Simplifying the Euclidean projection onto check polytope is an efficient way to reduce the computational complexity of alternating direction method of multipliers (ADMM) decoding algorithm for ...low-density parity-check (LDPC) codes. Existing algorithms for check polytope projection require sorting operation or iterative operation, which happens to be the most complex part of the projection. In this letter, a novel and fast projection algorithm is proposed without sorting and iterative operations. In the proposed algorithm, line segment projection replaces check polytope projection to approach approximate Euclidean projection at low computational complexity. Simulation results show that the proposed algorithm can substantially reduce the projection time while maintaining the frame error rate (FER) performance. In particular, the proposed algorithm can save the average projection time by 43% compared with cut search algorithm (CSA) when the dimension of the input vector is 20.
AutoDock Vina is one of the most popular molecular docking tools. In the latest benchmark CASF-2016 for comparative assessment of scoring functions, AutoDock Vina won the best docking power among all ...the docking tools. Modern drug discovery is facing a common scenario of large virtual screening of drug hits from huge compound databases. Due to the seriality characteristic of the AutoDock Vina algorithm, there is no successful report on its parallel acceleration with GPUs. Current acceleration of AutoDock Vina typically relies on the stack of computing power as well as the allocation of resource and tasks, such as the VirtualFlow platform. The vast resource expenditure and the high access threshold of users will greatly limit the popularity of AutoDock Vina and the flexibility of its usage in modern drug discovery. In this work, we proposed a new method, Vina-GPU, for accelerating AutoDock Vina with GPUs, which is greatly needed for reducing the investment for large virtual screens and also for wider application in large-scale virtual screening on personal computers, station servers or cloud computing, etc. Our proposed method is based on a modified Monte Carlo using simulating annealing AI algorithm. It greatly raises the number of initial random conformations and reduces the search depth of each thread. Moreover, a classic optimizer named BFGS is adopted to optimize the ligand conformations during the docking progress, before a heterogeneous OpenCL implementation was developed to realize its parallel acceleration leveraging thousands of GPU cores. Large benchmark tests show that Vina-GPU reaches an average of 21-fold and a maximum of 50-fold docking acceleration against the original AutoDock Vina while ensuring their comparable docking accuracy, indicating its potential for pushing the popularization of AutoDock Vina in large virtual screens.
A new heterobimetallic nitrilotriacetatoperoxotitanate complex of titanium and lead Pb(H
2
O)
3
2
Ti
2
(O
2
)
2
O(nta)
2
·4H
2
O (C
6
H
6
O
6
N=H
3
nta) was isolated in pure crystals directly from ...the solution containing tetrabutyl orthotitanate, hydrogen peroxoide, lead acetate, and nitrilotriacetic acid at pH = 2.0–4.0. The isolated complex was characterized by elemental analyses, IR spectrum, thermal analysis (TG), and single-crystal X-ray diffraction. The single-crystal X-ray structural analysis revealed that the titanium atom is N,O,O′,O′′-chelated by the nitrilotriacetate and O,O′-chelated by the peroxo group and was coordinated to the bridging O atom in an overall pentagonal-bipyramidal geometry. The thermal decomposition of this precursor led to the formation of phase-pure lead titanate (PbTiO
3
) at ≥450 °C. The morphology, microstructure, and crystalline of the resulting PbTiO
3
product have been characterized by BET, transmission electron microscopy, and powder X-ray diffraction. The TEM micrographs revealed that the size of the as-synthesized crystallines to be 50–100 nm range. The BET measurement revealed that the PbTiO
3
powders had a surface area of 5.6 m
2
/g.
Modern drug discovery typically faces large virtual screens from huge compound databases where multiple docking tools are involved for meeting various real scenes or improving the precision of ...virtual screens. Among these tools, AutoDock Vina and its numerous derivatives are the most popular and have become the standard pipeline for molecular docking in modern drug discovery. Our recent Vina-GPU method realized 14-fold acceleration against AutoDock Vina on a piece of NVIDIA RTX 3090 GPU in one virtual screening case. Further speedup of AutoDock Vina and its derivatives with graphics processing units (GPUs) is beneficial to systematically push their popularization in large-scale virtual screens due to their high benefit-cost ratio and easy operation for users. Thus, we proposed the Vina-GPU 2.0 method to further accelerate AutoDock Vina and the most common derivatives with new docking algorithms (QuickVina 2 and QuickVina-W) with GPUs. Caused by the discrepancy in their docking algorithms, our Vina-GPU 2.0 adopts different GPU acceleration strategies. In virtual screening for two hot protein kinase targets, RIPK1 and RIPK3, from the DrugBank database, our Vina-GPU 2.0 reaches an average of 65.6-fold, 1.4-fold, and 3.6-fold docking acceleration against the original AutoDock Vina, QuickVina 2, and QuickVina-W while ensuring their comparable docking accuracy. In addition, we develop a friendly and installation-free graphical user interface tool for their convenient usage. The codes and tools of Vina-GPU 2.0 are freely available at https://github.com/DeltaGroupNJUPT/Vina-GPU-2.0, coupled with explicit instructions and examples.
Simulated Annealing (SA) algorithm is not effective with large optimization problems for its slow convergence. Hence, several parallel Simulated Annealing (pSA) methods have been proposed, where the ...increase of searching threads can boost the speed of convergence. Although satisfactory solutions can be obtained by these methods, there is no rigorous mathematical analyses on their effectiveness. Thus, this article introduces a probabilistic model, on which a theorem about the effectiveness of multiple initial states parallel SA (MISPSA) has been proven. The theorem also demonstrates that the increasing parallelism in pSA algorithm with the reducing of search depth in each thread could obtain almost the same probability of finding the global optimal solution. We validated our theorem on AutoDock Vina, a widely used molecular docking tool with high accuracy and docking speed. AutoDock Vina uses a pSA strategy to find optimal molecular conformations. Under the premise that the total searching workload (i.e., thread number * iteration depth of each thread) remains unchanged, the docking accuracy from an aggressively parallelized SA searching method is almost the same or even better than those from the default exhaustiveness (parallelism degree) configuration of AutoDock Vina. Taking complex '1hnn' as an example,with the increase (125x) in the number of initial states (from 8 to 1000) and the decrease in the search depth for each thread (from 15540 to 124, or 1/125 of the original search depth), the mean energy is −7.80 and −7.94, while the mean RMSD is 3.4 and 3.14, respectively. The result also implies that a considerable speedup (in this case 125x in theory) can be obtained by a highly parallelized SA algorithm implementation.
AutoDock Vina (Vina) stands out among numerous molecular docking tools due to its precision and comparatively high speed, playing a key role in the drug discovery process. Hardware acceleration of ...Vina on FPGA platforms offers a high energy-efficiency approach to speed up the docking process. However, previous FPGA-based Vina accelerators exhibit several shortcomings: 1) Simple uniform quantization results in inevitable accuracy drop; 2) Due to Vina's complex computing process, the evaluation and optimization phase for hardware design becomes extended; 3) The iterative computations in Vina constrain the potential for further parallelization. 4) The system's scalability is limited by its unwieldy architecture. To address the above challenges, we propose Vina-FPGA-cluster, a multi-FPGA-based molecular docking tool enabling high-accuracy and multi-level parallel Vina acceleration. Standing upon the shoulders of Vina-FPGA, we first adapt hybrid fixed-point quantization to minimize accuracy loss. We then propose a SystemC-based model, accelerating the hardware accelerator architecture design evaluation. Next, we propose a novel bidirectional AG module for data-level parallelism. Finally, we optimize the system architecture for scalable deployment on multiple Xilinx ZCU104 boards, achieving task-level parallelism. Vina-FPGA-cluster is tested on three representative molecular docking datasets. The experiment results indicate that in the context of RMSD (for successful docking outcomes with metrics below 2Å), Vina-FPGA-cluster shows a mere 0.2% lose. Relative to CPU and Vina-FPGA, Vina-FPGA-cluster achieves 27.33× and 7.26× speedup, respectively. Notably, Vina-FPGA-cluster is able to deliver the 1.38× speedup as GPU implementation (Vina-GPU), with just the 28.99% power consumption.
Calcium titanate (CaTiO3) was conveniently synthesized by thermal decomposition of a single-source precursor Ca(H2O)32Ti2(O2)2O(NC6H6O6)2A.2H2O at low temperature. This single-source precursor was ...characterized by elemental analysis, IR spectrum, thermal gravimetric analysis and X-ray single crystal diffraction. The calcined products at different temperature were further characterized by powder X-ray diffractions and IR spectra. The morphology, microstructure, and crystallinity of the resulting CaTiO3 materials have been characterized by SEM and TEM. The BET measurement revealed that the CaTiO3 powders had a surface area of 14.0aam2/g. In addition, the microwave dielectric properties of the resulting CaTiO3 material have been measured. Display Omitted
Calcium titanate (CaTiO
3) was conveniently synthesized by thermal decomposition of a single-source precursor Ca(H
2O)
3
2Ti
2(O
2)
2O(NC
6H
6O
6)
2·2H
2O at low temperature. This single-source ...precursor was characterized by elemental analysis, IR spectrum, thermal gravimetric analysis and X-ray single crystal diffraction. The calcined products at different temperature were further characterized by powder X-ray diffractions and IR spectra. The morphology, microstructure, and crystallinity of the resulting CaTiO
3 materials have been characterized by SEM and TEM. The BET measurement revealed that the CaTiO
3 powders had a surface area of 14.0 m
2/g. In addition, the microwave dielectric properties of the resulting CaTiO
3 material have been measured.
Display omitted
