Cloud simulation service method

Abstract

The invention discloses a cloud simulation service method comprising the steps of: virtualizing hardware resources in a cloud simulation architecture; virtualizing software resources in the cloud simulation architecture; establishing a unified management platform in the cloud simulation architecture to manage the virtualized hardware resources and the virtualized software resources; and constructing a the professional model and a solver in the cloud simulation architecture. The method has the following advantages of using model sharing service, resource flexible scheduling and solver parallel computing as a core, scheduling tasks and distributing computing resources on demand, providing the professional model and the solver for engineering staff in the form of services by using service middleware, configuring on demand, providing a flexible and reliable computing platform for enterprises; and achieving high data security and high data reliability.

Description

technical field [0001] The invention relates to the technical field of cloud simulation, in particular to a cloud simulation service method. Background technique [0002] Cloud simulation is based on various original simulation technologies, based on the concept of cloud computing, and integrates technologies such as cloud computing and big data to realize various resources (model resources, computing resources, storage resources, network resources, and data resources) in the simulation process. , information resources, knowledge resources, software tool resources, hardware-in-the-loop simulation equipment, etc.) on-demand sharing and reuse, dynamic optimization scheduling, realize multi-user on-demand collaborative simulation applications, and support physical product development full life cycle simulation verification activities. [0003] In the traditional cloud simulation architecture mode, professional models and solvers are mostly deployed on the terminal computers of ...

AI Technical Summary

Problems solved by technology

[0004] 1. Inflexible resource allocation: each engineer who uses professional models and solvers needs to be equipped with high-end hardware equipment, but the use time and scale of professional models and solvers cannot be guaranteed, which may cause hardware resources to not be fully utilized ;

[0005] 2. The version management of professional models and solvers is chaotic: For different professional models and solvers, the versions used by each engineer may be inconsistent, making it difficult to manage professional models and solver versions

[0006] 3. Data security and reliability cannot be guaranteed: engineers use professional models and solvers to work on their own terminals, the calculation process cannot be traced back, and its reliability depends entirely on the software usage habits of engineers

The reliability of the data cannot be guaranteed, and at the same time, the data is scattered on the terminals of various engineers, and the security of the data cannot be guaranteed;

[0007] 4. Low efficiency of enterprise software management: Under the traditional cloud simulation architecture mode, more hardware resources and software resources are required, which greatly increases the workload of enterprise software managers and reduces the management efficiency of the entire enterprise software resources

Images