Abstract:
A distributed file system and a data block consistency managing method thereof are disclosed. The method comprises: a file location register generates the values of the counters corresponding to CHUNKs and the values of the counters are simultaneously stored in file access servers and a file location register; when writing data into a CHUNK, a file access client writes data into both the main and standby file access servers and revises the values of counters of CHUNKs in the file access servers into which data is written normally; the file location register takes the CHUNK whose counter has the maximal value as the normal and valid one according to the corresponding values of the counters of corresponding CHUNK reported by the main and standby file access servers.
Abstract:
An operation management apparatus obtains a value Xi indicating the number of process requests being processed by an information processing apparatus during each sampling operation, from N samplings acquired during a specific time period from the information processing apparatus, wherein N is an integer satisfying a condition of 1≦N, and i is an integer satisfying a condition of 1≦i≦N. The apparatus determines, for a plurality of information processing apparatuses, a ratio of the sum of values Xi, each value Xi having a difference, from a maximum value of the values Xi, falling within a specific range, to the total sum of the values Xi. The apparatus detects an information processing apparatus having the ratio equal to or higher than a specific value.
Abstract:
A technique includes providing data indicative of a counted value acquired by a hardware counter of a processing core during a time segment in which a plurality of tasks are active on the core and, in a processor-based machine, determining a likelihood that the counted value is attributable to a given task of the tasks during the time segment and attributing a portion of the counted value to the given task based at least in part on the determined likelihood.
Abstract:
Example methods and apparatus to dynamically optimize platforms are disclosed. A disclosed example method includes configuring a processor to operate in a first mode, executing a workload on the processor, and sampling a plurality of registers associated with a performance monitoring unit (PMU). The example method also includes transforming the sampled plurality of registers into a Gaussian signal, partitioning the probabilistic model representation into a plurality of discrete output symbols, and associating one of the plurality of discrete output symbols with the workload based on a probability value associated with the one of the plurality of discrete output symbols.
Abstract:
A method, apparatus, and computer instructions in a data processing system for monitoring the execution of instructions and accesses to memory locations. If an instruction is associated with a indicator, a counter associated with the instruction is incremented in response to detecting execution of the instruction. The indicator may be associated with a memory location with a counter associated with the memory location being incremented in response to an access of the memory location.
Abstract:
Disclosed is a method and system for determining one or more performance characteristics of a target server. A command is transmitted from a coordinator to a plurality of clients. The command instructs the plurality of clients to each transmit a request targeting a sub-system of said target server. A response time is then received from each client and a performance characteristic is determined from the received response times.
Abstract:
Analysis may be made of the amount that a load on a machine impacts the machine's performance. Performance counters on the machine record raw statistical data, such as a given resource's current utilization. The values of these counters may be captured. A n-bin histogram may be created that shows how many of the captured performance counter values occur within various ranges, such as 0-10% utilization, 10-20%, etc. A weight may be assigned to each bin. A weighted sum of the bins may be calculated by multiplying the number of occurrences in each bin by the bin's weight, and adding the products together. The weights may be chosen to reflect the relative amounts that particular performance counter values impact the overall performance of a machine. Thus, a metric that represents performance impact may be calculated based on the weighted sum.
Abstract:
Techniques are disclosed for detection of performance conditions in processing systems. For example, a method of detecting a performance condition in at least one particular processing device of a processing system having a plurality of processing devices includes the following steps. Data is input to a data structure associated with the particular processing device, over a given time period. The input data may be a buffer or a bucket. The input data represents data associated with the execution of at least one function performed by the particular processing device. The given time period includes the time period between consecutive heartbeat signals transmitted by the particular processing device. At least a portion of the input data is removed from the data structure associated with the particular processing device, near the end of the given time period. The removed input data is compared to an expected function execution level. An alarm signal is generated, when warranted, based on the comparison of the removed input data to the expected function execution level such that a performance condition in the particular processing device is determinable.
Abstract:
A computer implemented method of controlling a computer comprises periodically determining the total value of at least one activity metric of the controlled computer. The contribution(s) to the said total value(s) of one or more predetermined activities are determined. In one embodiment, the said contribution(s) are subtracted from the said total value(s) to provide respective net value(s). The net values are compared with respective preset values and the power state of the computer is controlled in dependence on the comparison. The one or more predetermined activities may be identified using a predetermined data set. In another embodiment the net value of at least one activity metric of the monitored computer is a net value excluding contributions to the said value(s) from the said one or more predetermined activities identified from the said data set.
Abstract:
A method is used in tracking use of interface and online assistance. A first set of a user's user interface activity is tracked. The user's online assistance activity subsequent to the user's user interface activity is tracked. A second set of the user's user interface activity is tracked. The second set occurs subsequent to the user's online assistance activity. A description of the first and second sets of the user's user interface activity and the user's online assistance activity are recorded together.