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检索条件"任意字段=FPGA 2000: ACM/SIGDA International Symposium on Field Programmable Gate Arrays"
1376 条 记 录,以下是291-300 订阅
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Towards Trainable Synthesis for Optimized Circuit Deployment on fpga  29
Towards Trainable Synthesis for Optimized Circuit Deployment...
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29th international symposium on Rapid System Prototyping, RSP 2018
作者: Legault, Jean-Philippe Patros, Panagiotis Kent, Kenneth B. Faculty of Computer Science University of New Brunswick FrederictonNB Canada Department of Computer Science University of Waikato Hamilton Waikato New Zealand
field programmable gate arrays (fpgas) utilize multiple programmable elements and non-programmable blocks. After synthesizing an input Hardware Design Language (HDL) design into a circuit, optimizations are used to di... 详细信息
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Xilinx Adaptive Compute Acceleration Platform: VersalTM Architecture  19
Xilinx Adaptive Compute Acceleration Platform: VersalTM Arch...
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Proceedings of the 2019 acm/sigda international symposium on field-programmable gate arrays
作者: Brian Gaide Dinesh Gaitonde Chirag Ravishankar Trevor Bauer Xilinx Inc. Longmont CO USA Xilinx Inc. San Jose CA USA
In this paper we describe Xilinx's Versal-Adaptive Compute Acceleration Platform (ACAP). ACAP is a hybrid compute platform that tightly integrates traditional fpga programmable fabric, software programmable proces... 详细信息
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A Lightweight YOLOv2: A Binarized CNN with A Parallel Support Vector Regression for an fpga  18
A Lightweight YOLOv2: A Binarized CNN with A Parallel Suppor...
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acm/sigda international symposium on field-programmable gate arrays (fpga)
作者: Nakahara, Hiroki Yonekawa, Haruyoshi Fujii, Tomoya Sato, Shimpei Tokyo Inst Technol Tokyo Japan
A frame object detection problem consists of two problems: one is a regression problem to spatially separated bounding boxes, the second is the associated classification of the objects within realtime frame rate. It i... 详细信息
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Towards a Uniform Template-based Architecture for Accelerating 2D and 3D CNNs on fpga  18
Towards a Uniform Template-based Architecture for Accelerati...
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acm/sigda international symposium on field-programmable gate arrays (fpga)
作者: Shen, Junzhong Huang, You Wang, Zelong Qiao, Yuran Wen, Mei Zhang, Chunyuan Natl Univ Def Technol Coll Comp Natl Key Lab Parallel & Distributed Proc Changsha Hunan Peoples R China
Three-dimensional convolutional neural networks (3D CNNs) are used efficiently in many computer vision applications. Most previous work in this area has concentrated only on designing and optimizing accelerators for 2... 详细信息
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A Framework for Generating High Throughput CNN Implementations on fpgas  18
A Framework for Generating High Throughput CNN Implementatio...
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acm/sigda international symposium on field-programmable gate arrays (fpga)
作者: Zeng, Hanqing Chen, Ren Zhang, Chi Prasanna, Viktor Univ Southern Calif Ming Hsieh Dept Elect Engn Los Angeles CA 90007 USA Univ Southern Calif Dept Comp Sci Los Angeles CA 90007 USA
We propose a framework to generate highly efficient accelerators for inferencing on fpgas. Our framework consists of multiple algorithmic optimizations for computation complexity and communication volume reduction, a ... 详细信息
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C-LSTM: Enabling Efficient LSTM using Structured Compression Techniques on fpgas  18
C-LSTM: Enabling Efficient LSTM using Structured Compression...
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acm/sigda international symposium on field-programmable gate arrays (fpga)
作者: Wang, Shuo Li, Zhe Ding, Caiwen Yuan, Bo Qiu, Qinru Wang, Yanzhi Liang, Yun Peking Univ Ctr Energy Efficient Comp & Applicat CECA Sch EECS Beijing Peoples R China Syracuse Univ Dept Elect Engn & Comp Sci Syracuse NY USA CUNY Dept Elect Engn New York NY 10021 USA
Recently, significant accuracy improvement has been achieved for acoustic recognition systems by increasing the model size of Long Short-Term Memory (LSTM) networks. Unfortunately, the ever-increasing size of LSTM mod... 详细信息
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FASTCF: fpga-based Accelerator for STochastic-Gradient-Descent-based Collaborative Filtering  18
FASTCF: FPGA-based Accelerator for STochastic-Gradient-Desce...
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acm/sigda international symposium on field-programmable gate arrays (fpga)
作者: Zhou, Shijie Kannan, Rajgopal Min, Yu Prasanna, Viktor K. Univ Southern Calif Los Angeles CA 90089 USA US Army Res Lab Los Angeles CA 90094 USA
Sparse matrix factorization using Stochastic Gradient Descent (SGD) is a popular technique for deriving latent features from observations. SGD is widely used for Collaborative Filtering (CF), itself a well-known machi... 详细信息
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Nuclear Reactor Simulations on OpenCL fpga Platform  19
Nuclear Reactor Simulations on OpenCL FPGA Platform
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Proceedings of the 2019 acm/sigda international symposium on field-programmable gate arrays
作者: Zheming Jin Hal Finkel Argonne National Laboratory Lemont IL USA
field-programmable gate arrays (fpgas) are becoming a promising choice as a heterogeneous computing component for scientific computing when floating-point optimized architectures are added to the current fpgas. The ma... 详细信息
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A Customizable Matrix Multiplication Framework for the Intel HARPv2 Xeon+fpga Platform A Deep Learning Case Study  18
A Customizable Matrix Multiplication Framework for the Intel...
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acm/sigda international symposium on field-programmable gate arrays (fpga)
作者: Moss, Duncan J. M. Krishnan, Srivatsan Nurvitadhi, Eriko Ratuszniak, Piotr Johnson, Chris Sim, Jaewoong Mishra, Asit Marr, Debbie Subhaschandra, Suchit Leong, Philip H. W. Intel Corp Santa Clara CA 95051 USA Koszalin Univ Technol Koszalin Poland Univ Sydney Sydney NSW Australia
General Matrix to Matrix multiplication (GEMM) is the cornerstone for a wide gamut of applications in high performance computing (HPC), scientific computing (SC) and more recently, deep learning. In this work, we pres... 详细信息
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Sparse Winograd Convolutional Neural Networks on Small-scale Systolic arrays  19
Sparse Winograd Convolutional Neural Networks on Small-scale...
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Proceedings of the 2019 acm/sigda international symposium on field-programmable gate arrays
作者: Feng Shi Haochen Li Yuhe Gao Benjamin Kuschner Song-Chun Zhu University of California Los Angeles Los Angeles CA USA University of Hong Kong Hong Kong China
The reconfigurability, energy-efficiency, and massive parallelism on fpgas make them one of the best choices for implementing efficient deep learning accelerators. However, state-of-art implementations seldom consider... 详细信息
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