| Reveal training performance mystery between TensorFlow and PyTorch in the single GPU environment | 0 | 0.34 | 2022 |
| vChecker: an application-level demand-based co-scheduler for improving the performance of parallel jobs in Xen | 0 | 0.34 | 2022 |
| PSNet: Fast Data Structuring for Hierarchical Deep Learning on Point Cloud | 0 | 0.34 | 2022 |
| Deep cross-modal discriminant adversarial learning for zero-shot sketch-based image retrieval | 0 | 0.34 | 2022 |
| TDGraph: a topology-driven accelerator for high-performance streaming graph processing | 0 | 0.34 | 2022 |
| Developing an Unsupervised Real-Time Anomaly Detection Scheme for Time Series With Multi-Seasonality | 0 | 0.34 | 2022 |
| Allocating Resource Capacities for an Offload-enabled Mobile Edge Cloud System | 0 | 0.34 | 2022 |
| Contention-aware prediction for performance impact of task co-running in multicore computers | 0 | 0.34 | 2022 |
| An On-Line Virtual Machine Consolidation Strategy for Dual Improvement in Performance and Energy Conservation of Server Clusters in Cloud Data Centers | 1 | 0.35 | 2022 |
| Feluca: A Two-Stage Graph Coloring Algorithm With Color-Centric Paradigm on GPU | 0 | 0.34 | 2021 |
| SAFA: A Semi-Asynchronous Protocol for Fast Federated Learning With Low Overhead | 10 | 0.59 | 2021 |
| A Power Consumption Model for Cloud Servers Based on Elman Neural Network | 0 | 0.34 | 2021 |
| An Efficiency-Boosting Client Selection Scheme for Federated Learning With Fairness Guarantee | 6 | 0.50 | 2021 |
| TurboDL: Improving the CNN Training on GPU With Fine-Grained Multi-Streaming Scheduling | 0 | 0.34 | 2021 |
| MGGAN: Improving sample generations of Generative Adversarial Networks | 0 | 0.34 | 2021 |
| Accelerating Federated Learning Over Reliability-Agnostic Clients in Mobile Edge Computing Systems | 4 | 0.42 | 2021 |
| DepGraph: A Dependency-Driven Accelerator for Efficient Iterative Graph Processing | 1 | 0.35 | 2021 |
| LCCG: a locality-centric hardware accelerator for high throughput of concurrent graph processing | 0 | 0.34 | 2021 |
| Developing a Loss Prediction-based Asynchronous Stochastic Gradient Descent Algorithm for Distributed Training of Deep Neural Networks. | 0 | 0.34 | 2020 |
| Developing a Semantic-Driven Hybrid Segmentation Method for Point Clouds of 3D Shapes. | 0 | 0.34 | 2020 |
| WolfGraph: The edge-centric graph processing on GPU | 0 | 0.34 | 2020 |
| A parameter-level parallel optimization algorithm for large-scale spatio-temporal data mining | 1 | 0.35 | 2020 |
| Minimizing Financial Cost of DDoS Attack Defense in Clouds With Fine-Grained Resource Management | 2 | 0.37 | 2020 |
| A reformed task scheduling algorithm for heterogeneous distributed systems with energy consumption constraints | 0 | 0.34 | 2020 |
| GraphM: an efficient storage system for high throughput of concurrent graph processing | 3 | 0.37 | 2019 |
| Developing the Parallelization Methods for Finding the All-Pairs Shortest Paths in Distributed Memory Architecture | 0 | 0.34 | 2019 |
| WolfPath : accelerating Iterative Traversing-Based Graph Processing Algorithms on GPU | 0 | 0.34 | 2019 |
| CGraph: A Distributed Storage and Processing System for Concurrent Iterative Graph Analysis Jobs | 2 | 0.36 | 2019 |
| Optimizing the SSD Burst Buffer by Traffic Detection | 0 | 0.34 | 2019 |
| Modelling and developing conflict-aware scheduling on large-scale data centres. | 1 | 0.35 | 2018 |
| Scheduling DAG Applications for Time Sharing Systems. | 0 | 0.34 | 2018 |
| Concurrent hash tables on multicore machines: Comparison, evaluation and implications. | 0 | 0.34 | 2018 |
| Developing a pattern discovery method in time series data and its GPU acceleration. | 1 | 0.35 | 2018 |
| vGrouper - Optimizing the Performance of Parallel Jobs in Xen by Increasing Synchronous Execution of Virtual Machines. | 0 | 0.34 | 2018 |
| Energy-efficient hadoop for big data analytics and computing: A systematic review and research insights. | 3 | 0.37 | 2018 |
| Data Fine-Pruning - A Simple Way to Accelerate Neural Network Training. | 0 | 0.34 | 2018 |
| Developing Co-scheduling Mechanisms for Virtual Machines in Clouds | 1 | 0.36 | 2017 |
| Multi-resource scheduling and power simulation for cloud computing. | 30 | 0.78 | 2017 |
| Policy-Customized: A New Abstraction for Building Security as a Service | 0 | 0.34 | 2017 |
| Modeling the Power Variability of Core Speed Scaling on Homogeneous Multicore Systems. | 1 | 0.36 | 2017 |
| Robot Cloud: Bridging the power of robotics and cloud computing. | 11 | 0.55 | 2017 |
| Performance analysis and optimization for workflow authorization. | 1 | 0.35 | 2017 |
| Developing power-aware scheduling mechanisms for computing systems virtualized by Xen. | 0 | 0.34 | 2017 |
| Lifetime-Based Memory Management for Distributed Data Processing Systems. | 0 | 0.34 | 2016 |
| Redundant Network Traffic Elimination with GPU Accelerated Rabin Fingerprinting. | 2 | 0.38 | 2016 |
| Developing graph-based co-scheduling algorithms on multicore computers | 5 | 0.41 | 2016 |
| Resource Management in Virtualized Clouds. | 0 | 0.34 | 2016 |
| Developing A Trustworthy Computing Framework For Clouds | 0 | 0.34 | 2016 |
| Enabling User-Policy-Confined VM Migration in Trusted Cloud Computing | 0 | 0.34 | 2016 |
| Lifetime-Based Memory Management for Distributed Data Processing Systems. | 15 | 0.69 | 2016 |
