Abstract: A storage abstraction system is described herein that exposes storage from an operating system as a uniform storage device and abstracts from applications the selection of a particular storage location and different properties of storage devices. The application provides the data to store and some information about the application's goals for storing the data, and lets the operating system route the data to the right place based on the data's characteristics. The operating system may choose to store data anywhere from L2 cache to a cloud-based storage service and anything in between, based on information about the data's persistence requirements, expected usage, access frequency, security needs, and so forth. The system lets applications and users focus on expressing their goals and needs for the data, and lets the operating system manage the hardware.

Abstract: Pairing information is used by the target application to determine how to connect to the correct controller. A network pipe is established between the target application and the controller. The network pipe is used to pass information, such as to deliver/receive test information, between the controller and target application. A bridge may also be established between the controller and an analysis tool for the device hosting the target application. The bridge creates a communication path for the controller to send/receive information (e.g. commands, queries) to the analysis tool s to perform tests of the target application. Code may also be injected into the target application such that dynamic linked libraries may be simulated. Crash data may also be obtained by the controller (or some other device) that may not be typically available by a particular device platform.

Abstract: A power context system is described herein that makes decisions related to device power usage based on factors such as location, load, available alternatives, cost of power, and cost of bandwidth. The system incorporates contextual knowledge about the situation in which a device is being used. Using the context of location, devices can make smarter decisions about deciding which processes to migrate to the cloud, load balancing between applications, and switching to power saving modes depending on how far the user is from a power source. As the cloud becomes more frequently used, load balancing by utilizing distributed data warehouses to move processes to different locations in the world depending on factors such as accessibility, locales, and cost of electricity are considerations for power management. Power management of mobile devices is becoming important as integration with the cloud yields expectations of devices being able to reliably access and persist data.

Abstract: A storage abstraction system is described herein that exposes storage from an operating system as a uniform storage device and abstracts from applications the selection of a particular storage location and different properties of storage devices. The application provides the data to store and some information about the application's goals for storing the data, and lets the operating system route the data to the right place based on the data's characteristics. The operating system may choose to store data anywhere from L2 cache to a cloud-based storage service and anything in between, based on information about the data's persistence requirements, expected usage, access frequency, security needs, and so forth. The system lets applications and users focus on expressing their goals and needs for the data, and lets the operating system manage the hardware.

Abstract: A power context system is described herein that makes decisions related to device power usage based on factors such as location, load, available alternatives, cost of power, and cost of bandwidth. The system incorporates contextual knowledge about the situation in which a device is being used. Using the context of location, devices can make smarter decisions about deciding which processes to migrate to the cloud, load balancing between applications, and switching to power saving modes depending on how far the user is from a power source. As the cloud becomes more frequently used, load balancing by utilizing distributed data warehouses to move processes to different locations in the world depending on factors such as accessibility, locales, and cost of electricity are considerations for power management. Power management of mobile devices is becoming important as integration with the cloud yields expectations of devices being able to reliably access and persist data.

Abstract: A storage abstraction system is described herein that exposes storage from an operating system as a uniform storage device and abstracts from applications the selection of a particular storage location and different properties of storage devices. The application provides the data to store and some information about the application's goals for storing the data, and lets the operating system route the data to the right place based on the data's characteristics. The operating system may choose to store data anywhere from L2 cache to a cloud-based storage service and anything in between, based on information about the data's persistence requirements, expected usage, access frequency, security needs, and so forth. The system lets applications and users focus on expressing their goals and needs for the data, and lets the operating system manage the hardware.

Abstract: A heterogeneous processing system is described herein that provides a software hypervisor to autonomously control operating system thread scheduling across big and little cores without the operating system's awareness or involvement to improve energy efficiency or meet other processing goals. The system presents a finite set of virtualized compute cores to the operating system to which the system schedules threads for execution. Subsequently, the hypervisor intelligently controls the physical assignment and selection of which core(s) execute each thread to manage energy use or other processing requirements. By using a software hypervisor to abstract the underlying big and little computer architecture, the performance and power operating differences between the cores remain opaque to the operating system. The inherent indirection also decouples the release of hardware with new capabilities from the operating system release schedule.

Abstract: A heterogeneous processing system is described herein that provides a software hypervisor to autonomously control operating system thread scheduling across big and little cores without the operating system's awareness or involvement to improve energy efficiency or meet other processing goals. The system presents a finite set of virtualized compute cores to the operating system to which the system schedules threads for execution. Subsequently, the hypervisor intelligently controls the physical assignment and selection of which core(s) execute each thread to manage energy use or other processing requirements. By using a software hypervisor to abstract the underlying big and little computer architecture, the performance and power operating differences between the cores remain opaque to the operating system. The inherent indirection also decouples the release of hardware with new capabilities from the operating system release schedule.

Abstract: Pairing information is used by the target application to determine how to connect to the correct controller. A network pipe is established between the target application and the controller. The network pipe is used to pass information, such as to deliver/receive test information, between the controller and target application. A bridge may also be established between the controller and an analysis tool for the device hosting the target application. The bridge creates a communication path for the controller to send/receive information (e.g. commands, queries) to the analysis tool s to perform tests of the target application. Code may also be injected into the target application such that dynamic linked libraries may be simulated. Crash data may also be obtained by the controller (or some other device) that may not be typically available by a particular device platform.

Abstract: A storage abstraction system is described herein that exposes storage from an operating system as a uniform storage device and abstracts from applications the selection of a particular storage location and different properties of storage devices. The application provides the data to store and some information about the application's goals for storing the data, and lets the operating system route the data to the right place based on the data's characteristics. The operating system may choose to store data anywhere from L2 cache to a cloud-based storage service and anything in between, based on information about the data's persistence requirements, expected usage, access frequency, security needs, and so forth. The system lets applications and users focus on expressing their goals and needs for the data, and lets the operating system manage the hardware.

Abstract: A power context system is described herein that makes decisions related to device power usage based on factors such as location, load, available alternatives, cost of power, and cost of bandwidth. The system incorporates contextual knowledge about the situation in which a device is being used. Using the context of location, devices can make smarter decisions about deciding which processes to migrate to the cloud, load balancing between applications, and switching to power saving modes depending on how far the user is from a power source. As the cloud becomes more frequently used, load balancing by utilizing distributed data warehouses to move processes to different locations in the world depending on factors such as accessibility, locales, and cost of electricity are considerations for power management. Power management of mobile devices is becoming important as integration with the cloud yields expectations of devices being able to reliably access and persist data.

Abstract: A heterogeneous processing system is described herein that provides a software hypervisor to autonomously control operating system thread scheduling across big and little cores without the operating system's awareness or involvement to improve energy efficiency or meet other processing goals. The system presents a finite set of virtualized compute cores to the operating system to which the system schedules threads for execution. Subsequently, the hypervisor intelligently controls the physical assignment and selection of which core(s) execute each thread to manage energy use or other processing requirements. By using a software hypervisor to abstract the underlying big and little computer architecture, the performance and power operating differences between the cores remain opaque to the operating system. The inherent indirection also decouples the release of hardware with new capabilities from the operating system release schedule.

Abstract: A storage placement system is described herein that uses an operating system's knowledge related to how data is being used on a computing device to more effectively communicate with and manage flash-based storage devices. Cold data that is not frequently used can be differentiated from hot data clusters and placed in worn areas, while hot data that is frequently used can be kept readily accessible. By clustering hot data together and cold data in separate sections, the system is better able to perform wear leveling and prolong the usefulness of the flash medium. Storage of data in the cloud or other storage can intelligently persist data in a location for a short time before coalescing data to write in a block. Thus, the system leverages the operating system's knowledge of how data has been and will be used to place data on flash-based storage devices in an efficient way.

Abstract: A flash driver tracks data stored in a flash memory device through the use of logical-to-physical sector mapping. The mapping is stored in a data structure and allows data to be written into the next free physical sector in the flash memory medium. Write operations complete quickly, because there is no need to perform an erase operation in order to write new data on to the flash memory medium. Data loss due to power interruption during a write operation is also minimized by the described implementations. The logical-to-physical sector mapping stored in data structure is backed-up on the flash memory medium. In the event there is a catastrophic power interruption, logical-to-physical sector mapping can easily be reestablished by scanning the backed-up mapping in the flash memory medium. The backed-up information can be stored in a spare portion of a NAND or NOR flash memory medium.

Abstract: A transactional file system developed to function with flash memory is described. The file system performs power-failure detection and ensures data integrity in the event of a power failure. In one described implementation, a power failure event can be detected by a file system, components of the file system, or individual modules in the form or computer-executable instructions and/or logic. Meta-information is stored at a location on a flash medium indicated by a write pointer if a computer device shuts-down according to a normal shutdown mode. During initialization of the computer, a check is performed whether the meta-information is present in the location on the flash medium indicated by the write pointer. If the meta-information is present, then a conclusion is made that the computer shutdown according to the normal shutdown mode.

Abstract: A transactional file system developed to function with flash memory is described. The file system performs power-failure detection and ensures data integrity in the event of a power failure. In one described implementation, a power failure event can be detected by a file system, components of the file system, or individual modules in the form or computer-executable instructions and/or logic. Meta-information is stored at a location on a flash medium indicated by a write pointer if a computer device shuts-down according to a normal shutdown mode. During initialization of the computer, a check is performed whether the meta-information is present in the location on the flash medium indicated by the write pointer. If the meta-information is present, then a conclusion is made that the computer shutdown according to the normal shutdown mode.

Abstract: A transactional file system developed to function with flash memory is described. The file system performs power-failure detection and ensures data integrity in the event of a power failure. In one described implementation, a power failure event can be detected by a file system, components of the file system, or individual modules in the form or computer-executable instructions and/or logic. Meta-information is stored at a location on a flash medium indicated by a write pointer if a computer device shuts-down according to a normal shutdown mode. During initialization of the computer, a check is performed whether the meta-information is present in the location on the flash medium indicated by the write pointer. If the meta-information is present, then a conclusion is made that the computer shutdown according to the normal shutdown mode.

Abstract: One or more secondary data structures are maintained containing mappings of logical flash memory addresses to physical flash memory addresses. Each secondary data structure has a predetermined capacity of mappings. A master data structure is also maintained containing a pointer to each of the one or more secondary data structures. Additional secondary data structures are allocated as needed to provide capacity for additional mappings. One or more counters associated with each of the one or more secondary data structures, respectively, provides an indication of when each of the one or more secondary data structures reaches the predetermined capacity of mappings.

Abstract: A transactional file system developed to function with flash memory is described. The file system provides for efficient storage of file system meta-information, performs robust transaction logging, and performs other related features. In one described implementation, metadata is stored in-line with data. In another embodiment, a transaction log is maintained by storing transaction information associated with requests to perform file transactions. The transaction information is stored at arbitrary physical sector addresses on the flash medium. In still another embodiment, a transaction log is stored in a physical sector of a flash medium. The transaction log contains transaction information associated with performing a file request. Metadata is written into a spare area of the physical sector indicating that the physical sector contains transaction information.

Abstract: A flash driver tracks data stored in a flash memory device through the use of logical-to-physical sector mapping. The mapping is stored in a data structure and allows data to be written into the next free physical sector in the flash memory medium. Write operations complete quickly, because there is no need to perform an erase operation in order to write new data on to the flash memory medium. Data loss due to power interruption during a write operation is also minimized by the described implementations. The logical-to-physical sector mapping stored in data structure is backed-up on the flash memory medium. In the event there is a catastrophic power interruption, logical-to-physical sector mapping can easily be reestablished by scanning the backed-up mapping in the flash memory medium. The backed-up information can be stored in a spare portion of a NAND or NOR flash memory medium.