Abstract: A method, system and computer program product for generating sets of training programs for machine learning models. Fixed values of one or more workload metrics are received from a user, where the workload metrics correspond to low-level program features which define particular low-level application behavior. A profile using the fixed values of the workload metrics is then created. A suite of synthetic applications is generated using the created profile to form a set of training programs which target particular aspects of program behavior. A machine learning model is then trained using the set of training programs. Since the generated synthetic applications provide a broader coverage of the program state-space, the formed set of training programs more accurately targets performance behavior thereby improving the prediction accuracy of the machine learning based predictive models.

Abstract: A method and apparatus for performing memory prefetching includes determining whether to initiate prefetching. Upon a determination to initiate prefetching, a first memory row is determined as a suitable prefetch candidate, and it is determined whether a particular set of one or more cachelines of the first memory row is to be prefetched.

Abstract: A data processing system includes a memory that includes a first memory bank and a second memory bank. The data processing system also includes a conflict detector connected to the memory and adapted to receive memory access information. The conflict detector tracks memory access statistics of the first memory bank, and determines if the first memory bank contains frequent row conflicts. The conflict detector also remaps a frequent row conflict in the first memory bank to the second memory bank. An indirection table is connected to the conflict detector and adapted to receive a memory access request, and redirects an address into a dynamically selected physical memory address in response to a remapping of the frequent row conflict to the second memory bank.

Abstract: A data processing system includes a memory that includes a first memory bank and a second memory bank. The data processing system also includes a conflict detector connected to the memory and adapted to receive memory access information. The conflict detector tracks memory access statistics of the first memory bank, and determines if the first memory bank contains frequent row conflicts. The conflict detector also remaps a frequent row conflict in the first memory bank to the second memory bank. An indirection table is connected to the conflict detector and adapted to receive a memory access request, and redirects an address into a dynamically selected physical memory address in response to a remapping of the frequent row conflict to the second memory bank.

Abstract: A method, system and computer program product for generating sets of training programs for machine learning models. Fixed values of one or more workload metrics are received from a user, where the workload metrics correspond to low-level program features which define particular low-level application behavior. A profile using the fixed values of the workload metrics is then created. A suite of synthetic applications is generated using the created profile to form a set of training programs which target particular aspects of program behavior. A machine learning model is then trained using the set of training programs. Since the generated synthetic applications provide a broader coverage of the program state-space, the formed set of training programs more accurately targets performance behavior thereby improving the prediction accuracy of the machine learning based predictive models.

Abstract: A method and apparatus for performing memory prefetching includes determining whether to initiate prefetching. Upon a determination to initiate prefetching, a first memory row is determined as a suitable prefetch candidate, and it is determined whether a particular set of one or more cachelines of the first memory row is to be prefetched.