腐蚀
发表于 2025-3-30 09:37:55
Applied Reconfigurable Computing. Architectures, Tools, and Applications14th International S
Fracture
发表于 2025-3-30 14:19:53
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
disciplined
发表于 2025-3-30 20:19:31
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-
LAST
发表于 2025-3-30 21:49:26
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不朽中国
发表于 2025-3-31 03:26:34
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
myriad
发表于 2025-3-31 06:51:59
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
过滤
发表于 2025-3-31 09:26:22
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
引起痛苦
发表于 2025-3-31 15:53:40
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上涨
发表于 2025-3-31 18:41:58
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
characteristic
发表于 2025-3-31 23:50:02
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.