Abstract: Mapping tasks to physical processors in parallel computing system may include partitioning tasks in the parallel computing system into groups of tasks, the tasks being grouped according to their communication characteristics (e.g., pattern and frequency); mapping, by a processor, the groups of tasks to groups of physical processors, respectively; and fine tuning, by the processor, the mapping within each of the groups.

Abstract: A method for increasing performance of an operation on a distributed memory machine is provided. Asynchronous parallel steps in the operation are transformed into synchronous parallel steps. The synchronous parallel steps of the operation are rearranged to generate an altered operation that schedules memory accesses for increasing locality of reference. The altered operation that schedules memory accesses for increasing locality of reference is mapped onto the distributed memory machine. Then, the altered operation is executed on the distributed memory machine to simulate local memory accesses with virtual threads to check cache performance within each node of the distributed memory machine.

Abstract: Mapping tasks to physical processors in parallel computing system may include partitioning tasks in the parallel computing system into groups of tasks, the tasks being grouped according to their communication characteristics (e.g., pattern and frequency); mapping, by a processor, the groups of tasks to groups of physical processors, respectively; and fine tuning, by the processor, the mapping within each of the groups.

Abstract: A target application is automatically tuned. A list of solutions for identified performance bottlenecks in a target application is retrieved from a storage device. A plurality of modules is executed to compute specific parameters for solutions contained in the list of solutions. A list of modification commands associated with specific parameters computed by the plurality of modules is generated. The list of modification commands associated with the specific parameters is appended to a command sequence list. The list of modification commands is implemented in the target application. Specific source code regions corresponding to the identified performance bottlenecks in the target application are automatically tuned using the implemented list of modification commands. Then, the tuned target application is stored in the storage device.

Abstract: Mapping tasks to physical processors in parallel computing system may include partitioning tasks in the parallel computing system into groups of tasks, the tasks being grouped according to their communication characteristics (e.g., pattern and frequency); mapping, by a processor, the groups of tasks to groups of physical processors, respectively; and fine tuning, by the processor, the mapping within each of the groups.

Abstract: A method for increasing performance of an operation on a distributed memory machine is provided. Asynchronous parallel steps in the operation are transformed into synchronous parallel steps. The synchronous parallel steps of the operation are rearranged to generate an altered operation that schedules memory accesses for increasing locality of reference. The altered operation that schedules memory accesses for increasing locality of reference is mapped onto the distributed memory machine. Then, the altered operation is executed on the distributed memory machine to simulate local memory accesses with virtual threads to check cache performance within each node of the distributed memory machine.

Abstract: A target application is automatically tuned. A list of solutions for identified performance bottlenecks in a target application is retrieved from a storage device. A plurality of modules is executed to compute specific parameters for solutions contained in the list of solutions. A list of modification commands associated with specific parameters computed by the plurality of modules is generated. The list of modification commands associated with the specific parameters is appended to a command sequence list. The list of modification commands is implemented in the target application. Specific source code regions corresponding to the identified performance bottlenecks in the target application are automatically tuned using the implemented list of modification commands. Then, the tuned target application is stored in the storage device.