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检索条件"任意字段=Conference on High Performance Computer Modernization Program"

共 10259 条记录，以下是101-110 订阅

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high-Level Synthesis of FPGA-Based Chirp Match Filtering for Synthetic Aperture Radar Systems 13

High-Level Synthesis of FPGA-Based Chirp Match Filtering for...

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2024 International conference on Radar Antenna Microwave Electronics and Telecommunications

作者： Wiyono, Agus Abner, Jefri Chasanah, Nurul Aditya, Satria Arief Wahyudi, Agus Fiendra Ruhiyat, Abdurrasyid Rohman, Abdul Firmansyah, Iman Arisandi, Effendi Dodi Arisal, Andria Kurniawan, Farohaji Setiadi, Bambang Natl Res & Innovat Agcy Res Ctr Aeronaut Bogor Indonesia Natl Res & Innovat Agcy Res Ctr Telecommun Bandung Indonesia Natl Res & Innovat Agcy Res Ctr Rocket Bogor Indonesia Natl Res & Innovat Agcy RC Data & Informat Sci Bandung Indonesia

ISBN: (纸本)9798350389937;9798350389920

This paper presents the implementation of chirp match filtering for Synthetic Aperture Radar (SAR) on a field-programmable gate array (FPGA) using high-Level Synthesis (HLS). HLS enables higher productivity by significantly reducing development time compared to traditional hardware description languages (HDL). A C-based programming approach is employed to leverage parallel processing, which is critical for high-performance signal processing tasks. The design utilizes a symmetric chirp signal as the reference for match filtering, with optimizations implemented through parallelism in the filtering process. Experimental results show that the FPGA-based match filtering, programmed using HLS, achieves low latency and high performance, with a speed increase of 937 times compared to running the same process in Octave on a standard computer.

关键词： FPGA match-filtering high Level Synthesis chirp SAR

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Native DRAM Cache: Re-architecting DRAM as a Large-Scale Cache for Data Centers 51

Native DRAM Cache: Re-architecting DRAM as a Large-Scale Cac...

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ACM/IEEE 51st Annual International Symposium on computer Architecture (ISCA)

作者： Ryu, Yesin Kim, Yoojin Jung, Giyong Ahn, Jung Ho Kim, Jungrae Sungkyunkwan Univ Suwon South Korea Seoul Natl Univ Seoul South Korea Samsung Elect Hwaseong South Korea

ISBN: (纸本)9798350326598;9798350326581

Contemporary data center CPUs are experiencing an unprecedented surge in core count. This trend necessitates scrutinized Last-Level Cache (LLC) strategies to accommodate increasing capacity demands. While DRAM offers significant capacity, using it as a cache poses challenges related to latency and energy. This paper introduces Native DRAM Cache (NDC), a novel DRAM architecture specifically designed to operate as a cache. NDC features innovative approaches, such as conducting tag matching and way selection within a DRAM subarray and repurposing existing precharge transistors for tag matching. These innovations facilitate Caching-In-Memory (CIM) and enable NDC to serve as a high-capacity LLC with high set-associativity, low-latency, high-throughput, and low-energy. Our evaluation demonstrates that NDC significantly outperforms state-of-the-art DRAM cache solutions, enhancing performance by 2.8%/52.5%/44.2% (up to 8.4%/140.6%/85.5%) in SPEC/NPB/GAP benchmark suites, respectively.

关键词： Caching-In-Memory (CIM) DRAM Cache high-capacity LLC

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Queue-aware Network Control Algorithm with a high Quantum Computing Readiness-Evaluated in Discrete-time Flow Simulator for Fat-Pipe Networks 25

Queue-aware Network Control Algorithm with a High Quantum Co...

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IEEE 25th International conference on high performance Switching and Routing (HPSR)

作者： Witt, Arthur Univ Stuttgart Inst Commun Networks & Comp Engn Stuttgart Germany

ISBN: (纸本)9798350363869;9798350363852

The emerging technology of quantum computing has the potential to change the way how problems will be solved in the future. This work presents a centralized network control algorithm executable on already existing quantum computer which are based on the principle of quantum annealing like the D-Wave AdvantageT. We introduce a resource reoccupation algorithm for traffic engineering in wide-area networks. The proposed optimization algorithm changes traffic steering and resource allocation in case of overloaded transceivers. Settings of active components like fiber amplifiers and transceivers are not changed for the reason of stability. This algorithm is beneficial in situations when the network traffic is fluctuating in time scales of seconds or spontaneous bursts occur. Further, we developed a discrete-time flow simulator to study the algorithm's performance in wide-area networks. Our network simulator considers backlog and loss modeling of buffered transmission lines. Concurring flows are handled equally in case of a backlog. This work provides an ILP-based network configuring algorithm that is applicable on quantum annealing computers. We showcase, that traffic losses can be reduced significantly by a factor of 2 if a resource reoccupation algorithm is applied in a network with bursty traffic. As resources are used more efficiently by reoccupation in heavy load situations, overprovisioning of networks can be reduced. Thus, this new form of network operation leads toward a zero-margin network. We show that our newly introduced network simulator enables analyses of short-time effects like buffering within fat-pipe networks. As the calculation of network configurations in real-sized networks is typically time-consuming, quantum computing can enable the proposed network configuration algorithm for application in realsized wide-area networks.

关键词： integer linear program network automation network simulation optical fat-pipe networks quantum computing resource allocation zero-margin networks

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Training Teachers to Employ Design and Analysis of computer Experiments for Research on Sustainable Building Design

Training Teachers to Employ Design and Analysis of Computer ...

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2024 ASEE Annual conference and Exposition

作者： Thomason, Laura Chen, Victoria C.P. Jones, Erick Rosenberger, Jay Michael Sood, Jaivardhan Sharma, Vishnu Sharma Kaipu Prabhakar Mohammadpour, Soulmaz Rahman Smalls, Rahsirearl Dominick Sigler, Jocelyn Hovey, James Mansfield ISD The University of Texas Arlington United States The University of Texas Arlington United States Everman ISD The University of Texas Arlington United States

The construction industry is one of the largest consumers of natural resources, including water, materials, and energy. Towards the goal of more sustainable building design, we present a "tiny home" case study that demonstrates our proposed design and analysis of computer experiments (DACE) process for conducting a comprehensive study of potential building designs. As part of a National Science Foundation Research Experiences for Teachers project (EEC-2055705), two cohorts of Junior high/high School teachers were trained to conduct the DACE process, employing sustainable building design software tools as computer models for the experiments. In this paper, we propose and illustrate the DACE process as a training framework for novice researchers who are brand new to research. The DACE process provides a general set of research tools, consisting of four steps: (1) Calibration of the computer model(s) for the application of interest, (2) Design of experiments to organize a set of computer model input parameter settings, (3) Execution of the computer model(s) to generate performance metric outputs, (4) Analysis of the input and output data. For sustainable building design, the performance metric outputs represent dimensions related to the pillars of sustainability: people, planet, prosperity. The first cohort of teachers focused on Steps 1-3, and the second cohort conducted Steps 2-4. This paper first provides a general description of the DACE process and articulates the engineering education connection with the Industrial Engineering undergraduate curriculum, then describes the teachers' implementation of the DACE process for the tiny home case study, as well as some of their thoughts on the program and project. © American Society for Engineering Education, 2024.

关键词： Sustainable building

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Research on Control Technology of Mine high Energy density permanent magnet Direct Drive Integrated Machine based on fuzzy PID 3

Research on Control Technology of Mine High Energy density p...

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3rd International conference on Consumer Electronics and computer Engineering, ICCECE 2023

作者： Wang, Sen Chen, Nan Deng, Yunpeng Liang, Daili Xiao, Yanhui Wang, Wenshuo Yu, Wanhong Wang, Lei Zhu, Yuqin Zhang, Li Liu, Hao Yu, Zhanyang Du, Jianmin Shenyang Institute of Engineering Department of College of Automation Liaoning Shenyang China China Coal Technology and Engineering Group Shenyang Resreach Institute State Key Laboratory of Coal Mine Safety Technology 113122 China Shenyang University of Technology Liaoning Shenyang China

ISBN: (纸本)9798350331578

In order to improve the mining high energy density of permanent magnet direct drive all-in-one control performance and anti-interference ability, for the traditional PID control performance efficiency is not high, and the working environment changes, through the traditional PID control and fuzzy PID control control performance, puts forward a smart control method based on fuzzy PID control. The simulation model of the fuzzy PID controller is constructed and the simulation experiment is conducted. The simulation results show that the fuzzy PID controller, compared with the traditional PID controller, has stronger reliability. © 2023 IEEE.

关键词： Permanent magnets

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Accelerating GP Genome Evaluation Through Real Compilation with a Multiple program Single Data Approach

Accelerating GP Genome Evaluation Through Real Compilation w...

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2024 Genetic and Evolutionary Computation conference Companion, GECCO 2024 Companion

作者： De Melo, Vinícius Veloso Banzhaf, Wolfgang Iacca, Giovanni Nasdaq Toronto Canada Michigan State University East Lansing United States University of Trento Trento Italy

ISBN: (纸本)9798400704956

Genetic programming (GP) presents a unique challenge in fitness evaluation due to the need to repeatedly execute the evolved programs, often represented as tree structures, to assess their quality on multiple input data. Traditional approaches rely on interpreting these program trees, which can be computationally expensive. This paper proposes an optimization method that leverages code generation using a novel strategy and Just-In-Time (JIT) compilation to significantly improve the efficiency of fitness evaluation in GP. We propose to revisit using an actual compiler to transform a GP individual into native computer code executable quickly on the CPU. Our GP implementation is a simple tree-based approach that makes it easy for researchers to experiment with, while the evaluation function shows high performance. Preliminary results in Symbolic Regression on artificial datasets demonstrate that our approach is more than 6× faster than a popular GP framework that uses high-performance single-function evaluation but in a stack-based interpreter mode. © 2024 is held by the owner/author(s).

关键词： Genetic programming

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Beatnik: A Novel Global Communication Mini-Application

Beatnik: A Novel Global Communication Mini-Application

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2024 Workshops of the International conference for high performance Computing, Networking, Storage and Analysis, SC Workshops 2024

作者： Stewart, Jason R. Bridges, Patrick G. University of New Mexico Department of Computer Science Albuquerque United States

ISBN: (纸本)9798350355543

Beatnik is a novel open source mini-application that exercises the complex communication patterns often found in production codes but rarely found in benchmarks or mini-applications. It simulates 3D Raleigh-Taylor instabilities based on Pandya and Shkoller's Z-Model formulation using the Cabana performance portability framework. This paper presents both the high-level design and important implementation details about Beatnik along with four benchmark setups for evaluating different aspects of HPC communication system performance. Evaluation results demonstrate both Beatnik's scalability on modern accelerator-based systems using weak and strong scaling tests up to 1024 GPUs, along with Beatnik's ability to expose communication challenges in modern systems and solver libraries. © 2024 IEEE.

关键词： Benchmarking Communication Patterns Scalability

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Lightweight Video Denoising using Aggregated Shifted Window Attention 23

Lightweight Video Denoising using Aggregated Shifted Window ...

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23rd IEEE/CVF Winter conference on Applications of computer Vision (WACV)

作者： Lindner, Lydia Effland, Alexander Ilic, Filip Pock, Thomas Kobler, Erich Graz Univ Technol Graz Austria Univ Bonn Bonn Germany

ISBN: (纸本)9781665493468

Video denoising is a fundamental problem in numerous computer vision applications. State-of-the-art attention-based denoising methods typically yield good results, but require vast amounts of GPU memory and usually suffer from very long computation times. Especially in the field of restoring digitized high-resolution historic films, these techniques are not applicable in practice. To overcome these issues, we introduce a lightweight video denoising network that combines efficient axial-coronal-sagittal (ACS) convolutions with a novel shifted window attention formulation (ASwin), which is based on the memory-efficient aggregation of self- and cross-attention across video frames. We numerically validate the performance and efficiency of our approach on synthetic Gaussian noise. Moreover, we train our network as a general-purpose blind denoising model for real-world videos, using a realistic noise synthesis pipeline to generate clean-noisy video pairs. A user study and non-reference quality assessment prove that our method outperforms the state-of-the-art on real-world historic videos in terms of denoising performance and temporal consistency.

关键词： computer vision Runtime Films Noise reduction Memory management Pipelines Quality assessment

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SparseBEV: high-performance Sparse 3D Object Detection from Multi-Camera Videos

SparseBEV: High-Performance Sparse 3D Object Detection from ...

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IEEE/CVF International conference on computer Vision (ICCV)

作者： Liu, Haisong Teng, Yao Lu, Tao Wang, Haiguang Wang, Limin Nanjing Univ State Key Lab Novel Software Technol Nanjing Peoples R China Shanghai AI Lab Shanghai Peoples R China

ISBN: (纸本)9798350307184

Camera-based 3D object detection in BEV (Bird's Eye View) space has drawn great attention over the past few years. Dense detectors typically follow a two-stage pipeline by first constructing a dense BEV feature and then performing object detection in BEV space, which suffers from complex view transformations and high computation cost. On the other side, sparse detectors follow a query-based paradigm without explicit dense BEV feature construction, but achieve worse performance than the dense counterparts. In this paper, we find that the key to mitigate this performance gap is the adaptability of the detector in both BEV and image space. To achieve this goal, we propose SparseBEV, a fully sparse 3D object detector that outperforms the dense counterparts. SparseBEV contains three key designs, which are (1) scale-adaptive self attention to aggregate features with adaptive receptive field in BEV space, (2) adaptive spatio-temporal sampling to generate sampling locations under the guidance of queries, and (3) adaptive mixing to decode the sampled features with dynamic weights from the queries. On the test split of nuScenes, SparseBEV achieves the state-of-the-art performance of 67.5 NDS. On the val split, SparseBEV achieves 55.8 NDS while maintaining a real-time inference speed of 23.5 FPS. Code is available at https://***/MCG-NJU/SparseBEV.

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Salient Object Detection in Complex Backgrounds Guided by high-Level Feature Aggregation 4

Salient Object Detection in Complex Backgrounds Guided by Hi...

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4th International conference on computer Science and Blockchain, CCSB 2024

作者： Wang, Zhengkai Zhou, Yongxia College of Information Engineering China Jiliang University Zhejiang Province Hangzhou China

ISBN: (纸本)9798350356502

Salient object detection is essential for many computer vision tasks and aims to detect the most prominent objects in images. However, existing methods often perform poorly when dealing with complex scenes. To overcome these issues, we propose a novel salient object detection network. A Global Feature Enhancement Module (GEM) is designed to solve the problem of inaccurate object localization in complex scenes. GEM enhances the importance of high-level semantic information in the network, using high-level features to guide lower-level features. Additionally, we introduced a Local Feature Refinement Module (LRM) designed to enhance the capture and optimization of low-level details, aggregating coarse saliency features generated by GEM with finer features from each decoding stage. By progressively refining features, the network effectively suppresses shallow background noise and achieves precise saliency maps. Comparative experiments on five public datasets with twelve advanced methods demonstrate the superior performance and efficiency of our proposed method. © 2024 IEEE.

关键词： Object recognition

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