17 results about "Hardware virtualization" patented technology

The invention discloses a local key secure storage method and device based on a virtualized cryptographic module, and aims to solve the problem that the security, the cost and the flexibility of the existing scheme are difficult to consider at the same time. According to the method, a high-isolation virtualized cryptographic module (VCM) is created through a CPU hardware virtualization technology, a safe execution environment is constructed, and safe generation, packaging storage and unpackaging operation of a master key and a working key are achieved; the device comprises a hardware layer, a virtualization layer, a VCM and a communication interface, and all the layers are coordinated and are subjected to authority isolation. According to the scheme, the system is supported to start automatic loading or on-demand dynamic loading, and various attacks are resisted in combination with TPM (Trusted Platform Module) enhanced packaging and a strong encryption mechanism. Through verification of a 110kV intelligent substation scene, special hardware does not need to be newly added, the cost is only 0.1% of that of a traditional HSM scheme, the operation response delay meets the real-time requirement, and the method is suitable for key security storage scenes of various types of equipment.

The application discloses a RISCV application program dynamic analysis method and device based on hardware virtualization, which comprises: an operating system kernel running on a reverse RISCV, obtaining process kernel data structure; simulating a RISCV CPU based on a hardware simulator, and constructing a basic process list of the operating system; using an sptbr register and the process kernel data structure to obtain characteristic information of a new process; screening the characteristic information according to the basic process list to obtain a target process; performing API detection and instruction analysis based on process information and dynamic running process information of the target process to obtain a dynamic analysis result. The application can completely and transparently monitor the whole process of program running on a RISCV CPU, and provides configurable efficient process information acquisition, API calling information acquisition and instruction execution information acquisition; the monitoring process does not depend on a system interface, transparent process monitoring can be realized, and the running process of the monitored target is not affected.

The invention relates to the technical field of power distribution Internet of Things, in particular to a power distribution Internet of Things area intelligent fusion terminal system which comprises a single physical processor, a first virtual machine, a second virtual machine, a virtual machine monitor and a single physical processor supporting hardware virtualization extension and an input and output memory management unit. The first virtual machine is specially used for power distribution monitoring services, running a real-time operating system, and processing fault recording and remote control tripping tasks; the second virtual machine is specially used for power utilization acquisition business, runs a non-real-time operating system and processes data reading and edge computing tasks; the virtual machine monitor runs on a single physical processor, and the virtual machine monitor realizes isolation of memory and equipment hardware between the first virtual machine and the second virtual machine through the input and output memory management unit. Redundancy of a control core is achieved so as to solve the problems of system reliability, control strategy and safety of an existing fusion terminal.

The embodiment of the invention discloses an interface interaction control method, a computer system, equipment and a computer storage medium. According to an interface type of a target virtual interface indicated by the creation request, creating a target virtual computing power device corresponding to the interface type in a target virtual environment, responding to a deep learning request of the target virtual environment through the target virtual computing power device, and forwarding the request to a host machine, and scheduling a physical computing power device corresponding to the interface type to respond to the request, and returning a processing result of the request to the target virtual environment through a target virtual computing power device. According to the method, virtualization is carried out from a software interaction level instead of virtualization of computing power hardware, the scheme is completely realized based on software, and a physical GPU is not required to have any special virtualization hardware function, so that almost all mainstream and even old models of GPUs on the market and accelerators such as NPUs with different architectures can be managed. And the user does not need to pay for expensive virtualization dedicated hardware and software license, so that the virtualization deployment cost is reduced.

Various examples disclose systems and methods related to hardware virtualization for error management. These systems and methods define a task flow for executing tasks on a first partition and a second partition. A processor can contain one or more circuits.The one or more circuits can determine that a first task of a multitude of tasks meets a criterion for execution in a redundant mode, determine a task flow for the execution of the multitude of tasks by assigning a switch before the execution of the first task, wherein the switch causes the one or more circuits to be partitioned into a first partition and a second partition, and the multitude of tasks is executed according to the task flow by executing a first instance of the first task on the first partition and a second instance of the first task on the second partition.

The invention provides a multi-dimensional self-adaptive large model inference engine method and system, and relates to the technical field of artificial intelligence, and the method comprises the steps: collecting hardware identification information of calculation hardware, and calling a hardware fingerprint database for matching to generate a hardware type result and a hardware characteristic parameter; constructing a hardware abstraction layer, loading a hardware abstraction driving plug-in according to a hardware type result, and virtualizing computing hardware into a unified logic computing power unit through a hardware abstraction interface; when a large model reasoning task is triggered, dynamically routing to a back-end executor according to a hardware type result by querying a back-end registry; on the basis of hardware characteristic parameters and a hardware abstract interface, a hardware compiling tool chain is called through a rear-end executor, graph optimization and operator fusion are executed on a large model calculation graph, and therefore self-adaptive deployment and efficient reasoning of a large model on heterogeneous hardware can be achieved; the problems that in the prior art, heterogeneous hardware is insufficient in compatibility, configuration is tedious and rigid, and compilation optimization barriers and performance losses are caused during model cross-platform migration are solved.

The invention relates to the technical field of cloud services, in particular to a computing power scheduling service system, which comprises a hardware virtualization module, a computing power scheduling module and a computing power scheduling module, the scheduling module is used for collecting user parameters for the newly added tenant container, establishing a scheduling model corresponding to the standard calculation unit and then distributing the standard calculation unit; and the charging module is used for charging according to the scheduled standard calculation unit and the user parameters. In order to solve the problem that in the prior art, a computing center is poor in effect on scheduling and charging of heterogeneous resources, in the scheme, unified virtualization processing is carried out on heterogeneous hardware resources, a standard computing unit is formed, scheduling and charging are carried out on the basis, and therefore the good adaptation effect on a heterogeneous system is achieved.

The invention provides a large-scale parallel sampling environment construction method and device for reinforcement learning of an intelligent computing cloud platform through computing power, and the method comprises the steps: obtaining a plurality of physical disks of a plurality of computing power nodes of the intelligent computing cloud platform, and constructing the plurality of physical disks into a bottom storage pool through an RAID technology, storing the basic mirror image of the operating system in a qcow2 format, and further generating a plurality of virtual machine instances and running the virtual machine instances; packaging the QEMU process and the running environment of the QEMU process into a container, and performing distributed scheduling on the container according to the disk topological relation among the plurality of bottom storage pools on the plurality of computing power nodes and the real-time I / O load condition. Therefore, the construction of a large-scale parallel sampling environment of reinforcement learning can be realized by utilizing the computing power of an intelligent computing cloud platform and integrating storage optimization, hardware virtualization and container arrangement technologies.

The application relates to a machine learning training resource allocation method based on multiple graphics cards and hardware virtualization, and relates to the technical field of resource allocation.The application is used for solving the problem that the existing training resource allocation method cannot consider both training hardware cost and universality.The application comprises the following steps: obtaining a virtualizable graphics card resource list and a non-virtualizable graphics card resource list; establishing a resource allocation operator AllocTaskCanVirt of a virtualizable computing task, and obtaining the number of allocated virtualizable resources; establishing a resource allocation operator AllocTaskNoVirt of a non-virtualizable computing task, and obtaining the number of allocated graphics cards; inputting training task resource requirements, calling the AllocTaskCanVirt and the AllocTaskNoVirt, and obtaining the final resource consumption number and the allocation result.The application is used for allocating computer graphics card resources.

The invention provides a resource providing method and device which can be applied to the technical field of cloud computing. The resource providing method comprises the steps that at least one trusted node is generated on a cloud computing platform according to a hardware layer and a virtualization layer, the hardware layer comprises multiple pieces of trusted hardware, and the virtualization layer comprises a virtual machine monitor for managing the trusted hardware; in response to a received resource acquisition request sent by a user to the cloud computing platform, determining at least one to-be-allocated trusted node according to resource demand information in the resource acquisition request; and distributing at least one trusted node to be distributed to the user.

This invention discloses a memory tiered management and dynamic migration method and system based on hardware virtualization, relating to the fields of virtualization and hardware management technology. The specific steps of the method are: multi-source data collaborative collection, multi-source data fusion prediction, virtual machine memory tiered configuration, active migration trigger judgment, and tiered migration execution. This invention collects hardware health data and memory load data, uses a multi-source data fusion weight coefficient formula to weight and integrate differentiated data, and uses a memory pressure peak prediction formula and a hardware failure risk level quantification formula to predict memory bottlenecks and hardware failure risks in advance, thereby dynamically adjusting the virtual machine memory tiered configuration. For example, core business data is preferentially stored in the local high-speed cache and configured with the highest migration priority, while cold data layers are compressed to reduce resource consumption. This tiered management strategy improves memory access efficiency, and at the same time, the active migration trigger mechanism avoids service interruptions.

The invention relates to hardware virtualization for fault management. In various examples, systems and methods related to hardware virtualization for fault management are disclosed. Systems and methods of determining a task flow to perform tasks on a first partition and a second partition are disclosed. The processor may include one or more circuits. The one or more circuits may determine that a first task of the plurality of tasks satisfies criteria for execution in a redundant mode, determine a task flow for execution of the plurality of tasks, where a translator is assigned prior to execution of the first task, the translator causing the one or more circuits to be divided into a first partition and a second partition, and execute the plurality of tasks according to the task stream by executing a first instance of the first task on the first partition and executing a second instance of the first task on the second partition.

In various examples, systems and methods are disclosed relating to hardware virtualization for fault management. Systems and methods are disclosed that determine a task flow to execute the tasks on a first partition and a second partition. A processor may include one or more circuits. The one or more circuits may determine that a first task of a plurality of tasks satisfies a criterion for execution in a redundant mode, determine a task flow, for execution of the plurality of tasks, in which a switch is assigned prior to execution of the first task, the switch to cause the one or more circuits to be partitioned into a first partition and a second partition and execute the plurality of tasks according to the task flow by executing a first instance of the first task on the first partition and a second instance of the first task on the second partition.

The embodiment of the invention provides a communication method applied to a hardware virtualization system. According to the system, two partitions for operating a first operating system and a second operating system respectively are isolated through a virtual machine monitoring program, and a first equipment file for a user program of the first operating system to access is created based on a shared memory. The method comprises the following steps: mapping the shared memory to an address space of a user program through the equipment file, so that the user program can directly read data written into the shared memory by the second operating system, or directly write the data and notify the second operating system to read the data. According to the scheme, intervention of a kernel of the first operating system is avoided, and data copying and context switching between a kernel mode and a user mode are eliminated, so that communication delay is remarkably reduced, throughput is improved, and efficient communication among different operating systems is realized.

The invention particularly relates to a multi-source data synchronization control method based on hardware virtualization. The method comprises the following steps: acquiring first time information by a first system; determining second time information corresponding to the first time information according to the proportional relation between the real physical time and the virtual time; sending the second time information to at least one second system based on a preset time interval, so that the second system executes a test task according to the second time information; wherein the second system is used for running in the first system and executing a test task. According to the method, the operation condition of the tested software is obtained through system environment binding monitoring based on the digital airborne embedded software, the operation process of the test environment is controlled by using a virtual crystal oscillator time service mechanism, and the working efficiency and accuracy of the dynamic test of the airborne embedded software are improved.

The invention discloses a strong isolation MCS system based on a single SOC chip and an implementation method, and relates to the technical field of computers, the strong isolation MCS system comprises a sharing subsystem and a special subsystem, the sharing subsystem and the special subsystem are isolated at the RTL level, and the resources of the special subsystem are isolated at three levels based on the RTL-MPU-ACL; and in the sharing subsystem, hardware-level isolation is realized through MPAM, an equipment hardware virtualization technology and a hardware multi-instance technology, system-level isolation is realized through a partition mechanism, and application-level isolation is realized through a container technology. According to the invention, sharing and isolation can be ensured, the flexibility characteristic is realized, and the performance loss can be obviously reduced.