Abstract: Embodiments of an invention for protecting supervisor mode information are disclosed. In one embodiment, an apparatus includes a storage location, instruction hardware, execution hardware, and control logic. The storage location is to store an indicator to enable supervisor mode information protection. The instruction hardware is to receive an instruction to access supervisor mode information. The execution hardware is to execute the instruction. The control logic is to prevent execution of the instruction if supervisor mode information protection is enabled and a current privilege level is less privileged than a supervisor mode.

Abstract: Embodiments of an invention for protecting supervisor mode information are disclosed. In one embodiment, an apparatus includes a storage location, instruction hardware, execution hardware, and control logic. The storage location is to store an indicator to enable supervisor mode information protection. The instruction hardware is to receive an instruction to access supervisor mode information. The execution hardware is to execute the instruction. The control logic is to prevent execution of the instruction if supervisor mode information protection is enabled and a current privilege level is less privileged than a supervisor mode.

Abstract: Embodiments of an invention for protecting supervisor mode information are disclosed. In one embodiment, an apparatus includes a storage location, instruction hardware, execution hardware, and control logic. The storage location is to store an indicator to enable supervisor mode information protection. The instruction hardware is to receive an instruction to access supervisor mode information. The execution hardware is to execute the instruction. The control logic is to prevent execution of the instruction if supervisor mode information protection is enabled and a current privilege level is less privileged than a supervisor mode.

Abstract: Embodiments of an invention for protecting supervisor mode information are disclosed. In one embodiment, an apparatus includes a storage location, instruction hardware, execution hardware, and control logic. The storage location is to store an indicator to enable supervisor mode information protection. The instruction hardware is to receive an instruction to access supervisor mode information. The execution hardware is to execute the instruction. The control logic is to prevent execution of the instruction if supervisor mode information protection is enabled and a current privilege level is less privileged than a supervisor mode.

Abstract: Embodiments of an invention for protecting supervisor mode information are disclosed. In one embodiment, an apparatus includes a storage location, instruction hardware, execution hardware, and control logic. The storage location is to store an indicator to enable supervisor mode information protection. The instruction hardware is to receive an instruction to access supervisor mode information. The execution hardware is to execute the instruction. The control logic is to prevent execution of the instruction if supervisor mode information protection is enabled and a current privilege level is less privileged than a supervisor mode.

Abstract: Systems and methods that manage memory usage by a virtual machine are provided. These systems and methods compact the virtual machine's memory footprint, thereby promoting efficient use of memory and gaining performance benefits of increased data locality. In some embodiments, a guest operating system running within the virtual machine is enhanced to allocate its VM memory in a compact manner. The guest operating system includes a memory manager that is configured to reference an artificial access cost when identifying memory areas to allocate for use by applications. These access costs are described as being artificial because they are not representative of actual, hardware based access costs, but instead are fictitious costs that increase as the addresses of the memory areas increase. Because of these increasing artificial access costs, the memory manager identifies memory areas with lower addresses for allocation and use prior to memory areas with higher addresses.

Abstract: The present disclosure provides RNG states. Generating the RNG states can include creating a first VM with a first RNG state and a second VM with a second RNG state and generating a plurality of interrupts for the first VM and the second VM. Generating the RNG states can also include providing the plurality of interrupts to the first VM with a first plurality of time intervals between the plurality of interrupts to configure the first RNG state and providing the plurality of interrupts to the second VM with a second plurality of time intervals, between the plurality of interrupts, that are different from the first plurality of time intervals to configure the second RNG state to be different from the first RNG state.

Abstract: Embodiments of an invention for protecting supervisor mode information are disclosed. In one embodiment, an apparatus includes a storage location, instruction hardware, execution hardware, and control logic. The storage location is to store an indicator to enable supervisor mode information protection. The instruction hardware is to receive an instruction to access supervisor mode information. The execution hardware is to execute the instruction. The control logic is to prevent execution of the instruction if supervisor mode information protection is enabled and a current privilege level is less privileged than a supervisor mode.

Abstract: Systems and methods that manage memory usage by a virtual machine are provided. These systems and methods compact the virtual machine's memory footprint, thereby promoting efficient use of memory and gaining performance benefits of increased data locality. In some embodiments, a guest operating system running within the virtual machine is enhanced to allocate its VM memory in a compact manner. The guest operating system includes a memory manager that is configured to reference an artificial access cost when identifying memory areas to allocate for use by applications. These access costs are described as being artificial because they are not representative of actual, hardware based access costs, but instead are fictitious costs that increase as the addresses of the memory areas increase. Because of these increasing artificial access costs, the memory manager identifies memory areas with lower addresses for allocation and use prior to memory areas with higher addresses.

Abstract: Embodiments of an invention for protecting supervisor mode information are disclosed. In one embodiment, an apparatus includes a storage location, instruction hardware, execution hardware, and control logic. The storage location is to store an indicator to enable supervisor mode information protection. The instruction hardware is to receive an instruction to access supervisor mode information. The execution hardware is to execute the instruction. The control logic is to prevent execution of the instruction if supervisor mode information protection is enabled and a current privilege level is less privileged than a supervisor mode.

Abstract: In one embodiment, the present invention includes a method for generating a list of files accessed during an operating system (OS) boot process to profile the OS boot process, and optimizing the list of files to generate an optimized file list for use in future OS boot processes, where the optimizing is according to a first optimization technique if the files were accessed from a solid state medium and according to a second optimization technique if the files were accessed from a rotating medium. Other embodiments are described and claimed.

Abstract: Technologies are provided in embodiments to detect malware. Embodiments are to receive context information related to a potentially affected system, create a prediction of normal traffic based, at least in part, on the received context information, compare network traffic associated with the potentially affected system to the prediction of normal traffic, and take an action based, at least in part, on the comparison. The action may be taken if the network traffic is not within an acceptable deviation range of the prediction of normal traffic or the action may be taken based on a degree of deviation of the network traffic from the prediction of normal traffic. The acceptable deviation range and the degree of deviation are based, at least in part, on a type of network traffic. The acceptable deviation range and the degree of deviation are based, at least in part, on a volume of network traffic.

Abstract: The present disclosure provides RNG states. Generating the RNG states can include creating a first VM with a first RNG state and a second VM with a second RNG state and generating a plurality of interrupts for the first VM and the second VM.

Abstract: Technologies for reducing connection time to a wireless access point includes recording wireless connection information in a log, computing parameters as a function of past wireless connection information in the log, generating an ordered list of wireless access points most likely to be available for reconnection at a desired time as a function of recent wireless connection information in the log, and directly probing a wireless access point instead of initiating a wireless access point scan. In some embodiments, computing parameters as a function of past wireless connection information in the log comprises performing genetic programming operations to generate prediction programs for later prediction of wireless access points most likely to be available for reconnection at a desired time.

Abstract: Embodiments of techniques and systems for performance of predicted actions are described. In embodiments, a predicted action performance engine (“PAE”) may receive one or probabilities of potential actions that may be performed on a computing device. The PAE may also receive a system context for the computing device describing available resources on the computing device, workload, etc. Based on these probabilities and the system context, the PAE may determine one or more predicted actions and/or resource utilizations which are likely to occur and which may be performed ahead of time. The PAE may then facilitate performance of these actions and/or resource utilizations. Other embodiments may be described and claimed.

Abstract: Techniques to prelink software to improve memory de-duplication in a virtual system are described. An apparatus may comprise a processor circuit, a memory unit coupled to the processor circuit to store private memory pages for multiple virtual machines, and a dynamic linker application operative on the processor circuit to link a binary version of a software program with associated program modules at run-time of the binary version on a virtual machine. The dynamic linker application may comprise a master prelink component operative on the processor circuit to relocate a first set of program modules for a first binary version of the software program for a first virtual machine using a first set of virtual memory addresses from a first private memory page allocated to the first virtual machine, and store relocation information for the first set of program modules in a global prelink layout map for use by a second virtual machine. Other embodiments are described and claimed.

Abstract: Methods and apparatus for using per task time slice information to improve dynamic performance state selection are described. In one embodiment, a new performance state is selected for a process based on one or more previous execution time slice values of the process. Other embodiments are also described.

Abstract: Embodiments of techniques and systems for performance of predicted actions are described. In embodiments, a predicted action performance engine (“PAE”) may receive one or probabilities of potential actions that may be performed on a computing device. The PAE may also receive a system context for the computing device describing available resources on the computing device, workload, etc. Based on these probabilities and the system context, the PAE may determine one or more predicted actions and/or resource utilizations which are likely to occur and which may be performed ahead of time. The PAE may then facilitate performance of these actions and/or resource utilizations. Other embodiments may be described and claimed.

Abstract: Embodiments of techniques and systems for performance of predicted actions are described. In embodiments, a predicted action performance engine (“PAE”) may receive one or probabilities of potential actions that may be performed on a computing device. The PAE may also receive a system context for the computing device describing available resources on the computing device, workload, etc. Based on these probabilities and the system context, the PAE may determine one or more predicted actions and/or resource utilizations which are likely to occur and which may be performed ahead of time. The PAE may then facilitate performance of these actions and/or resource utilizations. Other embodiments may be described and claimed.

Abstract: Technologies are provided in embodiments to detect malware. Embodiments are to receive context information related to a potentially affected system, create a prediction of normal traffic based, at least in part, on the received context information, compare network traffic associated with the potentially affected system to the prediction of normal traffic, and take an action based, at least in part, on the comparison. The action may be taken if the network traffic is not within an acceptable deviation range of the prediction of normal traffic or the action may be taken based on a degree of deviation of the network traffic from the prediction of normal traffic. The acceptable deviation range and the degree of deviation are based, at least in part, on a type of network traffic. The acceptable deviation range and the degree of deviation are based, at least in part, on a volume of network traffic.