Microsoft Technology Licensing, LLC

Yimin Deng

Andrew J Ritz

Yue Zuo

Forrest Curtis Foltz

Arun Upadhyaya Kishan

Scott Chao-Chueh Lee

Hoi Huu Vo

Nicholas Stephen Judge

Allen Marshall

Vivek Bhanu

Ellsworth Davis Walker

Samer Arafeh

Bryan William Tuttle

Liang Yang

Lei Kou

Ho-Yuen Chau

Vivek P Divakara

Christopher Ahna

Hoyuen Chau

Albert Gordon Greenberg

Thomas Moscibroda

Yevgeniy Bak

Landy Wang

Daniel Max Firestone

Pankaj Garg

Kenneth Dean Johnson

Marcus Felipe Fontoura

Ke Wang

Monish Shantilal Shah

Saurabh Mohan Kulkarni

Melur K Raghuraman

Aditya Bhandari

Sameh Elnikety

Martijn De Kort

Chandrasekhar Pasupuleti

Ricardo Gouvêa Bianchini

Chiuchin Chen

Inigo Goiri Presa

Brian Jacob Corell

Carlos Jose Cela

HoYuen Chau

Ho Yuen Chau

Tai Hing Tse

Chin Hwan Park

Kapil Arya

Alper Gun

Yevgeniy M Bak

Nicholas S Judge

Samer N Arafeh

The present disclosure describes a type of virtual machine, which the present disclosure may refer to as a harvest virtual machine, that may allow improved utilization of physical computing resources on a cloud-computing system. First, the harvest virtual machine may be evictable. In other words, higher priority virtual machines may preempt the harvest virtual machine's access to physical computing resources. Second, the harvest virtual machine may receive access to a dynamic amount of physical computing resources during the course of its operating life. Third, the harvest virtual machine may have a minimum size (in terms of an amount of physical computing resources) and may terminate whenever the harvest virtual machine has access to an amount of physical computing resources less than the minimum size.

Harvest virtual machine for utilizing cloud-computing resources

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

A bare metal resource includes a trusted portion and an untrusted portion. The trusted portion includes trusted hardware, an image repository, and a clearance manager. The clearance manager is executable during bootup of the bare metal resource to perform a clearance process on the untrusted portion, including deleting the BIOS in the untrusted portion and loading a trusted BIOS from the image repository on the untrusted hardware, to place the untrusted portion in a trusted state. The bare metal resource may be provisioned to a tenant of a cloud provider after being placed in the trusted state.

Clearance of bare metal resource to trusted state usable in cloud computing

Computerized methods, systems, and computer-storage media for allowing virtual machines (VMs) residing on a common physical node to fairly share network bandwidth are provided. Restrictions on resource consumption are implemented to ameliorate stressing the network bandwidth or adversely affecting the quality of service (QoS) guaranteed to tenants of the physical node. The restrictions involves providing a scheduler that dynamically controls networking bandwidth allocated to each of the VMs as a function of QoS policies. These QoS policies are enforced by controlling a volume of traffic being sent from the VMs. Controlling traffic includes depositing tokens into token-bucket queues assigned to the VMs, respectively. The tokens are consumed as packets pass through the token-bucket queues. Upon consumption, packets are held until sufficient tokens are reloaded to the token-bucket queues.

Applying policies to schedule network bandwidth among virtual machines

Computerized methods, systems, and computer-storage media for throttling requests from virtual machines (VMs) to a hard-disk drive (HDD) are provided. When a request for disk I/O is received from a VM, a disk-drive model that simulates performance characteristics of the HDD is accessed. During access, the disk-drive model's estimation of HDD parameters and the disk-drive model's estimation of a current state of a disk head of the HDD are gathered. A projected execution time to carry out the request is computed as a function of the estimated HDD parameters and the estimated current state of the disk head. Also, an actual execution time to carry out the request is measured upon allowing the request to pass to the HDD. Using a comparison of the projected execution time and the actual execution time, the traffic of the requests from the VMs is throttled.

Throttle disk I/O using disk drive simulation model

Techniques for memory image capture via memory write from a running system are described. In at least some embodiments, a request is received for an image of a portion of memory. Images of memory can be used for a variety of purposes, such as diagnosing and repairing error conditions for hardware and/or software, detecting unwanted and/or malicious processes (e.g., malware), general systems maintenance, and so forth. According to one or more embodiments, various techniques can be implemented to capture an image of a portion of memory. For example, an intermediate write to memory can be employed to write the image of the portion of memory to a memory buffer. Alternatively or additionally, an image of a portion of memory can be captured directly to storage.

Memory image capture via memory write from a running system

Techniques and apparatuses for providing power-aware thread scheduling and dynamic use of processors are disclosed. In some aspects, a multi-core system is monitored to determine core activity. The core activity may be compared to a power policy that balances a power savings plan with a performance plan. One or more of the cores may be parked in response to the comparison to reduce power consumption by the multi-core system. In additional aspects, the power-aware scheduling may be performed during a predetermined interval to dynamically park or unpark cores. Further aspects include adjusting the power state of unparked cores in response to the comparison of the core activity and power policy.

Power-aware thread scheduling and dynamic use of processors

The present invention extends to methods, systems, and computer program products for offloading packet processing for networking device virtualization. A host maintains rule set(s) for a virtual machine, and a physical network interface card (NIC) maintains flow table(s) for the virtual machine. The physical NIC receives and processes a network packet associated with the virtual machine. Processing the network packet includes the physical NIC comparing the network packet with the flow table(s) at the physical NIC. When the network packet matches with a flow in the flow table(s) at the physical NIC, the physical NIC performs an action on the network packet based on the matching flow. Alternatively, when the network packet does not match with a flow in the flow table(s) at the physical NIC, the physical NIC passes the network packet to the host partition for processing against the rule set(s).

Offloading packet processing for networking device virtualization

Techniques for transparently replacing a processor, that receives interrupts in a partitioned computing device, with a replacement processor, are disclosed. In at least some embodiments, methods are discussed for directing the interrupts to an unchangeable identifier mapped to the processor's identifier and replacing the processor with the replacement processor. An intermediary, such as an I/O APIC, is used for storing the unchangeable identifier. The mapping may use logical mode delivery, physical mode delivery, or interrupt mapping.

Processor replacement

A method and apparatus for transparently replacing a processor, that receives interrupts in a partitioned computing device, with a replacement processor, is disclosed. The method comprises directing the interrupts to an unchangeable identifier mapped to the processor's identifier and replacing the processor with the replacement processor. An intermediary, such as an I/O APIC, is used for storing the unchangeable identifier. The mapping may use logical mode delivery, physical mode delivery, or interrupt mapping.

Transparent replacement of a system processor

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Sammamish, WA, United States of America

Yimin Deng