher and higher 3D graphics quality continues to drive GPU computing requirements. To satisfy these demands, GPU vendors are moving towards new architectures, such as MCM-GPU and multi-GPUs, that connect multiple chip modules or GPUs with high-speed links (e.g., NVLink and XGMI) to provide higher computing capability. Unfortunately, it is not clear how to adequately parallelize the rendering pipeline to take advantage of these resources while maintaining low rendering latencies. Current implementations of Split Frame Rendering (SFR) are bottlenecked by redundant computations and sequential inter-GPU synchronization, and fail to scale as the GPU count increases. In this paper, we propose CHOPIN, a novel SFR scheme for multi-GPU systems that exploits the parallelism available in image composition to eliminate the bottlenecks inherent to existing solutions. CHOPIN composes opaque sub-images out-of order, and leverages the associativity of image composition to compose adjacent sub-images of transparent objects asynchronously. To mitigate load imbalance across GPUs and avoid inter-GPU network congestion, CHOPIN includes two new scheduling mechanisms: a draw-command scheduler and an image composition scheduler. Detailed cycle-level simulations on eight real-world game traces show that, in an 8-GPU system, CHOPIN offers speedups of up to 1.56× (1.25× gmean) compared to the best prior SFR implementation.",
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"title": "2018 5th International Conference on Information Science and Control Engineering (ICISCE)",
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"title": "A Feasible Method of Virtual Flow Field Simulation - Part II: Simulation and Visualization in RTT System",
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"abstract": "Dassault Systèmes' RTT system is a real-time virtual reality one that can achieve a virtual flow field simulation. However, the relative module is not only expensive, but also not satisfied in openness. A novel and feasible method is presented here to realize three-dimensional virtual streamlines based on RTT system without using the relative module in RTT system. In this part, the streamlines are imported into Autodesk Alias Automotive system via an IGES file, applied by the appropriate streamline type, and integrated with the vehicle model, which is used for the simulation in Fluent. The streamlines and the vehicle model are then imported into RTT system via a wire file. The virtual streamline simulation, like the smoke streamlines in the real wind tunnel test, has been achieved with the high quality through the real-time rendering of the streamlines and the vehicle model.",
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"content": "Dassault Systèmes' RTT system is a real-time virtual reality one that can achieve a virtual flow field simulation. However, the relative module is not only expensive, but also not satisfied in openness. A novel and feasible method is presented here to realize three-dimensional virtual streamlines based on RTT system without using the relative module in RTT system. In this part, the streamlines are imported into Autodesk Alias Automotive system via an IGES file, applied by the appropriate streamline type, and integrated with the vehicle model, which is used for the simulation in Fluent. The streamlines and the vehicle model are then imported into RTT system via a wire file. The virtual streamline simulation, like the smoke streamlines in the real wind tunnel test, has been achieved with the high quality through the real-time rendering of the streamlines and the vehicle model.",
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"abstract": "The paper describes an implementation of a tool for visualizing and interacting with huge information hierarchies, and some preliminary empirical evaluation of the tool's efficacy. Existing systems for visualizing huge hierarchies using cone trees \"break down\" once the hierarchy to be displayed exceeds roughly 1000 nodes, due to increasing visual clutter. The paper describes a system called fsviz which visualizes arbitrarily large hierarchies while retaining user control. This is accomplished by augmenting cone trees with several graphical and interaction techniques: usage-based filtering, animated zooming, hand-coupled rotation, fish-eye zooming, coalescing of distant nodes, texturing, effective use of colour for depth cueing, and the applications of dynamic queries. The fsviz system also improves upon earlier cone tree visualization systems through a more elaborate node layout algorithm. This algorithm enhances the usefulness of cone tree visualization for large hierarchies by all but eliminating clutter.",
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"abstract": "Information visualization shows tremendous potential for helping both expert and casual users alike make sense of temporal data, but current time series visualization tools provide poor support for comparing several foci in a temporal dataset while retaining context and distance awareness. We introduce a method for supporting this kind of multi-focus interaction that we call stack zooming. The approach is based on the user interactively building hierarchies of 1D strips stacked on top of each other, where each subsequent stack represents a higher zoom level, and sibling strips represent branches in the visual exploration. Correlation graphics show the relation between stacks and strips of different levels, providing context and distance awareness among the focus points. The zoom hierarchies can also be used as graphical histories and for communicating insights to stakeholders. We also discuss how visual spaces that support stack zooming can be extended with annotation and local statistics computations that fit the hierarchical stacking metaphor.",
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"abstract": "Identifying individuals using biometric data is an important task in surveillance, authentication and even entertainment. This task is more challenging when required to be performed without physical contact and at a distance. Analyzing video footages from individuals for patterns is an active area of research aiming at fulfilling this goal. We describe results on classifiers trained to identify individuals from data collected from 140 subjects walking in front of a Microsoft Kinect sensor, which allows tracking 3D points representing a subject's skeleton. From this data we extract anthropometric and gait attributes to be used by the classifiers. We show that anthropometric features are more important than gait features but using both allows for higher accuracies. Additionally, we explore how different numbers of subjects and numbers of available examples affect accuracy, providing evidences on how effective the proposed methodology can be in different scenarios.",
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"content": "Identifying individuals using biometric data is an important task in surveillance, authentication and even entertainment. This task is more challenging when required to be performed without physical contact and at a distance. Analyzing video footages from individuals for patterns is an active area of research aiming at fulfilling this goal. We describe results on classifiers trained to identify individuals from data collected from 140 subjects walking in front of a Microsoft Kinect sensor, which allows tracking 3D points representing a subject's skeleton. From this data we extract anthropometric and gait attributes to be used by the classifiers. We show that anthropometric features are more important than gait features but using both allows for higher accuracies. Additionally, we explore how different numbers of subjects and numbers of available examples affect accuracy, providing evidences on how effective the proposed methodology can be in different scenarios.",
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"title": "2014 International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH)",
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"doi": "10.5220/0005026900360042",
"title": "An effective implementation of agent's complex actions by reusing primitive motions",
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"abstract": "The efficient implementation of various physical actions of an agent to respond to dynamically changing situations is essential for the design of a realistic agent in a cyber world. To achieve a maximum diversity in actions, we develop a mechanism that allows composite actions to be constructed by reusing a set of primitive motions and enables an agent to instantly react to changes in the ambient states. Specifically we model an agent's body in terms of joints, and a primitive or composite motion is performed in a real time. To implement this mechanism, we produce an animation for each basic joint movement and develop a scheme to construct overall motions out of the primitive motions. These motions can be assembled into a plan by which an agent can achieve a goal. In this manner, diverse actions can be implemented without excessive efforts. This approach has conspicuous advantages when constructing a parallel action, e.g., eating while walking, that is, two or more parallel actions can be naturally merged into a parallel action with an arbitration on their priority. We implemented several composite and parallel actions to demonstrate the viability of our approach.",
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"title": "A Stable Walking Strategy of Quadruped Robot Based on Foot Trajectory Planning",
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"abstract": "For a quadruped robot to implement steady moving on horizontal planes, avoiding the impact against the ground, a foot trajectory planning method underling low contact impact was presented. At first, kinematic model of the quadruped robot though D-H algorithm have been established. Then, the foot trajectories, which are continuous not only in displacements and velocities but also in accelerations, was scheduled based on the walking gait. Lastly, the steering and straight line movements of the robot were simulated, simulation experiments show that the quadruped robot motion stably on horizontal planes without impact and sliding.",
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"affiliation": "Kyushu Institute of Technology,Fukuoka,Japan",
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"title": "Eye-tracking investigation during visual analysis of projected multidimensional data with 2D scatterplots",
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"abstract": "A common strategy for visual encoding of multidimensional data for visual analyses is to use dimensionality reduction. Each multidimensional data point is projected to a 2D point using a certain strategy for the 2D layout. Many layout strategies have been proposed addressing different objectives and targeted at distinct domains and applications. The resulting projected information is typically displayed in form of 2D scatterplots. The user's perspective such as the role of visual attention and guidance of attention for a respective layout and task has not been addressed much. It is the goal of this work to investigate, how characteristics in the layout affect the cognitive process during task completion. Eye trackers are an effective means to capture visual attention over time. We use eye tracking in a user study, where we ask users to perform typical analysis tasks for projected multidimensional data such as relation seeking, behavior comparison, and pattern identification. Those tasks often involve detecting and correlating clusters. To understand the role of point density within clusters, cluster sizes, and cluster shapes, we first conducted a study with synthetic 2D scatterplots, where we can set the respective properties manually. We evaluate how changing various parameters affect the visual attention pattern and correlate it to the correctness of the answer. In a second step, we conducted a study where the users were asked to complete tasks on real-world data with different characteristics (image collection and document collection) that are visualized using a selection of different dimensionality reduction algorithms. We transfer the insight obtained from synthetic data to investigate the decision making with real-world data. Gestalt laws can be applied to the layout structure. We examine how certain layout techniques produce certain characteristics that change the visual attention pattern. We draw some conclusions on how different projection methods support or hinder decision making leading to respective guidelines.",
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"Handheld Device",
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"affiliation": "Univ. of Tokyo, Tokyo, Japan",
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"title": "Homography Based Parallel Volume Intersection: Toward Real-Time Volume Reconstruction using Active Cameras",
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"abstract": "Silhouette volume intersection is one of the most popular ideas for reconstructing the 3D volume of an object from multi-viewpoint silhouette images. This paper presents a novel parallel volume intersection method based on plane-to-plane homography for real-time 3D volume reconstruction using active cameras. This paper mainly focuses on the acceleration of back-projection from silhouette images to 3D space without using any sophisticated software technique, such as octree volume representation, or look-up table based projection acceleration. Also this paper presents a parallel intersection method of projected silhouette images. From the preliminary experimental results we estimate near frame-rate volume reconstruction for a life-sized mannequin can be achieved at 3 cm spatial resolution on our PC cluster system.",
"abstracts": [
{
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"content": "Silhouette volume intersection is one of the most popular ideas for reconstructing the 3D volume of an object from multi-viewpoint silhouette images. This paper presents a novel parallel volume intersection method based on plane-to-plane homography for real-time 3D volume reconstruction using active cameras. This paper mainly focuses on the acceleration of back-projection from silhouette images to 3D space without using any sophisticated software technique, such as octree volume representation, or look-up table based projection acceleration. Also this paper presents a parallel intersection method of projected silhouette images. From the preliminary experimental results we estimate near frame-rate volume reconstruction for a life-sized mannequin can be achieved at 3 cm spatial resolution on our PC cluster system.",
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"fno": "07400331",
"keywords": [
"Image Reconstruction Real Time Volume Reconstruction Active Cameras Parallel Volume Intersection Back Projection Silhouette Images Octree Volume Representation Projection Acceleration Projected Silhouette Images Frame Rate Volume Reconstruction"
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"affiliation": "Dept. of Intelligent Sci. & Technol., Kyoto Univ., Japan",
"fullName": "T. Wada",
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"affiliation": "Dept. of Intelligent Sci. & Technol., Kyoto Univ., Japan",
"fullName": "Xiaojun Wu",
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"affiliation": "Dept. of Intelligent Sci. & Technol., Kyoto Univ., Japan",
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"affiliation": "Dept. of Intelligent Sci. & Technol., Kyoto Univ., Japan",
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"title": "Intelligent Robots and Systems, IEEE/RSJ International Conference on",
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"doi": "10.1109/IROS.1995.525804",
"title": "Planar projection stereopsis method for road extraction",
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"abstract": "This paper presents a new road extraction method for an autonomous vehicle which can acquire a road area by using height information of objects. Since a road area can be assumed to be a sequence of a flat plane in front of a vehicle, the road's height information is very effective for extracting a road area. For the purpose, the authors propose a new approach named the planar projection stereopsis (PPS) method which can easily decide whether each point in stereo images exists on the road plane or not. At first, PPS calculates a planar equation representing a road area by using height and pose of a camera in the vehicle. Next, stereo images are projected to the plane, where corresponding points are projected to the same positions on a certain road area if they really exist on a road plane, while corresponding points with different heights from the road plane are projected to different positions in each stereo image. Planar projection description is obtained by a subtraction between projected images from a set of stereo images and a road area can be represented by a set of points with small values. Experimental results for real road scenes have shown the effectiveness of the proposed method.",
"abstracts": [
{
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"content": "This paper presents a new road extraction method for an autonomous vehicle which can acquire a road area by using height information of objects. Since a road area can be assumed to be a sequence of a flat plane in front of a vehicle, the road's height information is very effective for extracting a road area. For the purpose, the authors propose a new approach named the planar projection stereopsis (PPS) method which can easily decide whether each point in stereo images exists on the road plane or not. At first, PPS calculates a planar equation representing a road area by using height and pose of a camera in the vehicle. Next, stereo images are projected to the plane, where corresponding points are projected to the same positions on a certain road area if they really exist on a road plane, while corresponding points with different heights from the road plane are projected to different positions in each stereo image. Planar projection description is obtained by a subtraction between projected images from a set of stereo images and a road area can be represented by a set of points with small values. Experimental results for real road scenes have shown the effectiveness of the proposed method.",
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"fno": "71080249",
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"affiliation": "Kansai Res. Labs., Toshiba Corp., Osaka, Japan",
"fullName": "K. Onoguchi",
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"affiliation": "Kansai Res. Labs., Toshiba Corp., Osaka, Japan",
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"affiliation": "Kansai Res. Labs., Toshiba Corp., Osaka, Japan",
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"abstract": "Intelligent Vehicle/Highway Systems (IVHS) is a multi-year research/demonstration program which aims at improving the vehicle/highway system operation and management techniques for the post-interstate construction era. The authors first describe the framework of IVHS, which as four major components: (1) advanced traffic management system (ATMS); (2) advanced driver information system (ADIS); (3) commercial vehicle operations (CVO); and (4) advanced vehicle control systems (AVCS). The ATMS related research and development plans to support the real-time traffic management systems and control strategies are considered. The state-of-the-art traffic engineering modeling software is reviewed. The discussion centers around the TRAF system, a family of microscopic and macroscopic traffic simulation software models for surface streets, freeways, and corridor networks. The gap between the capabilities provided by the current traffic modeling software and the functional requirement of the IVHS traffic models is also addressed.<>",
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"content": "Intelligent Vehicle/Highway Systems (IVHS) is a multi-year research/demonstration program which aims at improving the vehicle/highway system operation and management techniques for the post-interstate construction era. The authors first describe the framework of IVHS, which as four major components: (1) advanced traffic management system (ATMS); (2) advanced driver information system (ADIS); (3) commercial vehicle operations (CVO); and (4) advanced vehicle control systems (AVCS). The ATMS related research and development plans to support the real-time traffic management systems and control strategies are considered. The state-of-the-art traffic engineering modeling software is reviewed. The discussion centers around the TRAF system, a family of microscopic and macroscopic traffic simulation software models for surface streets, freeways, and corridor networks. The gap between the capabilities provided by the current traffic modeling software and the functional requirement of the IVHS traffic models is also addressed.<>",
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"abstract": "Traffic incidents cause great losses to people's lives and property, and have aroused great attention from researchers. In recent years, many machine learning methods have been utilized for traffic incident detection, e.g. Support Vector Machine (SVM) and Neural Networks (NN). However, all of them fail to consider the full spatial-temporal correlation on traffic data. In addition, the periodicity in traffic data is not well utilized. Traffic data in the same workday usually follows a similar pattern. In this paper, we introduce a deep learning framework, which captures both full spatial-temporal correlation and periodicity, to detect incidents on freeways. Experiments show that our method performs better than the state-of-the-art.",
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"affiliation": "The University of Hong Kong",
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"title": "Exploring Chinese Language Evolution via Computer Corpus Analysis: A Case Study of Liru's Lexicalization and Grammaticalization",
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"abstract": "No consensus has been achieved about part of speech of liru (for example in English equivalent, in Chinese characters) among Chinese linguists, and moreover the diachronic perspective of big data—though most promising—was seldom adopted owing to technological constraints. This study deploys a diachronic corpus of Chinese language to examine the evolution of liru across the time span of ancient and modern Chinese. Results show that, contemporary liru undergoes lexicalization of li and ru from as early as the Six Dynasties (222-589 A. D.) and grammaticalization of liru through their semantic blurring. It is as a result of complexities and subjectivity in the communication contexts, liru gradually takes on discoursal functions of illustrating.",
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"proceeding": {
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"title": "2016 IEEE 16th International Conference on Data Mining (ICDM)",
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"title": "Detecting Change Processes in Dynamic Networks by Frequent Graph Evolution Rule Mining",
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"abstract": "The analysis of the temporal evolution of dynamic networks is a key challenge for understanding complex processes hidden in graph structured data. Graph evolution rules capture such processes on the level of small subgraphs by describing frequently occurring structural changes within a network. Existing rule discovery methods make restrictive assumptions on the change processes present in networks. We propose EvoMine, a frequent graph evolution rule mining method that, for the first time, supports networks with edge insertions and deletions as well as node and edge relabelings. EvoMine defines embedding-based and event-based support as two novel measures to assess the frequency of rules. These measures are based on novel mappings from dynamic networks to databases of union graphs that retain all evolution information relevant for rule mining. Using these mappings the rule mining problem can be solved by frequent subgraph mining. We evaluate our approach and two baseline algorithms on several real datasets. To the best of our knowledge, this is the first empirical comparison of rule mining algorithmsfor dynamic networks.",
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"content": "The analysis of the temporal evolution of dynamic networks is a key challenge for understanding complex processes hidden in graph structured data. Graph evolution rules capture such processes on the level of small subgraphs by describing frequently occurring structural changes within a network. Existing rule discovery methods make restrictive assumptions on the change processes present in networks. We propose EvoMine, a frequent graph evolution rule mining method that, for the first time, supports networks with edge insertions and deletions as well as node and edge relabelings. EvoMine defines embedding-based and event-based support as two novel measures to assess the frequency of rules. These measures are based on novel mappings from dynamic networks to databases of union graphs that retain all evolution information relevant for rule mining. Using these mappings the rule mining problem can be solved by frequent subgraph mining. We evaluate our approach and two baseline algorithms on several real datasets. To the best of our knowledge, this is the first empirical comparison of rule mining algorithmsfor dynamic networks.",
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"proceeding": {
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"title": "2022 IEEE International Conference on Big Data (Big Data)",
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"article": {
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"doi": "10.1109/BigData55660.2022.10020941",
"title": "Dynamic Graph Node Classification via Time Augmentation",
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"abstract": "Node classification for graph-structured data aims to classify nodes whose labels are unknown. While studies on static graphs are prevalent, few studies have focused on dynamic graph node classification. Node classification on dynamic graphs is challenging for two reasons. First, the model needs to capture both structural and temporal information, particularly on dynamic graphs with a long history and require large receptive fields. Second, model scalability becomes a significant concern as the size of the dynamic graph increases. To address these problems, we propose the Time Augmented Dynamic Graph Neural Network (TADGNN) framework. TADGNN consists of two modules: 1) a time augmentation module that captures the temporal evolution of nodes across time structurally, creating a time-augmented spatio-temporal graph, and 2) an information propagation module that learns the dynamic representations for each node across time using the constructed time-augmented graph. We perform node classification experiments on four dynamic graph benchmarks. Experimental results demonstrate that TADGNN framework outperforms several static and dynamic state-of-the-art (SOTA) GNN models while demonstrating superior scalability. We also conduct theoretical and empirical analyses to validate the efficiency of the proposed method.",
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"content": "Node classification for graph-structured data aims to classify nodes whose labels are unknown. While studies on static graphs are prevalent, few studies have focused on dynamic graph node classification. Node classification on dynamic graphs is challenging for two reasons. First, the model needs to capture both structural and temporal information, particularly on dynamic graphs with a long history and require large receptive fields. Second, model scalability becomes a significant concern as the size of the dynamic graph increases. To address these problems, we propose the Time Augmented Dynamic Graph Neural Network (TADGNN) framework. TADGNN consists of two modules: 1) a time augmentation module that captures the temporal evolution of nodes across time structurally, creating a time-augmented spatio-temporal graph, and 2) an information propagation module that learns the dynamic representations for each node across time using the constructed time-augmented graph. We perform node classification experiments on four dynamic graph benchmarks. Experimental results demonstrate that TADGNN framework outperforms several static and dynamic state-of-the-art (SOTA) GNN models while demonstrating superior scalability. We also conduct theoretical and empirical analyses to validate the efficiency of the proposed method.",
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"affiliation": "University of Illinois at Urbana,Dept. of Electrical and Computer Engineering,Champaign,Urbana,USA",
"fullName": "Jiarui Sun",
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"affiliation": "Visa Research,Palo Alto,USA",
"fullName": "Mengting Gu",
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"affiliation": "Visa Research,Palo Alto,USA",
"fullName": "Chin-Chia Michael Yeh",
"givenName": "Chin-Chia Michael",
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"affiliation": "Visa Research,Palo Alto,USA",
"fullName": "Yujie Fan",
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"affiliation": "University of Illinois at Urbana,Dept. of Computer Science and Dept. of Agricultural and Biological Engineering,Champaign,Urbana,USA",
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"affiliation": "Visa Research,Palo Alto,USA",
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"abstract": "The past several years have seen both an explosion in the use of Convolutional Neural Networks (CNNs) and accelerators to make CNN inference practical. In the architecture community, the lion share of effort has targeted CNN inference for image recognition. The closely related problem of video recognition has received far less attention as an accelerator target. This is surprising, as video recognition is more computationally intensive than image recognition, and video traffic is predicted to be the majority of internet traffic in the coming years. This paper fills the gap between algorithmic and hardware advances for video recognition by providing a design space exploration and flexible architecture for accelerating 3D Convolutional Neural Networks (3D CNNs)-the core kernel in modern video understanding. When compared to (2D) CNNs used for image recognition, efficiently accelerating 3D CNNs poses a significant engineering challenge due to their large (and variable over time) memory footprint and higher dimensionality. To address these challenges, we design a novel accelerator called \"Morph,\" that can adaptively support different spatial and temporal tiling strategies depending on the needs of each layer of each target 3D CNN. We codesign a software infrastructure alongside the Morph hardware to find good-fit parameters to control the hardware. Evaluated on state-of-the-art 3D CNNs, Morph achieves up to 2.7× (1.9× average) reduction in energy consumption and improves performance/watt up to 4.4× (3× average) compared to a baseline 3D CNN accelerator, with an area overhead of 2%. Morph further achieves a 11.6× average energy reduction on 3D CNNs when compared to Eyeriss, a popular 2D CNN accelerator, while reducing efficiency compared to Eyeriss on a 2D CNN by 71%.",
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"content": "The past several years have seen both an explosion in the use of Convolutional Neural Networks (CNNs) and accelerators to make CNN inference practical. In the architecture community, the lion share of effort has targeted CNN inference for image recognition. The closely related problem of video recognition has received far less attention as an accelerator target. This is surprising, as video recognition is more computationally intensive than image recognition, and video traffic is predicted to be the majority of internet traffic in the coming years. This paper fills the gap between algorithmic and hardware advances for video recognition by providing a design space exploration and flexible architecture for accelerating 3D Convolutional Neural Networks (3D CNNs)-the core kernel in modern video understanding. When compared to (2D) CNNs used for image recognition, efficiently accelerating 3D CNNs poses a significant engineering challenge due to their large (and variable over time) memory footprint and higher dimensionality. To address these challenges, we design a novel accelerator called \"Morph,\" that can adaptively support different spatial and temporal tiling strategies depending on the needs of each layer of each target 3D CNN. We codesign a software infrastructure alongside the Morph hardware to find good-fit parameters to control the hardware. Evaluated on state-of-the-art 3D CNNs, Morph achieves up to 2.7× (1.9× average) reduction in energy consumption and improves performance/watt up to 4.4× (3× average) compared to a baseline 3D CNN accelerator, with an area overhead of 2%. Morph further achieves a 11.6× average energy reduction on 3D CNNs when compared to Eyeriss, a popular 2D CNN accelerator, while reducing efficiency compared to Eyeriss on a 2D CNN by 71%.",
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"abstract": "Modeling the spatial structure of crop inputs is of great importance for accurate yield prediction. It is a fundamental step towards optimizing the spatial allocation of resources such as seed and fertilizer. We propose two distinct architectures of Multi-Stream Convolutional Neural Network (MSCNN) - Late Fusion (LF) and Early Fusion (EF) - to model yield response to seed and nutrient management. A study presents a comparison between proposed models with conventional 2D and 3D CNN architectures, and existing agronomy methods. The dataset used to train and test the models is constructed using on-farm experiment data from nine cornfields across the US together with multispectral satellite images. Results show that the MSCNN-LF achieved a 20% reduction of the prediction's mean squared error value when compared to a 3D CNN, and a 26% reduction when compared to a 2D CNN. An optimization algorithm uses the MSCNN-LF model's gradient to change the manageable inputs variables in a way the expected profit is maximized subject to resource constraints. It is shown that an increase of up to 5.2% on expected crop yield return is obtained when compared to usual management practices.",
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"abstract": "Multiview video (MVV) can provide viewers a complete 3D perception by its multiple-viewpoint feature. In order to support smooth viewpoint switching, virtual view synthesis is required. However the ultra high computational complexity and the system memory bandwidth requirement make the real-time multiview applications difficult. For the quad full-HD (QFHD) specification, 31.5GByte/Sec is needed for every virtual view. Furthermore, the conventional line buffer based or block based data scheduling cannot support the various geometries required in the virtual view synthesis. In the paper, a six-dimensional free-viewpoint view synthesis flow is proposed. By the proposed texture reorder and inverse reorder data interface, the on-chip data scheduling can be done under the conventional block pipe lining even with different geometries. After integrating the pro posed bandwidth reduction schemes, including the dynamic warping reference frame selection and on-chip texture buffer optimization, 95.7% system memory bandwidth is saved. Comparing with the previous lD-horizontal-shifting-based 3DTV chips, the proposed scheduling provides full geometries including translations and rotations in the 3D space.",
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"abstract": "Conventional deep image inpainting methods are based on auto-encoder architecture, in which the spatial details of images will be lost in the down-sampling process, leading to the degradation of generated results. Also, the structure information in deep layers and texture information in shallow layers of the auto-encoder architecture can not be well integrated. Differing from the conventional image inpainting architecture, we design a parallel multi-resolution inpainting network with multi-resolution partial convolution, in which low-resolution branches focus on the global structure while high-resolution branches focus on the local texture details. All these high- and low-resolution streams are in parallel and fused repeatedly with multi-resolution masked representation fusion so that the reconstructed images are semantically robust and textually plausible. Experimental results show that our method can effectively fuse structure and texture information, producing more realistic results than state-of-the-art methods.",
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"abstract": "In haptics, both transparency and stability are major requirements for providing realistic feeling of virtual objects. The crisp contact feeling at the instant of touch with high impedance walls is necessary especially for proper identification and manipulation of virtual objects. This paper presents a new passivity condition that explicitly includes Coulomb friction effects. Moreover, the energy bounding algorithm incorporating Coulomb friction effects shows that the viscous damping of the haptic device affects the maximum displayable stiffness in steady-state and that the Coulomb friction of the device contributes to temporarily enhance rate-hardness in initial transient responses. Experimental results are presented for showing effectiveness of the proposed derivation and control law.",
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"title": "Adaptive Sliding Mode Control for Omnidirectional Mobile Robot Based on a New Friction Modeling",
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"abstract": "Due to the special structure of omni-directional wheels, friction forces among hubs, wheels and ground have a great influence on the motion accuracy of four-wheeled omnidirectional mobile robot. In order to reduce the effect of friction on motion control system, this paper proposes an adaptive sliding mode controller (ASMC) based on the dynamic model considering the friction on omni-directional wheels. The research on the omni-directional wheels friction force is described in detail, which lays a foundation for the accurate control of omnidirectional mobile robot. Firstly, the paper analyzes the Coulomb's friction on the driving wheel and the driven wheel respectively which is introduced to the friction model of the omni-directional wheel. Secondly, a new adaptive sliding mode control method is proposed to address the friction problem. Finally, the validity and performance of the control method are verified by simulations.",
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