Abstract:
PROBLEM TO BE SOLVED: To accurately perform the performance planning of a transaction base. SOLUTION: A model 110 of infrastructure is created using data 123 supplied by an existing managing tool 120 designed so as to monitor the infrastructure, and constituted automatically. Using the automatically constituted model 103, the performance of the infrastructure is simulated with the present constitution or the other potential constitution. A result from the simulation is compared with measured data to automatically perform the validity check and calibration. COPYRIGHT: (C)2006,JPO&NCIPI
Abstract:
PROBLEM TO BE SOLVED: To accurately execute performance planning for a computer infrastructure. SOLUTION: The transaction-based performance model with the automatic configuration comprises the steps of generating a model 110 by using a data 123 which is provided by a current management tool 120 designed for monitoring the computer infrastructure, automatically constructing the infrastructure, and simulating a performance for each of the infrastructures for an current computer configuration and the other available computer configurations by using the model 103 being automatically configured. COPYRIGHT: (C)2006,JPO&NCIPI
Abstract:
The present invention extends to methods, systems, and computer program products for protected mode scheduling of operations. Protected mode (e.g., user mode) scheduling can facilitate the development of programming frameworks that better reflect the requirements of the workloads through the use of workload-specific execution abstractions. In addition, the ability to define scheduling policies tuned to the characteristics of the hardware resources available and the workload requirements has the potential of better system scaling characteristics. Further, protected mode scheduling decentralizes the scheduling responsibility by moving significant portions of scheduling functionality from supervisor mode (e.g., kernel mode) to an application.
Abstract:
A prescribed system architecture is recommended to an entity that desires to implement a system supporting distributed applications. A performance scenario is created based on anticipated usage, devices employed by servers running the distributed applications, and topology of locations using the servers. An optimized scenario may be provided by determining device optimization, different use load, and if possible consolidation of distributed applications on servers.
Abstract:
Preconditioning for stochastic simulation of computer system performance is described. In an embodiment, methods taught herein include preconditioning a performance scenario that is simulated as part of a software deployment. The performance scenario specifies devices included as part of a hardware configuration supporting the software. The performance scenario can be modified based, at least in part, on the result of the preconditioning. Other methods taught herein include two complementary techniques for preconditioning performance scenarios, referred to as pseudo-simulation and workload aggregation.
Abstract:
The present invention extends to methods, systems, and computer program products for protected mode scheduling of operations. Protected mode (e.g., user mode) scheduling can facilitate the development of programming frameworks that better reflect the requirements of the workloads through the use of workload-specific execution abstractions. In addition, the ability to define scheduling policies tuned to the characteristics of the hardware resources available and the workload requirements has the potential of better system scaling characteristics. Further, protected mode scheduling decentralizes the scheduling responsibility by moving significant portions of scheduling functionality from supervisor mode (e.g., kernel mode) to an application.
Abstract:
The present invention extends to methods, systems, and computer program products for protected mode scheduling of operations. Protected mode (e.g., user mode) scheduling can facilitate the development of programming frameworks that better reflect the requirements of the workloads through the use of workload-specific execution abstractions. In addition, the ability to define scheduling policies tuned to the characteristics of the hardware resources available and the workload requirements has the potential of better system scaling characteristics. Further, protected mode scheduling decentralizes the scheduling responsibility by moving significant portions of scheduling functionality from supervisor mode (e.g., kernel mode) to an application.
Abstract:
Scheduling system resources. A system resource scheduling policy for scheduling operations within a workload is accessed. The policy is specified on a workload basis such that the policy is specific to the workload. System resources are reserved for the workload as specified by the policy. Reservations may be hierarchical in nature where workloads are also hierarchically arranged. Further, dispatching mechanisms for dispatching workloads to system resources may be implemented independent from policies. Feedback regarding system resource use may be used to determine policy selection for controlling dispatch mechanisms.
Abstract:
In an implementation, a system includes a simulation engine that is executable to simulate actions performed by a plurality of devices in a distributed system. The system also includes a plurality of pluggable device models that are accessible by the simulation engine via an interface. Each of the device models represents one of the devices and is configured to map a cost of performing at least one of the actions to an action latency by the corresponding device.