Abstract: A block frequency of a block in an irreducible loop in computer code is statically determined. The statically determining includes splitting an incoming block mass among multiple loop headers of the irreducible loop to provide an initial mass for the block. A bottom-up traversal and a top-down traversal of a plurality of loops of the computer code including the irreducible loop are iteratively performed to update a mass of the block. The iteratively performing commences with propagating the initial mass of the block to one or more blocks of one or more loops of the plurality of loops and continues with propagating and updating masses of select blocks of the plurality of loops until a predefined point is reached providing a resulting mass for the block. The block frequency of the block is determined using the resulting mass and is to be used in processing associated with the computer code.

Abstract: A block frequency of a block in an irreducible loop in computer code is statically determined. The statically determining includes splitting an incoming block mass among multiple loop headers of the irreducible loop to provide an initial mass for the block. A bottom-up traversal and a top-down traversal of a plurality of loops of the computer code including the irreducible loop are iteratively performed to update a mass of the block. The iteratively performing commences with propagating the initial mass of the block to one or more blocks of one or more loops of the plurality of loops and continues with propagating and updating masses of select blocks of the plurality of loops until a predefined point is reached providing a resulting mass for the block. The block frequency of the block is determined using the resulting mass and is to be used in processing associated with the computer code.

Abstract: A static safety analysis for control-flow linearization receives a control flow graph (CFG) and an intermediate representation of a computer program, and identifies, for a given loop, all memory load instructions belonging to one side of a diamond-shape structure in the CFG. For each representation of an address of each memory load instruction identified, determining whether it is used on all other sides of the diamond-shape structure. Responsive to determining each representation of an address of each memory load instruction on the one side of the diamond-shape structure is used on all other sides of the diamond-shape structure, determining whether an immediate predecessor of a top of the diamond-shape structure for the given loop post-dominates a header of the given loop. Responsive to determining the immediate predecessor of the top of the diamond-shape structure for the given loop post-dominates the header of the given loop, affirming safety of linearization.

Abstract: A static safety analysis for control-flow linearization receives a control flow graph (CFG) and an intermediate representation of a computer program, and identifies, for a given loop, all memory load instructions belonging to one side of a diamond-shape structure in the CFG. For each representation of an address of each memory load instruction identified, determining whether it is used on all other sides of the diamond-shape structure. Responsive to determining each representation of an address of each memory load instruction on the one side of the diamond-shape structure is used on all other sides of the diamond-shape structure, determining whether an immediate predecessor of a top of the diamond-shape structure for the given loop post-dominates a header of the given loop. Responsive to determining the immediate predecessor of the top of the diamond-shape structure for the given loop post-dominates the header of the given loop, affirming safety of linearization.

Abstract: Optimizing program parameters in multithreaded programming may include: generating, for a program, a plurality of low-level metric functions, each of the low-level metric functions calculating a respective low-level metric of a plurality of low-level metrics; generating one or more high-level metric functions for one or more high-level metrics, each of the one or more high-level metric functions comprising a piecewise-rational function based on one or more of the low-level metric functions; and generate, based on the one or more high level-metric functions, one or more data parameter values and one or more hardware parameter values, one or more program parameter values for executing the program, wherein the one or more program parameter values are configured to optimize the one or more high-level metrics.

Abstract: Optimizing program parameters in multithreaded programming may include: generating, for a program, a plurality of low-level metric functions, each of the low-level metric functions calculating a respective low-level metric of a plurality of low-level metrics; generating one or more high-level metric functions for one or more high-level metrics, each of the one or more high-level metric functions comprising a piecewise-rational function based on one or more of the low-level metric functions; and generate, based on the one or more high level-metric functions, one or more data parameter values and one or more hardware parameter values, one or more program parameter values for executing the program, wherein the one or more program parameter values are configured to optimize the one or more high-level metrics.