A5071939085- Machine Learning in Materials Science
- Computational Drug Discovery Methods
- Viral Infectious Diseases and Gene Expression in Insects
- Water Quality Monitoring and Analysis
- Metaheuristic Optimization Algorithms Research
- Advanced Memory and Neural Computing
- Parallel Computing and Optimization Techniques
- Evolutionary Algorithms and Applications
- Quantum-Dot Cellular Automata
- Low-power high-performance VLSI design
- Protein Structure and Dynamics
Southeast University
2021-2023
AutoDock Vina is one of the most popular molecular docking tools. In latest benchmark CASF-2016 for comparative assessment scoring functions, won best power among all Modern drug discovery facing a common scenario large virtual screening hits from huge compound databases. Due to seriality characteristic algorithm, there no successful report on its parallel acceleration with GPUs. Current typically relies stack computing as well allocation resource and tasks, such VirtualFlow platform. The...
Simulated Annealing (SA) algorithm is not effective with large optimization problems for its slow convergence. Hence, several parallel (pSA) methods have been proposed, where the increase of searching threads can boost speed Although satisfactory solutions be obtained by these methods, there no rigorous mathematical analyses on their effectiveness. Thus, this article introduces a probabilistic model, which theorem about effectiveness multiple initial states SA (MISPSA) has proven. The also...
Molecular docking (MD) is one of the core steps in expensive and time-consuming process drug design, which basically an optimization problem based on scoring functions. AutoDock series MD software widely accepted by academia industry, among Vina (Vina) latest most popular version due to its accuracy relatively high speed. However, contrast prior version, i.e., AutoDock4, hardware acceleration approaches are rarely reported. In this article, we propose Vina-field-programmable gate array...
Simulated Annealing (SA) algorithm is not effective with large optimization problems for its slow convergence. Hence, several parallel (pSA) methods have been proposed, where the increase of searching threads can boost speed Although these obtain satisfactory solutions to problems, there no rigorous mathematical analyses on their effectiveness. Thus, this paper introduces a probabilistic model, which theorem about effectiveness multiple initial states SA (MISPSA) has proven. The also...
To improve the performance of SRAM in caches under near-threshold voltages, several timing speculation techniques, such as cross-sensing (CS-SRAM), are proposed. Meanwhile, for a given process, voltage, and temperature (PVT) condition, CS-SRAM has an optimal bitline discharging time (TBL) to achieve lowest average access latency. However, existing do not track variations different PVT conditions adjust TBL point, on which system possesses memory time. In this article, we propose design...