International Business Machines Corporation

Yi Xuan Zhang

Qi Liang

Gui Yu Jiang

Chao Wei

Yu Sun

Data format conversion processing of an accelerator accessed by a processor of a computing environment is reduced. The processor and accelerator use different data formats, and the accelerator is configured to perform an input conversion to convert data from a processor data format to an accelerator data format prior to performing an operation using the data, and an output conversion to convert resultant data from accelerator data format back to processor data format after performing the operation. The reducing includes determining that adjoining operations of a process to run on the processor and accelerator are to be performed by the accelerator, where the adjoining operations include a source operation and destination operation. Further, the reducing includes blocking an output data format conversion of the source operation and an input data format conversion of the input data for the destination operation.

Reducing data format conversion of an accelerator

Data format conversion processing of an accelerator accessed by a processor of a computing environment is reduced. The processor and accelerator use different data formats, and the accelerator is configured to perform an input conversion to convert data from a processor data format to an accelerator data format prior to performing an operation using the data, and an output conversion to convert resultant data from accelerator data format back to processor data format after performing the operation. The reducing includes determining that adjoining operations of a process to run on the processor and accelerator are to be performed by the accelerator, where the adjoining operations include a source operation and destination operation. Further, the reducing includes identifying for removal output data format conversion of output data of the source operation for input to the destination operation, and input data format conversion of the input to the destination operation.

Techniques for profile clustering for homogenous instance analysis are described herein. An aspect includes collecting for each of a plurality of homogenous instances in a cloud computing environment, respective profiling information, the profiling information comprising counter data. Another aspect includes identifying a code unit for analysis. Another aspect includes aggregating counters corresponding to the code unit for each of the plurality of homogenous instances from the respective profiling information. Another aspect includes determining a cluster comprising a subset of the plurality of homogenous instances based on the aggregated counters.

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Zhangjiang, China

Yi Xuan Zhang