45 results about "High-throughput computing" patented technology

Embodiments of the present invention manage workloads in a high-throughput computing environment for a hybrid processing system. A set of high-throughput computing service level agreements (SLAs) is retrieved. The set of SLAs is associated with a hybrid processing system including a server system and a set of accelerator systems, where each system has a different architecture. A first set of data-parallel workload tasks scheduled on the server system and a second set of data-parallel workload tasks scheduled with the set of accelerator systems are identified. At least a portion of one of the first set of data-parallel workload tasks and the second set of data-parallel workload tasks is dynamically rescheduled on a second one of the server system and the set of accelerator systems. The dynamically rescheduling substantially satisfies the set of high-throughput computing SLAs.

The present invention provides users with cloud-based high throughput computing system for integrative analyses of next generation sequencing genomic data, such that human cancer biomarkers and drug targets can be accurately and quickly identified. Advantageously, the present invention harness a comprehensive systematic analysis pipelines for all types of next generation sequencing genomic data, advanced genomic variants calling algorithms and modeling, variant data correlation and integration, and identification of cancer specific biomarkers and therapeutic targets. Thus, the present invention will aid users so that less of their time and efforts are required in order to obtain precisely the desired information for which they are analyzing.

The invention relates to the technical field of genetic engineering, in particular to a method for specifically knocking out a human PCSK9 gene by virtue of CRISPR-Cas9 and sgRNA for specifically targeting the PCSK9 gene; through high-throughput cloud computing and designing, a group of sgRNA for specifically knocking out the specifically targeted PCSK9 gene in the human PCSK9 gene by virtue of the CRISPR-Cas9 is synthesized; meanwhile, each sgRNA is linked to a linear pCG-U6-SgRNA plasmid, so that a carrier is obtained, and a pair of forward and reverse sgRNA oligonucleotide carriers, together with the pCG-NLS-FLAG-Cas9 plasmid, are used for successfully transfecting cells, so that the PCSK9 gene is knocked out; the method has the advantage that the large-scale production of the sgRNA can be achieved just by synthesizing a few of polynucleotide segments; and the preparation method is simple and easy to implement, good in sgRNA targeting properties and high in knocking-out efficiency on the CRISPR-Cas9 system.

A computer simulation analysis method suitable for describing the mechanical behavior of multiphase composites based on the real microstructure of materials relates to a multidisciplinary field such as computational material science, simulation and high throughput calculation. Through the first-principles calculation under nano scale, the molecular dynamics simulation under micro scale, and the thermodynamic calculation under mesoscopic scale, various physical parameters needed for the finite element simulation under macro scale can be obtained, including the elastic and plastic physical parameters of each phase in the composite at different temperature and different grain sizes. Focused ion beam experiment and image processing are adopted to obtain real material microstructure. Through the parameter coupling and parameter transfer among the calculated results of various scales, combining the microstructure of the material, stress-strain relationship, stress distribution and its evolution law, plastic deformation and other mechanical behaviors of the multiphase composites under complex stress and different temperature can be simulated.

Disclosed is a method of efficiently allocating resources in a cloud computing system of the High-Throughput Computing (HTC) field. In more detail, a cloud resource allocation model is proposed in which accumulated job histories are analyzed, a correlation between a performance factor and the job properties is extracted, a factor which is greatly influential in a task performance is identified based on the result of the analyzing and the extracting and is applied to subsequent resource allocations, and reanalysis is performed adaptively.

The invention provides a high-throughput calculation method for crop plant height. The method comprises the following steps: acquiring a color image, an infrared image and a depth image of a crop sample group; and carrying out image registration on the color image and the depth image, and constructing a point cloud image with color information; extracting crop canopy three-dimensional point cloudaccording to the point cloud image with the color information; extracting a canopy image corresponding to each crop in the crop sample group according to the crop canopy three-dimensional point cloud,and calculating the plant height of each crop through a high-throughput calculation method. According to the embodiment of the invention, the plant height of each pot of crops in the group crops canbe quickly and accurately calculated; Compared with a traditional plant height measuring method which utilizes a ruler, a handheld laser range finder and other devices to manually measure the verticallength from the highest point of a canopy to the root of a plant, the high-throughput calculation of the plant height of the crop is realized, and the method is quicker, simpler and more convenient.Compared with a network camera remote phenotype measurement method, the accuracy of crop plant height measurement is improved.

The invention provides a catalytic material screening method and a catalytic material screening system combining a high-throughput experiment and high-throughput calculation. The method comprises thesteps: screening a to-be-confirmed catalytic material meeting a target catalytic performance by using a catalyst structure-activity relation model constructed based on the data results of a high-throughput experiment and high-throughput calculation; performing high-throughput preparation and high-throughput performance evaluation on the screening result to obtain the experimental result of the to-be-confirmed catalytic material; and comparing the catalytic performance prediction result of the to-be-confirmed catalytic material with the experimental result of the to-be-confirmed catalytic material, and determining that the to-be-confirmed catalytic material is the catalytic material reaching the target catalytic performance under the condition of a predetermined deviation range. According to the scheme, the theoretical calculation simulation result, the existing experiment result and the new catalyst characterization result can form a mutual verification relationship through the catalyst structure-activity relationship model constructed based on the high-throughput experiment and the high-throughput calculation, so that the screening precision and the screening speed of the catalytic material are improved.

The invention discloses a method for measuring contents of iron ions in different valence states in feed. The method comprises the following steps: masking copper ions by sodium thiosulfate, and reducing ferric ions in the feed to ferrous ions by hydroxylamine hydrochloride; complexing ferrous ions with phenanthroline at pH 6 and room temperature to form a purple complex with good stability; reacting for 30 minutes, and detecting at the position of 562 nm by a microplate reader; and in combination with a drawn standard curve, rapidly calculating the content of iron ions in different valence states in the feed with high throughput. Complex sample pretreatment and expensive instruments are not needed, and the method is quite suitable for being popularized and used in primary laboratories.

The invention belongs to the technical field of material calculation, and provides a high-throughput calculation screening method for a doped energy material, which is realized through four modules. The method specifically comprises the steps of obtaining a crystal structure information file of an intrinsic material through an intrinsic material structure extraction module; processing the crystalstructure information file by a doped structure construction module to obtain a doped structure information file; reading the structure information file through a doped material structure optimizationand property calculation module; generating structure optimization-property calculation work flow in batches and performing high-throughput calculation; and finally storing calculation results of energy, electronic properties and the like in a private database through a material database importing module. The purpose of high-throughput calculation screening can be efficiently achieved; the working efficiency of material screening is improved; and relatively high universality and expandability are achieved.

The invention belongs to the field of material genetic engineering, multi-scale simulation and material big data, and relates to a multi-scale integrated visual high-flux automatic calculation processand data intelligent system, which comprises a material modeling system, a scientific calculation system, a server configuration system, a data storage system, a data analysis system and an artificial intelligence system. According to the method, an automatic construction method of a material complex model, various material calculation simulation methods with different scales, various types of material databases, a material performance analysis technology and a data mining technology based on artificial intelligence are combined, and 1000-magnitude material high-flux calculation simulation can be automatically carried out; material calculation simulation of multiple scales such as an electronic scale, an atomic scale, a molecular scale and a mesoscopic scale can be carried out, and errorspossibly occurring in the calculation process can be automatically corrected; all calculated structural data, intermediate metadata and result data can be stored in various types of material databases, so that a user can conveniently inquire and carry out data mining analysis.

The invention provides a high-throughput calculation method and system based on the container technology, and relates to the field of high-throughput calculation. The workflow jobs are defined througha workflow description file, each workflow job is composed of one or more subtask jobs, and the dependency relationship between the subtask jobs is defined through a directed graph; the sub-task jobsare constructed into job containers in a container mode, the job containers are in butt joint with a resource pool, and the resource pool comprises computing resources and storage resources which aremainly composed of local physical resources, grid resources and virtualization resources; and scheduling, distributing, running, monitoring and managing the sub-tasks according to the dependency relationship. A high-throughput computing platform for docking local physical resources, grid resources and virtualized cloud resources is realized by utilizing a container and related technologies, so that the influence factors of the environment are shielded for computing, the resource requirements under different scenes are met, the research efficiency and flexibility are improved, Meanwhile, the support of the system on a workflow form computing task is considered.

The invention describes an explicit solvent all-atom molecular dynamics methodology (SILCS: Site Identification by Ligand Competitive Saturation) that uses small aliphatic and aromatic molecules plus water molecules to map the affinity pattern of a large molecule for hydrophobic groups, aromatic groups, hydrogen bond donors, and hydrogen bond acceptors. By simultaneously incorporating ligands representative of all these functionalities, the method is an in silico free energy-based competition assay that generates three-dimensional probability maps of fragment binding (FragMaps) indicating favorable fragment:large molecule interactions. The FragMaps may be used to qualitatively inform the design of small-molecule ligands or as scoring grids for high-throughput in silico docking that incorporates both an atomic-level description of solvation and the large molecule's flexibility.

The invention belongs to the technical field of battery material screening, relates to screening high-performance and excellent-structure electrolyte materials for lithium batteries, and aims at solving the defects that existing methods are long in period and difficult to control and the screened materials are bad in practicability. The invention provides a high throughput calculation-based methodfor screening electrolyte materials for lithium batteries. By adoption of a high throughout calculation method, the method starts from existing battery material structure database and stands on basicindexes such as chemical stoichiometric equations, ion conductivity, electronic conductivity, stability, high-oxygenolysis voltage and toxicity, and sets a series of screening conditions, so as to finally obtain electrolyte materials with optimum structures and high performance.

The invention relates to a supercomputer-based high-throughput task processing method, and the method comprises the following steps: obtaining the task parameters of a to-be-executed task, wherein the task parameters comprise task physical information and task execution information, the task physical information comprises a job chain type and an application program type, and the task execution information comprises a job chain number M corresponding to a to-be-executed task, a logical relationship between job chains, a job number N of each job chain, a job structure file, a logical relationship between jobs and execution precision; obtaining a corresponding workflow template from a preset database according to the task parameters of the to-be-executed task to generate M workflows in one-to-one correspondence with the M job chains; distributing the M workflows to the computing nodes corresponding to the super computer according to the current computing resources for parallel execution, and storing a final task execution result in the database. According to the method, the calculation efficiency of the high-throughput calculation task is improved.

The invention discloses a calculation method for ideal strength of a two-dimensional material under an electrochemical polarization condition, and belongs to the technical field of two-dimensional materials. By analyzing a rotation axis of the two-dimensional material, the calculation method rotates a system along the rotation axis, a structure after rotating each angle is stored, the structure isstretched uniaxially and biaxially respectively, and ideal strength under each angle is calculated. An ideal strength database of two-dimensional materials under the electrochemical polarization condition is established by high-flux calculation, and the two-dimensional material with the highest ideal strength under the electrochemical polarization condition is selected. The method comprises constructing a two-dimensional material system under the electrochemical polarization condition, realizes calculation of the ideal strength in any direction, and calculates the ideal strength of the two-dimensional material under the electrochemical polarization condition by using a high-flux technology. The method can more precisely screen the two-dimensional material with excellent mechanical properties, and provides favorable assistance for design of new materials.

The invention discloses a system and method for calculating the surface adsorption diversity of a two-dimensional material under experimental condition. The method comprises analyzing the experimental environment of the two-dimensional material, establishing a relationship between the formation energy of functional groups of the two-dimensional material and the corresponding chemical potential, then enumerating all possible surface configurations, storing each structure with different surface functional group proportions and arrangements, carrying out relaxation on the structures, and calculating corresponding formation energy. Through high-throughput calculation, a formation energy database of the two-dimensional material under the experimental condition is established, and the proportion of the functional group with the lowest formation energy within the same chemical potential range under the experimental condition and the corresponding configuration are screened out. According to the system and the method, a method for unifying formation energy of different functional groups into a calculation formula is realized, and the formation energy of the functional groups on the surface of the two-dimensional material under the experimental condition is calculated by applying a high-throughput technology; the surface configuration of the two-dimensional material with excellent thermodynamic stability can be more accurately screened by the method, and beneficial help is provided for new material design.

This disclosure describes methods and systems for high-throughput computations in a fully-connected deep neural network. Specifically, a hardware-based deep neural network architecture including a set of parallel node processors is used to process node value transition between layers of the deep neural network, which usually involves a large-scale matrix multiplication. The set of parallel node processors are configured to decompose the large-scale matrix multiplication into sub-matrix multiplications with smaller sizes and thus reducing the hardware-complexity and making feasible direct implementation in hardware. With this implementation deep neural network may achieve a very high throughput and can handle a large number of processing layers.

The invention discloses a high-throughput calculation method for ideal strength of a crystal material in a lattice disturbance mode, which comprises the following steps of: analyzing a crystal structure of the material, and performing tensile deformation or shear deformation on the material structure to obtain crystal structure information; applying random atomic disturbance to a measured object, breaking symmetric constraint to capture a structural energy ground state, calculating a stress-strain curve of a crystal structure to which a series of uniform strains are applied after random disturbance, and determining and comparing anisotropic ideal tensile strength or shear strength along a typical crystallography direction or a slip system; and then solving the minimum value of the ideal tensile strength and shear strength; through high-throughput calculation, constructing a material system under the condition of increasing atom random disturbance; and realizing the ideal strength of the crystal in any direction under the condition of atom random disturbance by utilizing a high-throughput technology. The ideal strength calculated by a disturbance method is closer to the strength of an actual material, which is essential for better measuring the mechanical property of the material; and meanwhile, two-dimensional or three-dimensional materials with excellent mechanical properties can be screened, and guiding significance is achieved for design of strong solid materials.

The invention provides an accelerator for accelerating a security hash algorithm. The accelerator comprises a storage module, a PE operation module, a task division module and an algorithm mapping module. Compared with the prior art, the method has the advantages that the calculation time overhead can be reduced, and the calculation performance is improved; secondly, the power consumption caused by calculation can be reduced; and, besides, high-throughput calculation of the safety hash function can be achieved, the hash rate is remarkably increased, and a computer system designed through the method has good expandability and compatibility.

The invention discloses a data collection method and device, electronic equipment and a readable storage medium. The method comprises the following steps: constructing an input file which conforms to a material structure and is suitable for material simulation software according to material attribute parameters of original data in a target database; based on a preset convergence standard and the input file, performing optimization processing on the material structure through high-throughput calculation to obtain a target material structure; and processing the target material structure by using the target calculation method for calculating the to-be-demanded physical quantity to obtain the instance data of the to-be-demanded physical quantity, so that a large amount of instance data meeting the material informatics reality demand can be obtained.

The invention discloses a novel material gene decoding and novel material structure and function predicating method which relates to the cross technology field of novel material technology and computer. The method comprises the following steps of storing and visualizing the gene characteristic parameter of all elements or groups; performing big data mining on a novel material database, and settinga material characteristic function F; according to decoding to the material gene characteristic, defining a relation among the material characteristic function F, a material synthesis structure and an environment parameter; generating a high-flux calculating script, and submitting to a supercomputing platform for calculation. According to the method of the invention, through technologies of determining a structure required for determining the gene characteristic and the heredity expression of the material and the synthesis environment parameter, and mass candidate material structures are generated according to the determined material gene characteristic; after high-flux calculation, through setting a characteristic function F threshold, the property and the synthesis environment parameterare predicated, thereby facilitating novel material gene cracking and performing characteristic and function predication on the novel material according to the novel material gene.

The invention provides an intelligent green manufacturing system. The intelligent green manufacturing system is used for manufacturing a coal-based nano carbon polycrystal formula product containing nano carbon fibers, nano carbon tubes, nano carbon onions, nano graphene and a nano graphite mixture. According to the nanocarbon polymorphic crystal intelligent green manufacturing system, nanocarbonpolymorphic crystal green manufacturing of coal-related natural materials is creatively combined with computer-assisted and internet-assisted automatic manufacturing, collaborative network operation,large-scale database management, high-throughput calculation and material genome engineering; customers and insiders participate in adaptive decisions and logistics optimizations, and become cross-keyproduction operations with distributed hardware and software. Installation of the nanocarbon polymorph intelligent green manufacturing system results in immediate green manufacturing of formulated products derived from nanocarbon polymorph, the requirements of customers for the functions and delivery time of composite additives, lubricating additives, coatings, printing ink and other applicationsare met most effectively and efficiently, and the composite additives can remarkably improve the performance of cement-based, polymer-based and metal-based composite materials. The system can increase the product value and reduce the environmental load.

The invention discloses a workflow modeling method suitable for multi-scale high-throughput material calculation, particularly relates to the technical field of computers, and aims to deal with challenges of automatic construction of a microcosmic to macroscopic multi-scale processing process and efficient execution of a large number of high-concurrency calculation tasks in a material design process. The invention provides a workflow flexible configuration and hierarchical modeling method suitable for multi-scale high-throughput material calculation. Packaging of a high-concurrency computing task and flexible expression of a typical process control structure are achieved through a high-throughput computing component model; and a multi-level resource scheduling model oriented to material high-throughput calculation is established, and unified delivery, monitoring and result access of high-throughput scheduling tasks in a high-performance calculation environment are supported. The method is innovative in automatic control of the service flow facing high-throughput calculation, the multi-scale and high-throughput material calculation service workflow can be constructed through a visual means, and execution of the calculation process and transmission of calculation data are automatically achieved.

The invention discloses a high-throughput calculation method of surface properties based on automatic modeling technology, which belongs to the field of materials. Firstly, the structure file of the crystal Q to be studied is obtained, and the crystal Q is converted into a unit cell by using the structure file, and the symmetry is analyzed. Then convert the initial base vector of crystal Q according to the Miller index specified by the user, and obtain the new base vector matrix corresponding to the new crystal structure G. Determine the atomic coordinates corresponding to the new base vector matrix, and fill the new base vector with the atoms of crystal Q, Construct a surface model of crystal G. Finally, the surface energy and work function of the new surface model of crystal G constructed by DFT calculation. For several other crystals with different materials and different surface structures, high-throughput batch calculations are performed separately to obtain their respective surface energies and work functions to form a database of material surface properties. The invention realizes the parallel calculation of the surface properties of different surface structures and improves the calculation efficiency.