Abstract: A method, a computer program product, and a system for initializing components to monitor for unauthorized encryptions of filesystem objects stored on a computing system. The method includes configuring an encryption monitor register to establish monitoring preferences of filesystem objects and allocating a predetermined size of persistent memory as a backup memory area for storing pre-encrypted versions of the filesystem objects. The method also includes inserting a starting address of the backup memory area in data bits of the encryption monitor register, and setting encryption monitor bits of page table entries in a hardware page table that correspond to at least one filesystem object, thereby establishing encryption monitoring of the filesystem object.

Abstract: A method, a computer program product, and a system for mitigating unauthorized encryptions of filesystem objects stored on a computing system. The method includes allocating a backup memory area for storing pre-encrypted filesystem objects, setting data bits in an encryption register that allow for monitoring a filesystem object marked for ransomware protection. The method also includes calculating an encryption rate of an encryption occurring on the filesystem object and determining that the encryption rate of the filesystem object exceeds an encryption-rate threshold. The encryption-rate threshold can be set by an administrator when marking the filesystem object for ransomware protection. The method further includes generating an alert to an administrator that the encryption rate of the filesystem object exceeds the encryption rate threshold and storing a backup of the filesystem object for a predetermined amount of time in the backup memory area.

Abstract: A method, a computer program product, and a system for initializing components to monitor for unauthorized encryptions of filesystem objects stored on a computing system. The method includes configuring an encryption monitor register to establish monitoring preferences of filesystem objects and allocating a predetermined size of persistent memory as a backup memory area for storing pre-encrypted versions of the filesystem objects. The method also includes inserting a starting address of the backup memory area in data bits of the encryption monitor register, and setting encryption monitor bits of page table entries in a hardware page table that correspond to at least one filesystem object, thereby establishing encryption monitoring of the filesystem object.

Abstract: Communication endpoints associated with a virtual machine for migration can be discovered. Properties associated with the communication endpoints can be discovered. The communication endpoints can be matched to establish a communication channel between the endpoints. The communication endpoints, the properties and the at least one communication channel can be used in recreating the communication channel for a migrated version of the virtual machine.

Abstract: Provided is a method for certifying a communicative connection. The method includes, in response to receiving a first request from a first virtualized communication endpoint (VCE), allocating and assigning a first communication portal to the first VCE, generating an encryption key associated with the first communication portal, and returning the encryption key and an identification of the first communication portal to the first VCE. The method further includes, in response to receiving a second request from a second VCE to establish a communicative connection with the first communication portal, the second request being accompanied by an encrypted certificate, comparing, using the encryption key, the information included in the certificate with certificate input information. The method further includes, in response to determining that the information included in the certificate matches the certificate input information, establishing the communicative connection between the first VCE and the second VCE.

Abstract: A method and system are provided. The method includes generating, by a machine-based sentiment prediction generator, respective machine-determined sentiment predictions for each of a plurality of software patches using sentiment analysis. The method further includes setting, by a sentiment-based confidence value generator, a confidence value for each of the plurality of software patches based on the machine-determined sentiment predictions. The method also includes at least one of selecting and prioritizing, by a software patch selector and prioritizer, at least one of the plurality of software patches based on the respective confidence value therefor.

Abstract: Various embodiments execute a program with improved cache efficiency. In one embodiment, a first subset of operations of a program is performed on a plurality of objects stored in one or more data structures. The first subset of operations has a regular memory access pattern. After each operation in the first subset of operations has been performed, results of the operation are stored in one of the plurality of queues. Each queue in the plurality of queues is associated with a different cacheable region of a memory. A second subset of operations in the program is performed utilizing at least one queue in the plurality of queues. The second subset of operations utilizes results of the operations in the first subset of operations stored in the queue. The second subset of operations has an irregular memory access pattern that is regularized by localizing memory locations accessed by the second subset of operations to the cacheable region of memory associated with the at least one queue.

Abstract: Communication endpoints associated with a virtual machine for migration can be discovered. Properties associated with the communication endpoints can be discovered. The communication endpoints can be matched to establish a communication channel between the endpoints. The communication endpoints, the properties and the at least one communication channel can be used in recreating the communication channel for a migrated version of the virtual machine.

Abstract: The present disclosure relates to sharing an I/O device across multiple virtual machines. According to one embodiment, a computing system configures shared ownership of the I/O device between a first partition and one or more of the plurality of virtual machines. The computing system transfers partial ownership of the I/O device from the first partition to the one or more virtual machines and generates device configuration information for the I/O device. The virtual machines can use the generated device configuration information to access and configure the I/O device. Once the I/O device is configured for shared ownership, the computing system boots the one or more virtual machines.

Abstract: A server LPAR operating in a virtualized computer shares pages with client LPARs using a shared memory region (SMR). A virtualization function of the computer receives a get-page-ID request associated with a client LPAR to identify a physical page corresponding to a shared page included in the SMR. The virtualization function requests the server LPAR to provide an identity of the physical page. The virtualization function receives a page-ID response comprising the identity of a server LPAR logical page that corresponds to the physical page. The virtualization element determines a physical page identity and communicates the physical page identity to the client LPAR. The virtualization element receives a page ID enter request and enters an identity of the physical page into a translation element of the computer to associate a client LPAR logical page with the physical page.

Abstract: A server logical partition (LPAR) of a virtualized computer includes shared memory regions (SMRs). The SMRs include pages of the server LPAR memory to share with client LPARs. A hypervisor utilizes an export vector to associate logical pages of the server LPAR with SMRs. The hypervisor further utilizes a reference array to associate SMRs with client LPARs that have mapped at least one physical memory page of the SMR from a logical page of the client LPAR memory. In processing an operation to unmap one or more shared physical pages from one or more LPARs, the hypervisor uses the export vector and reference array to determine which LPARs have had a mapping to the physical pages.

Abstract: Systems, methods, and computer program products to perform an operation comprising executing a device driver in a private logical partition on a compute host, wherein the device driver is configured to execute in an environment different than an environment of a hypervisor of the compute host, establishing a communication channel between the private logical partition and an adjunct partition executing on the compute host, and configuring, responsive to a command sent by the adjunct partition to the device driver via the communication channel, a physical function of a single root I/O virtualization (SR-IOV) device of the host system.

Abstract: A server LPAR operating in a virtualized computer shares pages with client LPARs using a shared memory region (SMR). A virtualization function of the computer receives a get-page-ID request associated with a client LPAR to identify a physical page corresponding to a shared page included in the SMR. The virtualization function requests the server LPAR to provide an identity of the physical page. The virtualization function receives a page-ID response comprising the identity of a server LPAR logical page that corresponds to the physical page. The virtualization element determines a physical page identity and communicates the physical page identity to the client LPAR. The virtualization element receives a page ID enter request and enters an identity of the physical page into a translation element of the computer to associate a client LPAR logical page with the physical page.

Abstract: A server logical partition (LPAR) of a virtualized computer includes shared memory regions (SMRs). The SMRs include pages of the server LPAR memory to share with client LPARs. A hypervisor utilizes an export vector to associate logical pages of the server LPAR with SMRs. The hypervisor further utilizes a reference array to associate SMRs with client LPARs that have mapped at least one physical memory page of the SMR from a logical page of the client LPAR memory. In processing an operation to unmap one or more shared physical pages from one or more LPARs, the hypervisor uses the export vector and reference array to determine which LPARs have had a mapping to the physical pages.

Abstract: A server LPAR operating in a virtualized computer shares pages with client LPARs using a shared memory region (SMR). A virtualization function of the computer receives a get-page-ID request associated with a client LPAR to identify a physical page corresponding to a shared page included in the SMR. The virtualization function requests the server LPAR to provide an identity of the physical page. The virtualization function receives a page-ID response comprising the identity of a server LPAR logical page that corresponds to the physical page. The virtualization element determines a physical page identity and communicates the physical page identity to the client LPAR. The virtualization element receives a page ID enter request and enters an identity of the physical page into a translation element of the computer to associate a client LPAR logical page with the physical page.

Abstract: A server logical partition (LPAR) of a virtualized computer includes shared memory regions (SMRs). The SMRs include pages of the server LPAR memory to share with client LPARs. A hypervisor utilizes an export vector to associate logical pages of the server LPAR with SMRs. The hypervisor further utilizes a reference array to associate SMRs with client LPARs that have mapped at least one physical memory page of the SMR from a logical page of the client LPAR memory. In processing an operation to unmap one or more shared physical pages from one or more LPARs, the hypervisor uses the export vector and reference array to determine which LPARs have had a mapping to the physical pages.

Abstract: A method and system are provided. The method includes generating, by a machine-based sentiment prediction generator, respective machine-determined sentiment predictions for each of a plurality of software patches using sentiment analysis. The method further includes setting, by a sentiment-based confidence value generator, a confidence value for each of the plurality of software patches based on the machine-determined sentiment predictions. The method also includes at least one of selecting and prioritizing, by a software patch selector and prioritizer, at least one of the plurality of software patches based on the respective confidence value therefor.

Abstract: A method and system are provided. The method includes generating, by a machine-based sentiment prediction generator, respective machine-determined sentiment predictions for each of a plurality of software patches using sentiment analysis. The method further includes setting, by a sentiment-based confidence value generator, a confidence value for each of the plurality of software patches based on the machine-determined sentiment predictions. The method also includes at least one of selecting and prioritizing, by a software patch selector and prioritizer, at least one of the plurality of software patches based on the respective confidence value therefor.

Abstract: A method for diagnosing software crashes includes calculating, using vector space modeling, angles between vectors representing stack-traces from reports in a repository on one or more server computer systems, to define similarities in the reports, wherein reports are deemed similar where angles between their respective vectors are less than a threshold value. The method further includes grouping the reports into similar sets using a maximal cliques process and automatically diagnosing, in response to a received software crash, a first stack-trace extracted from a first report of the received software crash, to determine a potential solution to the received software crash.

Abstract: A method and system are provided. The method includes generating, by a machine-based sentiment prediction generator, respective machine-determined sentiment predictions for each of a plurality of software patches using sentiment analysis. The method further includes setting, by a sentiment-based confidence value generator, a confidence value for each of the plurality of software patches based on the machine-determined sentiment predictions. The method also includes at least one of selecting and prioritizing, by a software patch selector and prioritizer, at least one of the plurality of software patches based on the respective confidence value therefor.