32 results about "High performance parallel computing" patented technology

The invention pertains to a system and method for dispatching and executing the compute-intensive parts of the workflow for database queries on an attached high-performance, parallel computing platform. The performance overhead for moving the required data and results between the database platform and the high-performance computing platform where the workload is executed is amortized in several ways, for example,

• • by exploiting the fine-grained parallelism and superior hardware performance on the parallel computing platform for speeding up compute-intensive calculations,
  • by using in-memory data structures on the parallel computing platform to cache data sets between a sequence of time-lagged queries on the same data, so that these queries can be processed without further data transfer overheads,
  • by replicating data within the parallel computing platform so that multiple independent queries on the same target data set can be simultaneously processed using independent parallel partitions of the high-performance computing platform.

A specific embodiment of this invention was used for deploying a bio-informatics application involving gene and protein sequence matching using the Smith-Waterman algorithm on a database system connected via an Ethernet local area network to a parallel supercomputer.

A system, method and computer program product for supporting system initiated checkpoints in high performance parallel computing systems and storing of checkpoint data to a non-volatile memory storage device. The system and method generates selective control signals to perform checkpointing of system related data in presence of messaging activity associated with a user application running at the node. The checkpointing is initiated by the system such that checkpoint data of a plurality of network nodes may be obtained even in the presence of user applications running on highly parallel computers that include ongoing user messaging activity. In one embodiment, the non-volatile memory is a pluggable flash memory card.

The invention provides a spatial data processing method and system. The spatial data processing method includes acquiring a geographic unit data set on the basis of dividing spatial data by geographic units; storing the geographic unit data set to an open source distribution type file system in batches; performing distribution type computing on the geographic unit data set stored in the open source distribution type file system by the Map / Reduce algorithm. By the aid of the spatial data processing method, a task can be divided into a plurality of tasks to be processed simultaneously, high-performance parallel computing is achieved; since the open source distribution type file system and the Map / Reduce algorithm are adopted, high-performance computing of geographic information can be supported by using an ordinary computer and computing model, and the method has the advantages of high adaptability and low cost.

The invention relates to a hybrid model test platform for vibration control of a deep sea platform. The hybrid model test platform for vibration control of the deep sea platform comprises a deep sea platform motion simulation system, a test data acquisition and analysis system, a high-performance parallel computation and control system and a structure vibration control device test model, wherein the deep sea platform motion simulation system comprises a deep sea platform motion simulator; the deep sea platform motion simulator has a fixed lower platform and upper platform; the upper platform is a six-degree-of-freedom motion platform, realizes six-degree-of-freedom motion of the motion platform by driving a servo motor, and is used for simulating the motion deep sea platform; the test dataacquisition and analysis system comprises a three-axis force transducer, a high-speed camera and an image processing computer; the high-performance parallel computation and control system comprises amain control computer and a high-performance parallel workstation; the structure vibration control device test model is put on the upper platform of the deep sea platform motion simulator; and the deep sea platform motion simulator simulates six-degree-of-freedom motion of the deep sea platform under the control of the main control computer.

The invention discloses an MPI (Moldflow Plastics Insight) information scheduling method based on reinforcement learning under a multi-network environment, aiming at overcoming the defect of low practical application performance of a high-performance parallel computer, caused by the traditional circulating scheduling method. The method comprises the steps of: initiating parameters in a process of starting an MPI system, creating Cm<2> Q tables according to a multiple Q table combined method for a computing environment matched with m networks; continuously receiving an MPI information sending request sent by application in a process of starting the MPI system, determining a current information segment, then obtaining a current environment state, scheduling the current information segment to an optimal network according to the state information of historical empirical values stored in the Q tables; and finally, computing an instant reward value obtained by the scheduling and updating Q values in the Q tables. By adopting the invention, the problems that communication loads are distributed unequally, can not adapt to the network state dynamic change and have poor adaptability on the computing environment can be solved, and the practical application performance of the high-performance parallel computer is improved.

The present invention discloses a parallel quantification computation method for global cross correlation of non-linear data. A parallel NLI algorithm is developed by using a CPU multi-thread technology and a CUDA based GPGPU multi-thread method in high-performance parallel computation, and an idea of parallel computation is introduced into the algorithm, so as to improve performance of the algorithm and assist analysis of a multi-channel signal; and data processing is extended from dual channels to multiple channels, and by combining a process where an S estimator performs data analysis from locally to globally to locally again, synchronization strength of a signal within a certain regional range is quantified, and more, more accurate and more useful information is mined out of original data to analyze a synchronization problem of the multi-channel signal, so that execution efficiency of the algorithm is greatly improved while the effect of the algorithm is reserved. As an experiment proves, the method has higher efficiency and usability in actual cross correlation analysis of multi-channel non-linear data.

The invention provides a computing analysis system which is based on multi-core CPU and GPGPU hardware and combines software and hardware, and particularly relates to a high-throughput sequencing data quality control system based on multi-core CPU and GPGPU hardware. According to the characteristic that massive data can be processed in parallel in the high-throughput sequencing data processing process, the system is provided to solve the problem that a traditional computer cannot meet the analysis requirement for carrying out quality control over massive high-throughput sequencing data. A main module of the high-throughput sequencing data quality control system based on the multi-core CPU and GPGPU hardware comprises a multi-core CPU and GPGPU computer and a unified software platform. The system is characterized in that a high-performance parallel computing and storage hardware system and the high-performance, unified and configurable software platform are included. According to high-throughput sequencing data quality control processing based on the multi-core CPU and GPGPU hardware, analysis efficiency of high-throughput sequencing data quality control can be obviously improved.

The invention discloses a Grover quantum simulation algorithm optimization method based on cloud computing, and mainly solves the problems of few quantum bits and low simulation efficiency of quantumalgorithm simulation at home and abroad. According to the invention, optimization is carried out for Grover quantum search single iteration unitary operation, an optimization algorithm which greatly saves storage space and remarkably improves unitary operation efficiency is provided, and distributed processing is conducted on large-matrix unitary operation on a cloud computing cluster by utilizingthe advantages of a MapReduce parallel computing model based on Hadoop. The high-performance parallel computing capability provided by the cloud computing platform is fully utilized, the advantages of the cluster architecture are utilized to construct the multi-bit quantum parallel computing model, and the simulation algorithm efficiency is successfully improved.

The invention provides a high-performance parallel computing method based on external PCI-E connection. The method includes the steps of (a) connecting all pieces of computer equipment through a PCI-E bus, (b) running a parallel computing program, (c) constructing a virtual memory addressing table, (d) sending virtual memory information, (e) receiving the virtual memory information, (f) judging correctness of the received information, (g) judging whether a virtual memory address is constructed, (h) allocating computing tasks, (i) executing the computing tasks, and (j) obtaining results and providing the results for a user. The data transmission speed between processors is increased in the parallel computing process through the parallel computing method; the parallel computing method is improved, so that the copy data size of a system CPU is reduced, efficiency of parallel computing operation is greatly improved, multiple parallel computing resources are effectively connected for communication, and data are transmitted at a high speed.

The invention belongs to the technical field of chip layout design, in particular to a layout structure and a preparation method for saving chip area. The invention mainly relates to a chip layout structure in which the design rule is reasonably utilized in a digital money mining machine chip or a high-performance parallel computing chip, and the module shape is changed to reduce the waste of thechip corner area to the minimum in the AIO flow. By cutting off the right angle corner of the core module, the core module cutting off the right angle corner is arranged at the chip corner, and the cutting angle is placed relative to the chip sealring corner; And the area of the core module with the right angle cut is kept constant by increasing the width or length of the core module with the right angle cut. So as to realize the reduction of chip area.

The invention provides a method and a system of SQL-like queries based on an HBase coprocessor. The method and the system can standardize and unify query conditions and returned results, and can execute high-performance parallel computing of real-time data while intrusion into an upper-layer service is avoided. The method includes: preconfiguring the metadata of tables, which are stored by HBase, on an HBase client; establishing an upper-layer service access connection, parsing SQL query statements imported from the upper-layer service, and generating query requests; distributing the query requests to RegionServers by the HBase client; utilizing the HBase coprocessor by the RegionServers to carry out the parallel queries and processing on the data according to the query requests; and merging data, which is returned by the RegionServers, by the HBase client, and encapsulating a result set.

The invention provides a Cache simulator based on a GPU and a time parallel speedup simulating method thereof. The Cache simulator comprises an initializing module, a Trace segmentation module, a GPU parallel simulating module, a GPU parallel modifying module and a statistical calculation module. The cache simulator is based on the GPU with strong high-performance parallel computing capacity, has multi granularity and multi configuration abilities and parallel simulation characteristic. The invention adopts a time parallel speedup method to segment longer Trace arrays, realizes the parallel simulation of multi Trace segments on the GPU, and utilizes the GPU parallel modifying module to modify the error caused by the modifying and simulating processes in the simulating process. The invention has the advantages that the Cache simulating efficiency is improved, computing resources are better utilized and simultaneously higher cost-performance ratio is achieved.

The invention discloses a method for submitting an OpenCL kernel. The method comprises the following steps of 1, transmitting kernel information to the OpenCL kernel; 2, converting the dimension of the work item from one dimension to two dimensions; 3, checking whether the OpenCL kernel uses a local memory or not, and applying for space storage if the OpenCL kernel uses the local memory; 4, checking the size of a local working group; and 5, buffering and submitting the command containing the OpenCL kernel information to hardware equipment. The invention further discloses a device for submitting the OpenCL kernel. The device comprises a kernel information creating and submitting module; a work item dimension conversion module; a local memory variable module; a local work group module; and an OpenCL working thread module. On the premise that the OpenCL standard framework is met, work tasks are reasonably distributed to hardware, the OpenCL kernel is submitted to the hardware to be executed, the parallel operation efficiency is improved, and the method and the device can be widely applied to the field of high-performance parallel calculation.

The invention discloses a vehicle trajectory clustering method based on a parallel ST-AGNES algorithm, and the method is characterized in that multiple processing units are utilized to work together,and a certain task is executed at the same time to achieve higher performance. Parallel computing is an effective means for improving the computing speed and the processing capacity of a computer system. Therefore, the invention provides the vehicle trajectory clustering method based on the parallel ST-AGNES algorithm from a brand-new perspective, and the vehicle trajectory time and space similarity measurement method based on dynamic time warping better solves the problems of different vehicle trajectory sampling rates and inconsistent time scales. The method comprises the steps: constructinga time and space similarity matrix of vehicle tracks; studying a splitting scheme of irregular trajectory data and a communication mechanism of parallel computing, wherein one of the object-orientedtrajectory data splitting schemes is an object-oriented trajectory data splitting scheme; carrying out clustering connection based on the minimum distance, and designing a parallel STAGNES algorithm oriented to vehicle trajectory data.

The invention provides a data processing method. The HPC storage device and the distributed storage device are separately used; when high-performance parallel computing is required, the HPC storage device is used for storing to-be-processed data pre-copied from the distributed storage device and is responsible for providing parallel computing real-time data for computing nodes of the HPC cluster,computing result data of the computing nodes are transferred to the distributed storage device, and the distributed storage device is used for storing data uploaded by a terminal, the computing resultdata and subsequent data needing to be processed by the terminal. Thus, the page view of the HPC storage device and the network bandwidth burden during parallel data calculation can be reduced, the capacity requirement of the HPC storage device is reduced, and the total ownership cost of the HPC storage device is reduced. In addition, when high-performance parallel computing is needed, a terminaldoes not need to independently upload data or download computing result data, data operation time is saved, and sharing of the computing result data is facilitated.

The invention provides an OpenFOAM computing task management method based on a Web technology. The method comprises the steps of providing a unified, convenient and visual OpenFOAM cloud computing task management and post-processing visual operation interface and an API communication interface based on a Web technology; and providing a CFD calculation task creation and management mechanism for a multi-user use scene. A user does not need to master remote login and operation skills of the server and does not need to know OpenFOAM calculation details, so that the operation difficulty of an OpenFOAM application in a building CFD aided design process is remarkably reduced. According to the method, unattended operation is achieved through a CFD multi-task management program, and resource waste caused by manual monitoring and untimely error processing is avoided; by automatically allocating the computing resources, efficiency reduction caused by resource competition during multi-user use is avoided; according to the invention, the multi-core high-performance parallel computing capability of the computing server is fully exerted, the server can continuously and efficiently carry out CFD analysis work of constructional engineering, and a new technical means is provided for CFD batch automatic computing.