標(biāo)題: Titlebook: Applied Reconfigurable Computing. Architectures, Tools, and Applications; 14th International S Nikolaos Voros,Michael Huebner,Pedro C. Dini [打印本頁] 作者: 巡洋 時間: 2025-3-21 16:06
書目名稱Applied Reconfigurable Computing. Architectures, Tools, and Applications影響因子(影響力)
書目名稱Applied Reconfigurable Computing. Architectures, Tools, and Applications影響因子(影響力)學(xué)科排名
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書目名稱Applied Reconfigurable Computing. Architectures, Tools, and Applications網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Applied Reconfigurable Computing. Architectures, Tools, and Applications被引頻次
書目名稱Applied Reconfigurable Computing. Architectures, Tools, and Applications被引頻次學(xué)科排名
書目名稱Applied Reconfigurable Computing. Architectures, Tools, and Applications年度引用
書目名稱Applied Reconfigurable Computing. Architectures, Tools, and Applications年度引用學(xué)科排名
書目名稱Applied Reconfigurable Computing. Architectures, Tools, and Applications讀者反饋
書目名稱Applied Reconfigurable Computing. Architectures, Tools, and Applications讀者反饋學(xué)科排名
作者: Contort 時間: 2025-3-21 23:30
Applied Reconfigurable Computing. Architectures, Tools, and Applications978-3-319-78890-6Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 大洪水 時間: 2025-3-22 04:28
Image Re-processing of Satellite Imageries,searchers have found that the achievable performance highly depends on the interface between memory and CGRA. In this contribution we show that a smart prefetching mechanism can increase the performance of the CGRA. At the same time it consumes less hardware resources and energy as state of the art prefetching mechanisms.作者: defeatist 時間: 2025-3-22 08:12
Stacia Ryder,Michael Mikulewiczing Artificial Intelligence tasks. Nevertheless, the highest performing LSTM models are becoming increasingly demanding in terms of computational and memory load. At the same time, emerging latency-sensitive applications including mobile robots and autonomous vehicles often operate under stringent c作者: Psa617 時間: 2025-3-22 09:12
Potential and Flow Visualizationred to many conventional feature-based computer vision algorithms. However, the high computational complexity of CNN models can lead to low system performance in power-efficient applications. In this work, we firstly highlight two levels of model redundancy which widely exist in modern CNNs. Additio作者: 擦掉 時間: 2025-3-22 13:59 作者: CAMP 時間: 2025-3-22 17:17
https://doi.org/10.1007/978-3-642-22042-5nected to other nodes. Unlike other multi-FPGA systems, the circuit switching fabric with the STDM (Static Time Division Multiplexing) is implemented on the FPGA for predictable communication and cost-efficient data broadcasting. Parallel convolution modules for AlexNet are implemented on FiC-SW1 pr作者: Talkative 時間: 2025-3-22 22:03
Streamfunction and Complex Potentialsuch as object recognition and object detection. Most of these solutions come at a huge computational cost, requiring billions of multiply-accumulate operations and, thus, making their use quite challenging in real-time applications that run on embedded mobile (resource-power constrained) hardware. 作者: Aggregate 時間: 2025-3-23 04:49 作者: 濃縮 時間: 2025-3-23 09:08 作者: 倒轉(zhuǎn) 時間: 2025-3-23 10:05
Image Re-processing of Satellite Imageries,searchers have found that the achievable performance highly depends on the interface between memory and CGRA. In this contribution we show that a smart prefetching mechanism can increase the performance of the CGRA. At the same time it consumes less hardware resources and energy as state of the art 作者: amputation 時間: 2025-3-23 15:09
Surface Water Pathway Analysis, mapping large designs is greatly affected by the long runtime of FPGA CAD flow. To mitigate it, modular design methodology has been introduced in the past that allows designers to partition large designs into smaller modules and compile & test the modules individually before assembling them togethe作者: Immunotherapy 時間: 2025-3-23 21:08
Principles of Environmental Modeling,hitecture platform. KF is realized using Modified Faddeeva Algorithm (MFA) as a basic building block due to its versatility and REDEFINE Coarse Grained Reconfigurable Architecture (CGRA) is used as a platform for experiments since REDEFINE is capable of supporting realization of a set algorithmic co作者: Statins 時間: 2025-3-23 22:38
Nuno Videira,Paula Antunes,Rui Santosng or pattern recognition in artificial intelligence while realizing high cost-performance and energy efficiency. To achieve this goal, optimizing different aspects of the system communication is a key challenge. In order to do this, a preliminary study on the application mapping for both the execut作者: 治愈 時間: 2025-3-24 06:15
Environmental Modelling and Predictionin using them for further computations. In this paper, we present an FPGA accelerator for checking resolution proofs, a popular proof format. Our accelerator exploits parallelism at the low level by implementing the basic resolution step in hardware, and at the high level by instantiating a number o作者: 燈泡 時間: 2025-3-24 07:23
https://doi.org/10.1007/978-3-662-04868-9rmed in two phases: in the Bing Bang phase, similarly to other Genetic Algorithms (GAs) it generates a random population of candidate solutions, while in the Big Crunch phase it shrinks these candidates around an optimal point via a center-of-mass or minimal cost approach. It has been shown that the作者: 使苦惱 時間: 2025-3-24 14:11 作者: 思鄉(xiāng)病 時間: 2025-3-24 18:13
Ocean Modelling and Prediction,-speed networks, NIDS needs to be high-speed hardware and parallelization is inevitable. The pattern matching of PCRE (Perl Compatible Regular Expressions) is one of the most complex parts in NIDS. We tried to improve the parallelization of PCRE pattern matching in Snort, implementing it on an FPGA.作者: 轎車 時間: 2025-3-24 20:15
https://doi.org/10.1007/978-3-319-78890-6artificial intelligence; computer architecture; data communication systems; energy efficiency; field pro作者: malapropism 時間: 2025-3-25 00:13
978-3-319-78889-0Springer International Publishing AG, part of Springer Nature 2018作者: 外形 時間: 2025-3-25 04:27
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/160099.jpg作者: hypotension 時間: 2025-3-25 09:32 作者: PLAYS 時間: 2025-3-25 14:01
0302-9743 daptive architectures; design methods and fast prototyping; FPGA-based design and applications; and special session: research projects.?.978-3-319-78889-0978-3-319-78890-6Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: Obloquy 時間: 2025-3-25 18:10
Potential and Flow Visualizationt, our RR-mobileNet has 25. less parameters, 3.2. less operations per image inference but 9%/5.2% higher Top1/Top5 classification accuracy on ImageNet classification task. The latency of a single image inference is only 7.85?ms.作者: Nonporous 時間: 2025-3-25 21:27 作者: ESO 時間: 2025-3-26 00:58 作者: 四溢 時間: 2025-3-26 07:21
Principles of Environmental Modeling,rovement in terms of Gflops/watt over several academically and commercially available realizations of KF is attained. In REDEFINE, we show that our implementation is scalable and the performance attained is commensurate with the underlying hardware resources.作者: 有雜色 時間: 2025-3-26 09:48 作者: 職業(yè)拳擊手 時間: 2025-3-26 14:45 作者: 放大 時間: 2025-3-26 20:27 作者: GNAW 時間: 2025-3-26 22:06
Achieving Efficient Realization of Kalman Filter on CGRA Through Algorithm-Architecture Co-designrovement in terms of Gflops/watt over several academically and commercially available realizations of KF is attained. In REDEFINE, we show that our implementation is scalable and the performance attained is commensurate with the underlying hardware resources.作者: 愛得痛了 時間: 2025-3-27 02:45
https://doi.org/10.1007/978-3-642-22042-5ototype boards consisting of Kintex Ultrascale FPGA, and evaluation results show that the parallel execution with 20 boards achieved 4.6 times better performance than the state of art implementation on a single Virtex 7 FPGA board.作者: 使激動 時間: 2025-3-27 08:56 作者: 顧客 時間: 2025-3-27 09:47 作者: 豐富 時間: 2025-3-27 15:42
Streamfunction and Complex Potentiale of the SqueezeNet DCNN architecture, which is designed specifically for use in embedded systems. Results show that SqueezeJet can achieve 15.16 times speed-up compared to the software implementation of SqueezeNet running on an embedded mobile processor with less than 1% drop in?top-5 accuracy.作者: monopoly 時間: 2025-3-27 19:58
Introduction to Computational Techniques,ons. While the main focus of this work is flexibility, we are able to show maximum throughput for connections between two FPGAs and up?to 88% saturation of the available bandwidth for connections between the FPGA and the host system.作者: META 時間: 2025-3-28 02:00
Environmental Modelling and Predictionelerator memory. The results show that while the accelerator is scalable and achieves speedups for all benchmark proofs, performance improvements are currently limited by the overhead of transitioning the proof into the accelerator memory.作者: vertebrate 時間: 2025-3-28 05:12 作者: 文件夾 時間: 2025-3-28 07:14 作者: 同音 時間: 2025-3-28 14:12
An FPGA/HMC-Based Accelerator for?Resolution Proof Checkingelerator memory. The results show that while the accelerator is scalable and achieves speedups for all benchmark proofs, performance improvements are currently limited by the overhead of transitioning the proof into the accelerator memory.作者: hieroglyphic 時間: 2025-3-28 18:16
Deep Learning on High Performance FPGA Switching Boards: Flow-in-Cloudototype boards consisting of Kintex Ultrascale FPGA, and evaluation results show that the parallel execution with 20 boards achieved 4.6 times better performance than the state of art implementation on a single Virtex 7 FPGA board.作者: 非秘密 時間: 2025-3-28 21:12
Towards an Optimized Multi FPGA Architecture with STDM Network: A?Preliminary Studyion time and the number of slots for the STDM is carried out. An optimization based on a multi-criteria paradigm is implemented and the preliminary results show the possibility to optimize several parameters of the communication simultaneously alongside quantitative analyses of different architecture choices.作者: 根除 時間: 2025-3-28 23:20 作者: amyloid 時間: 2025-3-29 04:13
Conference proceedings 2018sed design and CGRA optimizations; applications and surveys; fault-tolerance, security and communication architectures; reconfigurable and adaptive architectures; design methods and fast prototyping; FPGA-based design and applications; and special session: research projects.?.作者: 反復(fù)無常 時間: 2025-3-29 10:58
0302-9743 Greece, in May 2018.?. The 29 full papers and 22 short presented in this volume were carefully reviewed and selected from 78 submissions. In addition, the volume contains 9 contributions from research projects. The papers were organized in topical sections named: machine learning and neural network作者: 合并 時間: 2025-3-29 12:05 作者: 設(shè)想 時間: 2025-3-29 16:09 作者: 粗魯?shù)娜?nbsp; 時間: 2025-3-29 21:13 作者: 向前變橢圓 時間: 2025-3-30 00:48 作者: labile 時間: 2025-3-30 06:35
FPGA-Based Memory Efficient Shift-And Algorithm for Regular Expression Matching作者: 腐蝕 時間: 2025-3-30 09:37
Applied Reconfigurable Computing. Architectures, Tools, and Applications14th International S作者: Fracture 時間: 2025-3-30 14:19
Stacia Ryder,Michael Mikulewiczperformance LSTM execution in time-constrained applications. Quantitative evaluation on a real-life image captioning application indicates that the proposed system required up?to 6.5. less time to achieve the same application-level accuracy compared to a baseline method, while achieving an average o作者: disciplined 時間: 2025-3-30 20:19
Potential and Flow Visualizationlly provide insightful observation. For example, one of our tests show 32-bit floating point is more hardware efficient than 1-bit parameters to achieve 99% MNIST accuracy. In general, 2-bit and 4-bit fixed point parameters show better hardware trade-off on small-scale datasets like MNIST and CIFAR-作者: LAST 時間: 2025-3-30 21:49 作者: 不朽中國 時間: 2025-3-31 03:26
Matthew H. England,Peter R. Oke relevant information. Through this paper, we present ReneGENE-GI, an innovatively engineered GI pipeline. We also present the performance analysis of ReneGENE-GI’s Comparative Genomics Module (CGM), prototyped on a reconfigurable bio-computing accelerator platform. Alignment time for this prototype作者: myriad 時間: 2025-3-31 06:51
Approximate FPGA-Based LSTMs Under Computation Time Constraintsing Artificial Intelligence tasks. Nevertheless, the highest performing LSTM models are becoming increasingly demanding in terms of computational and memory load. At the same time, emerging latency-sensitive applications including mobile robots and autonomous vehicles often operate under stringent c作者: 過濾 時間: 2025-3-31 09:26
Redundancy-Reduced MobileNet Acceleration on Reconfigurable Logic for ImageNet Classificationred to many conventional feature-based computer vision algorithms. However, the high computational complexity of CNN models can lead to low system performance in power-efficient applications. In this work, we firstly highlight two levels of model redundancy which widely exist in modern CNNs. Additio作者: 引起痛苦 時間: 2025-3-31 15:53 作者: 上漲 時間: 2025-3-31 18:41
Deep Learning on High Performance FPGA Switching Boards: Flow-in-Cloudnected to other nodes. Unlike other multi-FPGA systems, the circuit switching fabric with the STDM (Static Time Division Multiplexing) is implemented on the FPGA for predictable communication and cost-efficient data broadcasting. Parallel convolution modules for AlexNet are implemented on FiC-SW1 pr作者: characteristic 時間: 2025-3-31 23:50
SqueezeJet: High-Level Synthesis Accelerator Design for Deep Convolutional Neural Networkssuch as object recognition and object detection. Most of these solutions come at a huge computational cost, requiring billions of multiply-accumulate operations and, thus, making their use quite challenging in real-time applications that run on embedded mobile (resource-power constrained) hardware.
