Microsoft Technology Licensing, LLC

Lei Kou

Scott Chao-Chueh Lee

Zhongyuan Li

Yimin Deng

Monish Shantilal Shah

Liang Yang

Martijn De Kort

Pushkar Vijay Chitnis

Ho-Yuen Chau

Simon Leet

Tianzhuang Dou

Chin Hwan Park

Brenda Wai Yan Bell

The disclosed technologies provide functionality for collecting quality of service ('QoS') statistics for in-use child physical functions of multiple physical function (“PF”) non-volatile memory devices (“MFNDs”). A host computing device creates a child PF on a MFND and configures the child PF on the MFND to provide a specified QoS level to an associated VM executing on the host computing device. The MFND then collects child PF QoS statistics for the child PF that describe the utilization of resources provided by child PF to an assigned VM. The MFND provides the child PF QoS statistics from the MFND to the host computing device. The collected child PF QoS statistics can be utilized to inform decisions regarding reallocation of MFND-provided resources, provisioning of new MFND-provided resources, and for other purposes.

Collecting quality of service statistics for in-use child physical functions of multiple physical function non-volatile memory devices

The disclosed technologies provide functionality for non-volatile memory device-assisted live migration of virtual machine ('VM') data. A host computing device (the “host”) requests that a source non-volatile memory device track changes to a namespace by a VM. In response thereto, the source device tracks changes made by the VM to the namespace and stores one or more data structures that identify the changed portions of the namespace. The host requests the data structures from the source device and requests the contents of the changed portions from the source device. The host then causes the data changed by the VM in the namespace to be written to a namespace on a target non-volatile memory device. The host can also retrieve the device internal state of a child physical function on the source device. The host migrates the retrieved device internal state to a child physical function on the target device.

Non-volatile memory device-assisted live migration of virtual machine data

The disclosed technologies include functionality for managing Multiple Physical Function NVMe Devices ('MFNDs') and the physical functions ('PFs') provided by MFNDs. For example, host devices can discover MFNDs, query the capabilities of MFNDs, and change the operating mode of an MFND between a user mode and a super administrator mode. Hosts can also utilize the disclosed technologies to create and delete individual child PFs on MFNDs. The disclosed technologies also include functionality for managing the settings associated with individual PFs of MFNDs. For example, hosts can query and modify the settings associated with individual child PFs of an MFND. The disclosed technologies also include functionality for managing the QoS provided by individual PFs of a MFND. For example, hosts can also query and modify the QoS provided by individual child PFs of an MFND.

Management of multiple physical function nonvolatile memory devices

Automatic detection of software program regression points enables developers to more quickly and accurately diagnose and solve issues in changes to software. Traces of instructions are collected from before and after a change to a program or settings thereto on a computing device and are compared to identify differences between the two traces. Areas of differences are ranked and returned to identify the point(s) of regression in the traces to alert a user of programs of behaviors to avoid and/or a developer a point to focus efforts on to patch the responsible program or update other programs around the responsible application.

Deviation finder

Enhanced longest common subsequence techniques are provided to improve efficiency and accuracy of any process that uses long sequences. Two superscale data sequences are received. Each data sequence is divided into a set of segments based on one or more heuristics or user input. From the sets of segments, pairs of segments are selected and processed using any longest common subsequence algorithm to determine the longest common subsequence for each pair of segments. The results of the processing are merged to determine the enhanced longest subsequence which is the longest common subsequence for the received superscale data sequences. Dividing the superscale data sequences into segments allows for parallel processing of each segment pair, which results in a faster completion time than prior art methods for determining longest common subsequences.

Determining enhanced longest common subsequences

A static multi-entry point function with more than one entry point is provided. The function allows callers to enter the function at different entry points using an offset. Each entry point of the function is associated with a different offset, and includes instructions that identify data that is associated with the entry point. Each entry point further includes an instruction that jumps to a common prologue of the function. The common prologue loads the identified data into local variables. The function also includes a functional component that performs different actions depending on the data in the local variables. The function includes a default entry point that is used when the function is called without any offset, so that the function appears to behave like a normal function to scanners.

Generating and executing multi-entry point functions

Instantiating an attestation facilitation component that allows a remote application to attest to a secure state of a secure memory application executing upon a secure platform of a computer system regardless of a type of either the secure platform or a health attestation service. Instantiation comprises identifying a property that includes at least one of the secure platform type and the health attestation service type. The instantiation is customized with the identified property. The attestation facilitation component verifies that a report generated by the secure platform represents that the secure memory application is operating in a secure state, and accesses a token generated by the health attestation service that represents that the secure platform is operating in a secure state. The attestation facilitation component generates a quote that allows the remote application to verify that the secure platform and the secure memory application are both operating in secure states.

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Redmond, WA, United States of America

Lei Kou