A Survey of Graph Pre-processing Methods: From Algorithmic to Hardware Perspectives

Graph-related applications have experienced significant growth in academia and industry, driven by the powerful representation capabilities of graph. However, efficiently executing these applications faces various challenges, such as load imbalance, random memory access, etc. To address these challenges, researchers have proposed various acceleration systems, including software frameworks and hardware accelerators, all of which incorporate graph pre-processing (GPP). GPP serves as a preparatory step before the formal execution of applications, involving techniques such as sampling, reorder, etc. However, GPP execution often remains overlooked, as the primary focus is directed towards enhancing graph applications themselves. This oversight is concerning, especially considering the explosive growth of real-world graph data, where GPP becomes essential and even dominates system running overhead. Furthermore, GPP methods exhibit significant variations across devices and applications due to high customization. Unfortunately, no comprehensive work systematically summarizes GPP. To address this gap and foster a better understanding of GPP, we present a comprehensive survey dedicated to this area. We propose a double-level taxonomy of GPP, considering both algorithmic and hardware perspectives. Through listing relavent works, we illustrate our taxonomy and conduct a thorough analysis and summary of diverse GPP techniques. Lastly, we discuss challenges in GPP and potential future directions

Computer-Aided Drug Design of Capuramycin Analogues as Anti-Tuberculosis Antibiotics by 3D-QSAR and Molecular Docking

Capuramycin and a few semisynthetic derivatives have shown potential as anti-tuberculosis antibiotics.To understand their mechanism of action and structureactivity relationships a 3D-QSAR and molecular docking studies were performed. A set of 52 capuramycin derivatives for the training set and 13 for the validation set was used. A highly predictive MFA model was obtained with crossvalidated q2 of 0.398, and non-cross validated partial least-squares (PLS) analysis showed a conventional r2 of 0.976 and r2pred of 0.839. The model has an excellent predictive ability. Combining the 3D-QSAR and molecular docking studies, a number of new capuramycin analogs with predicted improved activities were designed. Biological activity tests of one analog showed useful antibiotic activity against Mycobacterium smegmatis MC2 155 and Mycobacterium tuberculosis H37Rv. Computer-aided molecular docking and 3D-QSAR can improve the design of new capuramycin antimycobacterial antibiotics

Sputtering of cobalt film with perpendicular magnetic anisotropy on disorder-free graphene

Growth of thin cobalt film with perpendicular magnetic anisotropy has been investigated on pristine graphene for spin logic and memory applications. By reduction of the kinetic energy of the sputtered atoms using indirect sputtered deposition, deposition induced defects in the graphene layer have been controlled. Cobalt film on graphene with perpendicular magnetic anisotropy has been developed. Raman spectroscopy of the graphene surface shows very little disorder induced in the graphene by the sputtering process. In addition, upon increasing the cobalt film thickness, the disorder density increases on the graphene and saturates for thicknesses of Co layers above 1 nm. The AFM image indicates a surface roughness of about 0.86 nm. In addition, the deposited film forms a granular structure with a grain size of about 40 nm

Multi-objective generative design of three-dimensional material structures

Generative design for materials has recently gained significant attention due to the rapid evolution of generative deep learning models. There have been a few successful generative design demonstrations of molecular-level structures with the help of graph neural networks. However, in the realm of macroscale material structures, most of the works are targeting two-dimensional, ungoverned structure generations. Hindered by the complexity of 3D structures, it is hard to extract customized structures with multiple desired properties from a large, unexplored design space. Here we report a novel framework, a multi-objective driven Wasserstein generative adversarial network (WGAN), to implement inverse designs of 3D structures according to given geometrical, structural, and mechanical requirements. Our framework consists of a WGAN-based network that generates 3D structures possessing geometrical and structural features learned from the target dataset. Besides, multiple objectives are introduced to our framework for the control of mechanical property and isotropy of the structures. An accurate surrogate model is incorporated into the framework to perform efficient prediction on the properties of generated structures in training iterations. With multiple objectives combined by their weight and the 3D WGAN acting as a soft constraint to regulate features that are hard to define by the traditional method, our framework has proven to be capable of tuning the properties of the generated structures in multiple aspects while keeping the selected structural features. The feasibility of a small dataset and the scalability of the objectives of other properties make our work an effective approach to provide fast and automated structure designs for various functional materials

Design and performance research of single rubber cylinder for high pressure gas injection packer

In order to solve the problem of "gas explosion" at the end of common rubber cylinder in the process of high temperature, high pressure and gas drive operation, the rubber cylinder with new structure suitable for 51/2 in casing pipe is developed. The "M" type single rubber cylinder structure is adopted in the new structure rubber cylinder, and the "gas explosion" problem of the end gas in the low-pressure side is solved by setting the double-layer staggered slotted steel cover to prevent outburst. The finite element method is used to simulate the setting of the rubber cylinder, and the structural parameters of the new rubber cylinder are obtained by single factor analysis and orthogonal optimization, simulation test and seal test were carried out to verify the sealing performance of the rubber cylinder. According to the actual working condition, the simulation test results and seal test results show that the sealing capacity of the packer reaches 50 MPa under the temperature resistance of 120℃, and the end steel cover is fully opened to wrap the rubber cylinder, which meets the operation requirements of high temperature and high pressure gas injection packer