Methods and apparatus for automatic qubit calibration. In one aspect, a method includes obtaining a plurality of qubit parameters and data describing dependencies of the plurality of qubit parameters on one or more other qubit parameters; identifying a qubit parameter; selecting a set of qubit parameters that includes the identified qubit parameter and one or more dependent qubit parameters; processing one or more parameters in the set of qubit parameters in sequence according to the data describing dependencies, comprising, for a parameter in the set of qubit parameters: performing a calibration test on the parameter; and performing a first calibration experiment or a diagnostic calibration algorithm on the parameter when the calibration test fails.

A test apparatus for testing a mobile AP provided with an AP package and a memory package according to the disclosure is configured to include: a lower test socket mounted on a tester and connected to the AP package put on an upper side thereof; an upper test socket mounted with the memory package and connected to the AP package put on a lower side thereof; an upper mechanism configured to accommodate the memory package and mounted with the upper test socket; and a heat dissipation device disposed on the upper mechanism. Since heat generated in the AP package can be dissipated through forming of a frame of the upper test socket as an inelastic conductive housing of a metal material having high thermal conductivity, a test can be performed in a step before stacking the AP package and the memory package on each other.

Provided are a method and an apparatus for testing AI chip computing performance, and a non-transitory computer-readable storage medium. The method includes: forming computing performance result data of a to-be-tested AI chip according to a plurality of items of simulation data formed in a development process of the to-be-tested AI chip; acquiring a function instruction set matched with a to-be-tested service function, wherein the function instruction set is composed of a plurality of instructions in a standard instruction set matched with the to-be-tested AI chip; and predicting computing time required by the to-be-tested AI chip to execute the to-be-tested service function according to the function instruction set and the computing performance result data.

In different example embodiments, a system-on-chip is provided. The system-on-chip can have a control circuit with a plurality of control circuit areas, wherein the control circuit is configured to control a device, a security circuit which has a separately secured key memory and a hardware accelerator for cryptographic operations, wherein the security circuit is configured to electively enable either a read-only access or a read and write access to at least one of the control circuit areas, wherein the security circuit is furthermore configured to provide a communication path by means of the key memory and the hardware accelerator for the secured communication with a diagnostic system disposed outside the security circuit, to make the selection between the read access and the read and write access to the at least one selected area of the control circuit depending on a certificate supplied to the security circuit and authenticated by means of information stored in the key memory, and to execute the read access or the read and write access.

A central processing unit includes a core, a state memory, a plurality of bus contacts, a data generation unit, and a bus interface unit. The state memory stores a state, the bus interface unit is coupled to the core and the state memory, and the bus interface unit selectively couples the core to the plurality of bus contacts or the data generation unit according to the state.

Provided is a computer capable of reducing a diagnosis load. For each predetermined diagnosis target node among a plurality of nodes in a neural network, a determination processing unit calculates an expected output value expected as a calculation result of a node calculation process corresponding to the predetermined diagnosis target node, which is obtained when the node calculation process is executed using a predetermined input value. For each diagnosis target node, a generation processing unit generates as a diagnosis program a program for comparing the calculation result of the node calculation process corresponding to the diagnosis target node, which is obtained when the node calculation process is executed by an NN calculation processor using the input value, with the expected output value.

In various examples, permanent faults in hardware component(s) and/or connections to the hardware component(s) of a computing platform may be predicted before they occur using in-system testing. As a result of this prediction, one or more remedial actions may be determined to enhance the safety of the computing platform (e.g., an autonomous vehicle). A degradation rate of a performance characteristic associated with the hardware component may be determined, detected, and/or computed by monitoring values of performance characteristics over time using fault testing.

An apparatus to facilitate watchpoints for debugging in a graphics environment is disclosed. The apparatus includes processing resources to perform graphics operations using a plurality of threads; and load store pipeline hardware circuitry coupled to the processing resources to: configure a watchpoint register with a value of a watchpoint address, the watchpoint address comprising an address of a memory location in the processor; receive a memory access request from a thread of the plurality of threads; determine, using the watchpoint register, whether the memory access request is requesting access to the watchpoint address; and responsive to the memory access request requesting access to the watchpoint address, return an exception payload to the thread, the exception payload comprising watchpoint details corresponding to the watchpoint address and a scoreboard identifier (SBID) associated with the memory access request.

An apparatus to facilitate exception handling for debugging in a graphics environment is disclosed. The apparatus includes load store pipeline hardware circuitry to: in response to a page fault exception being enabled for a memory access request received from a thread of the plurality of threads, allocate a memory dependency token correlated to a scoreboard identifier (SBID) that is included with the memory access request; send, to memory fabric of the graphics processor, the memory access request comprising the memory dependency token; receive, from the memory fabric in response to the memory access request, a memory access response comprising the memory dependency token and indicating occurrence of a page fault error condition and fault details associated with the page fault error condition; and return the SBID associated with the memory access response and fault details of the page fault error condition to a debug register of the thread.

An Information Handling System (IHS) includes multiple hardware devices, and a baseboard Management Controller (BMC) in communication with the plurality of hardware devices. The BMC includes a first processor configured to execute a custom BMC firmware stack, and a second processor including executable instructions for receiving a request to perform a test on the first processor in which the request is received through a secure communication session established with a remote IHS. The instructions further perform the acts of controlling the first processor to perform the test according to the request, the first processor generating test results associated with the test, and transmitting the test results to the remote IHS through the secure communication session.