Abstract: A method of managing power state transitions for an interactive workload includes storing one or more parameters, each representing an electrical operating characteristic that controls power consumption of the processing unit, receiving a first user input requesting execution of a task by the processing unit, in response to receiving a second user input, modifying at least one of the one or more parameters, and executing the task in the processing unit while operating the processing unit according to the at least one modified parameter.

Abstract: A method of managing power state transitions for an interactive workload includes storing one or more parameters, each representing an electrical operating characteristic that controls power consumption of the processing unit, receiving a first user input requesting execution of a task by the processing unit, in response to receiving a second user input, modifying at least one of the one or more parameters, and executing the task in the processing unit while operating the processing unit according to the at least one modified parameter.

Abstract: First and second processor cores are configured to concurrently execute tasks. A scheduler is configured to schedule tasks for execution by the first and second processor cores. The first processor core is configured to selectively steal a task that was previously scheduled for execution by the second processor core based on additional power consumption incurred by migrating the task from the second processor core to the first processor core.

Abstract: A method of computing is performed in a first processing node of a plurality of processing nodes of multiple types with distinct processing capabilities. The method includes, in response to a command, partitioning data associated with the command among the plurality of processing nodes. The data is partitioned based at least in part on the distinct processing capabilities of the multiple types of processing nodes.

Abstract: In one form, a computer system includes a central processing unit, a memory controller coupled to the central processing unit and capable of accessing non-volatile random access memory (NVRAM), and an NVRAM-aware operating system. The NVRAM-aware operating system causes the central processing unit to selectively execute selected ones of a plurality of application programs, and is responsive to a predetermined operation to cause the central processing unit to execute a memory persistence procedure using the memory controller to access the NVRAM.

Abstract: A processor modifies memory management mode for a range of memory locations of a multilevel memory hierarchy based on changes in an application phase of an application executing at a processor. The processor monitors the application phase (e.g.,. computation-bound phase, input/output phase, or memory access phase) of the executing application and in response to a change in phase consults a management policy to identify a memory management mode. The processor automatically reconfigures a memory controller and other modules so that a range of memory locations of the multilevel memory hierarchy are managed according to the identified memory management mode. By changing the memory management mode for the range of memory locations according to the application phase, the processor improves processing efficiency and flexibility.

Abstract: A cluster compute server stores different types of data at different storage volumes in order to reduce data duplication at the storage volumes. The storage volumes are categorized into two classes: common storage volumes and dedicated storage volumes, wherein the common storage volumes store data to be accessed and used by multiple compute nodes (or multiple virtual servers) of the cluster compute server. The dedicated storage volumes, in contrast, store data to be accessed only by a corresponding compute node (or virtual server).

Abstract: The described embodiments comprise a selection mechanism that selects a resource from a set of resources in a computing device for performing an operation. In some embodiments, the selection mechanism performs a lookup in a table selected from a set of tables to identify a resource from the set of resources. When the resource is not available for performing the operation and until another resource is selected for performing the operation, the selection mechanism identifies a next resource in the table and selects the next resource for performing the operation when the next resource is available for performing the operation.

Abstract: Various datacenter or other computing center control apparatus and methods are disclosed. In one aspect, a method of computing is provided that includes defining plural processor performance bins where each processor performance bin has a processor performance state. At least one processor is assigned to each of the plural processor performance bins. Processor performance metrics of at least one of the processors are monitored while the at least one of the processors executes an incoming task. Processor power is modeled based on the monitored performance metrics. Future incoming tasks are assigned to one of the processor performance bins based on the modeled processor power.

Abstract: The present disclosure relates to a method and system for configuring a computing system, such as a cloud computing system. A method includes determining, based on a shared execution of a workload by a cluster of nodes of the computing system, that at least one node of the cluster of nodes operated at less than a threshold operating capacity during the shared execution of the workload. The method further includes selecting a modified hardware configuration of the cluster of nodes based on the determining such that the cluster of nodes with the modified hardware configuration has at least one of a reduced computing capacity and a reduced storage capacity.

Abstract: A system and method for efficiently limiting storage space for data with particular properties in a cache memory. A computing system includes a cache array and a corresponding cache controller. The cache array includes multiple banks, wherein a first bank is powered down. In response a write request to a second bank for data indicated to be stored in the powered down first bank, the cache controller determines a respective bypass condition for the data. If the bypass condition exceeds a threshold, then the cache controller invalidates any copy of the data stored in the second bank. If the bypass condition does not exceed the threshold, then the cache controller stores the data with a clean state in the second bank. The cache controller writes the data in a lower-level memory for both cases.

Abstract: An apparatus and method is described herein for conditionally committing and/or speculative checkpointing transactions, which potentially results in dynamic resizing of transactions. During dynamic optimization of binary code, transactions are inserted to provide memory ordering safeguards, which enables a dynamic optimizer to more aggressively optimize code. And the conditional commit enables efficient execution of the dynamic optimization code, while attempting to prevent transactions from running out of hardware resources. While the speculative checkpoints enable quick and efficient recovery upon abort of a transaction. Processor hardware is adapted to support dynamic resizing of the transactions, such as including decoders that recognize a conditional commit instruction, a speculative checkpoint instruction, or both. And processor hardware is further adapted to perform operations to support conditional commit or speculative checkpointing in response to decoding such instructions.

Abstract: A system, processor, and method to predict with high accuracy and retain instruction boundaries for previously executed instructions in order to decode variable length instructions is disclosed. In at least one embodiment, a disclosed processor includes an instruction fetch unit, an instruction cache, a boundary byte predictor, and an instruction decoder. In some embodiments, the instruction fetch unit provides an instruction address and the instruction cache produces an instruction tag and instruction cache content corresponding to the instruction address. The instruction decoder, in some embodiments, includes boundary byte logic to determine an instruction boundary in the instruction cache content.

Abstract: The described embodiments comprise a selection mechanism that selects a resource from a set of resources in a computing device for performing an operation. In some embodiments, the selection mechanism is configured to perform a lookup in a table selected from a set of tables to identify a resource from the set of resources. When the identified resource is not available for performing the operation and until a resource is selected for performing the operation, the selection mechanism is configured to identify a next resource in the table and select the next resource for performing the operation when the next resource is available for performing the operation.

Abstract: A method is performed in a computing system that includes a plurality of processing nodes of multiple types configurable to run in multiple performance states. In the method, an application executes on a thread assigned to a first processing node. Power and performance of the application on the first processing node is estimated. Power and performance of the application in multiple performance states on other processing nodes of the plurality of processing nodes besides the first processing node is also estimated. It is determined that the estimated power and performance of the application on a second processing node in a respective performance state of the multiple performance states is preferable to the power and performance of the application on the first processing node. The thread is reassigned to the second processing node, with the second processing node in the respective performance state.

Abstract: An approach and a method for efficient execution of nested map-reduce framework workloads to take advantage of the combined execution of central processing units (CPUs) and graphics processing units (GPUs) and lower latency of data access in accelerated processing units (APUs) is described. In embodiments, metrics are generated to determine whether a map or reduce function is more efficiently processed on a CPU or a GPU. A first metric is based on ratio of a number of branch instructions to a number of non-branch instructions, and a second metric is based on the comparison of execution times on each of the CPU and the GPU. Selecting execution of map and reduce functions based on the first and second metrics result in accelerated computations. Some embodiments include scheduling pipelined executions of functions on the CPU and functions on the GPU concurrently to achieve power-efficient nested map reduce framework execution.

Abstract: The present disclosure relates to a method and system for configuring a computing system, such as a cloud computing system. A method includes selecting, based on a user selection received via a user interface, a workload for execution on a cluster of nodes of the computing system. The workload is selected from a plurality of available workloads including an actual workload and a synthetic test workload. The method further includes configuring the cluster of nodes of the computing system to execute the selected workload such that processing of the selected workload is distributed across the cluster of nodes. The synthetic test workload may be generated by a code synthesizer based on a set of user-defined workload parameters provided via a user interface that identify execution characteristics of the synthetic test workload.

Abstract: An apparatus and method is described herein for conditionally committing and/or speculative checkpointing transactions, which potentially results in dynamic resizing of transactions. During dynamic optimization of binary code, transactions are inserted to provide memory ordering safeguards, which enables a dynamic optimizer to more aggressively optimize code. And the conditional commit enables efficient execution of the dynamic optimization code, while attempting to prevent transactions from running out of hardware resources. While the speculative checkpoints enable quick and efficient recovery upon abort of a transaction. Processor hardware is adapted to support dynamic resizing of the transactions, such as including decoders that recognize a conditional commit instruction, a speculative checkpoint instruction, or both. And processor hardware is further adapted to perform operations to support conditional commit or speculative checkpointing in response to decoding such instructions.

Abstract: A memory implements a programmable physical address mapping that can change to reflect changing memory access patterns, observed or anticipated, to the memory. The memory employs address decode logic that can implement any of a variety of physical address mappings between physical addresses and corresponding memory locations. The physical address mappings may locate the data within one or more banks and rows of the memory so as to facilitate more efficient memory accesses for a given access pattern. The programmable physical address mapping employed by the hardware of the memory can include, but is not limited to, hardwired logic gates, programmable look-up tables or other mapping tables, reconfigurable logic, or combinations thereof. The physical address mapping may be programmed for the entire memory or on a per-memory region basis.

Abstract: A device may receive information that identifies a first task to be processed, may determine a performance metric value indicative of a behavior of a processor while processing a second task, and may assign, based on the performance metric value, the first task to a bin for processing the first task, the bin including a set of processors that operate based on a power characteristic.