Abstract: A method for determining parallel-processing parameters including: randomly generating first sample points each having a coordinate value representing the number of nodes to be used for running a first program and the number of processes per node to be executed in the running of the first program, calculating evaluation values of the respective first sample points based on information collected in the running, calculating a first statistics from the evaluation values; repeating the generating of the first sample points until the first statistic becomes equal to or smaller than a first threshold; and determining, based on a result of interpolation of the evaluation values of the first and the second sample points, the number of nodes and the number of processes that are recommended for running the first program.

Abstract: A method for determining parallel-processing parameters including: randomly generating first sample points each having a coordinate value representing the number of nodes to be used for running a first program and the number of processes per node to be executed in the running of the first program, calculating evaluation values of the respective first sample points based on information collected in the running, calculating a first statistics from the evaluation values; repeating the generating of the first sample points until the first statistic becomes equal to or smaller than a first threshold; and determining, based on a result of interpolation of the evaluation values of the first and the second sample points, the number of nodes and the number of processes that are recommended for running the first program.

Abstract: While a first code, in an object code generated from a source code, for a loop included in the source code or a second code in the object code is executed, a feature amount concerning the number of times that a condition of a conditional branch is true is obtained. The loop includes the conditional branch, and the conditional branch is coded in the first code. The second code is a code to perform computation of a branch destination for a case where the condition of the conditional branch is true, only for loop indices that were extracted as the aforementioned case. Then, a processor executes, based on the feature amount, the second code or a third code included in the object code. The third code is a code to write, by using a predicated instruction and into a memory, any computation result of computations of branch destinations.

Abstract: While a first code, in an object code generated from a source code, for a loop included in the source code or a second code in the object code is executed, a feature amount concerning the number of times that a condition of a conditional branch is true is obtained. The loop includes the conditional branch, and the conditional branch is coded in the first code. The second code is a code to perform computation of a branch destination for a case where the condition of the conditional branch is true, only for loop indices that were extracted as the aforementioned case. Then, a processor executes, based on the feature amount, the second code or a third code included in the object code. The third code is a code to write, by using a predicated instruction and into a memory, any computation result of computations of branch destinations.

Abstract: Computational unit area selecting units, each of which is provided in individual multiple cores, sequentially select uncomputed computational unit areas in a computational area. Computing units, each of which is provided in the individual multiple cores, perform computation for the selected computational unit areas. In addition, the computing units write computational results in a memory device which is accessible from each of the multiple cores. Computational result transmitting unit of the core performs computational result acquisition and transmission processing in a different time period with respect to each of multiple computational result transmission areas. The computational result acquisition processing is for acquiring, from the memory device, computational results related to the computational result transmission areas.

Abstract: A data processing method for sampling data from data each varying over time, each of the data being associated with each of grid points arranged in an area, the method includes: dividing the area into blocks; calculating a variation rate of each of the data associated with each of the grid points included in each of the blocks; dividing the blocks into sub-blocks in accordance with the variation rate of the blocks; calculating a variation rate of each set of the data associated with each of the grid points included in each of the sub-blocks; and determining a frequency of sampling data associated with each of the grid points for the sub-blocks of the blocks and for the rest of the blocks in accordance with the variation rate of the sub-blocks and the rest of the blocks.

Abstract: The data acquisition unit acquires data in correspondence with each dimensional axis and the time axis. The mode setting unit makes setting and clearing of a dimensionality investigation mode. In the dimensionality investigation mode, the axis-determinative variation-rate calculation unit calculates axial data variation rates. The axis determination unit determines whether or not the axial data variation rate corresponding to each axis is low. The objective-axis setting unit sets each axis as an objective axis when the axial data variation rate corresponding to the axis is determined to be high. While the dimensionality investigation mode is cleared, the recording-determinative variation-rate calculation unit calculates axial data variation rates. The recording determination unit determines, on the basis of the axial data variation rate, whether to record the acquired data. The recording unit does not record the data when the data is determined not to be recorded.

Abstract: Computational unit area selecting units, each of which is provided in individual multiple cores, sequentially select uncomputed computational unit areas in a computational area. Computing units, each of which is provided in the individual multiple cores, perform computation for the selected computational unit areas. In addition, the computing units write computational results in a memory device which is accessible from each of the multiple cores. Computational result transmitting unit of the core performs computational result acquisition and transmission processing in a different time period with respect to each of multiple computational result transmission areas. The computational result acquisition processing is for acquiring, from the memory device, computational results related to the computational result transmission areas.

Abstract: The data acquisition unit acquires data in correspondence with each dimensional axis and the time axis. The mode setting unit makes setting and clearing of a dimensionality investigation mode. In the dimensionality investigation mode, the axis-determinative variation-rate calculation unit calculates axial data variation rates. The axis determination unit determines whether or not the axial data variation rate corresponding to each axis is low. The objective-axis setting unit sets each axis as an objective axis when the axial data variation rate corresponding to the axis is determined to be high. While the dimensionality investigation mode is cleared, the recording-determinative variation-rate calculation unit calculates axial data variation rates. The recording determination unit determines, on the basis of the axial data variation rate, whether to record the acquired data. The recording unit does not record the data when the data is determined not to be recorded.

Abstract: A data processing method for sampling data from data each varying over time, each of the data being associated with each of grid points arranged in an area, the method includes: dividing the area into blocks; calculating a variation rate of each of the data associated with each of the grid points included in each of the blocks; dividing the blocks into sub-blocks in accordance with the variation rate of the blocks; calculating a variation rate of each set of the data associated with each of the grid points included in each of the sub-blocks; and determining a frequency of sampling data associated with each of the grid points for the sub-blocks of the blocks and for the rest of the blocks in accordance with the variation rate of the sub-blocks and the rest of the blocks.

Abstract: A simulation apparatus performs a plurality of simulations, each at a different time step interval, in parallel. The simulation apparatus calculates results of the simulations based on a plurality of execute objects operating at different time steps specified by a user. The simulation apparatus stores the results of the processed simulations in a shared table, and outputs the results to a visualizing apparatus. The simulation apparatus determines whether the shared table stores simulation data more accurate than processed simulation data. If the processed simulation data is more accurate, the simulation apparatus writes the simulation data to the shared table, and outputs the simulation data to the visualizing apparatus.

Abstract: The gap between upper and lower electrodes 1, 2 is measured at constant intervals of time while a contact 5 and a base 6 are pressed by the upper and lower electrodes under a constant pressure. Supply of an electric current to the upper and lower electrodes is controlled upon elapse of a predetermined interval of time after the gap has reached a maximum 18. The amount of metal melted out of a joining interface between the contact 5 and the base 6 is thus quantized to improve and stabilize the quality of joining between the contact 5 and the base 6.