The Synthetic Aperture Radar (SAR) system is a kind of modern high-resolution microwave imaging radar used in all-weather and all day long to provide remote sensing means and generate high resolution images of the lan...
详细信息
The global open source software resources have become an Internet-scale repository, which provide abundant resources for software reuse. However, how to locate the desired resource efficiently and accurately from such...
详细信息
Software projects are not developed in isolation but often build upon other open source resources. These projects form a kind of reference ecosystem regarded as a software world. Most of social computing works focus o...
详细信息
In this paper, an improved algorithm is proposed for the reconstruction of singularity connectivity from the available pairwise connections during preprocessing phase. To evaluate the performance of our algorithm, an ...
详细信息
Bloom filters are frequently used to to check the membership of an item in a set. However, Bloom filters face a dilemma: the transmission bandwidth and the accuracy cannot be optimized simultaneously. This dilemma is ...
详细信息
With the rapid development of open source software, various elements such as OSS, developers, users and online posts, across different communities and their interactions constitute a novel software ecosystem. Most of ...
详细信息
With the social networks getting increasingly larger, fast community detection algorithms like the label propagation algorithm, are attracting more attention. But the label propagation algorithm deals vertices with no...
详细信息
Convolutional neural networks (CNNs) are widely used in many computer vision applications. Previous FPGA implementations of CNNs are mainly based on the conventional convolutional algorithm. However, the high arithmet...
Convolutional neural networks (CNNs) are widely used in many computer vision applications. Previous FPGA implementations of CNNs are mainly based on the conventional convolutional algorithm. However, the high arithmetic complexity of conventional convolution algorithm for CNNs restricts the performance of accelerators and significantly increases the challenges of design. It has been proved that the Winograd algorithm for CNNs can effectively reduce the computational complexity. Although a few FPGA approaches based on the Winograd algorithm have been implemented, their works are lake of evaluation on the performance for different tile sizes of the Winograd algorithm. In this work, we focus on exploring the possibility of using the Winograd algorithm to accelerate CNNs on FPGA. First, we propose an accelerator architecture applying to both convolutional layers and fully connected layers. Second, we use high level synthesis tool to expediently implement our design. Finally, we evaluate our accelerator with different tile sizes in terms of resource utilization, performance and efficiency. On VUS440 platform, we achieve an average 943 GOPS for overall VGG16 under low resource utilization, which reaches higher efficiency than the state-of-the-art works on FPGAs.
Fingerprint has been widely used in a variety of biometric identification systems in the past several years due to its uniqueness and immutability. With the rapid development of fingerprint identification techniques, ...
详细信息
Fingerprint has been widely used in a variety of biometric identification systems in the past several years due to its uniqueness and immutability. With the rapid development of fingerprint identification techniques, many fingerprint identification systems are in urgent need to deal with large-scale fingerprint storage and high concurrent recognition queries, which bring huge challenges to the system. In this circumstance, we design and implement a distributed and load-balancing fingerprint identification system named Pegasus, which includes a distributed feature extraction subsystem and a distributed feature storage subsystem. The feature extraction procedure combines the Hadoop Image processing Interface(HIPI) library to enhance its overall processing speed; the feature storage subsystem optimizes MongoD B's default load balance strategy to improve the efficiency and robustness of *** and simulations are carried out, and results show that Pegasus can reduce the time cost by 70% during the feature extraction procedure. Pegasus also balances the difference of access load among front-end mongos nodes to less than 5%. Additionally, Pegasus reduces over 40% of data migration among back-end data shards to obtain a more reasonable data distribution based on the operation load(insertion, deletion, update, and query) of each shard.
暂无评论