Abstract: An illustrative embodiment of a computer-implemented process for managing aliasing constraints, identifies an object to form an identified object, identifies a scope of the identified object to form an identified scope, and assigns a unique value to the identified object within the identified scope. The computer-implemented process further demarcates an entrance to the identified scope, demarcates an exit to the identified scope, optimizes the identified object using a property of the identified scope and associated aliasing information, tracks the identified object state to form tracked state information; and uses the tracked state information to update the identified object.

Abstract: An illustrative embodiment of a computer-implemented process for managing aliasing constraints, identifies an object to form an identified object, identifies a scope of the identified object to form an identified scope, and assigns a unique value to the identified object within the identified scope. The computer-implemented process further demarcates an entrance to the identified scope, demarcates an exit to the identified scope, optimizes the identified object using a property of the identified scope and associated aliasing information, tracks the identified object state to form tracked state information; and uses the tracked state information to update the identified object.

Abstract: An illustrative embodiment of a computer-implemented process for managing aliasing constraints, identifies an object to form an identified object, identifies a scope of the identified object to form an identified scope, and assigns a unique value to the identified object within the identified scope. The computer-implemented process further demarcates an entrance to the identified scope, demarcates an exit to the identified scope, optimizes the identified object using a property of the identified scope and associated aliasing information, tracks the identified object state to form tracked state information; and uses the tracked state information to update the identified object.

Abstract: Embodiments of the present invention provide a method, system and computer program product for the data splitting of recursive data structures. In one embodiment of the invention, a method for data splitting recursive data structures can be provided. The method can include identifying data objects of a recursive data structure type, such as a linked list, within source code, the recursive data structure type defining multiple different data fields. The method further can include grouping the data objects into some memory pool units, each of which can contain the same number of data objects. Each memory pool unit can be seen as an array of data objects. The method can include data splitting, which could be maximal array splitting in each different memory pool unit. Finally, the method can include three different approaches, including field padding, field padding and field splitting, to handle irregular field sizes in the data structure.

Abstract: A code region of an application is instrumented by a multi-pass profiler with first annotations for generating profile data. The application is executed with the first annotations, wherein executing the application with the first annotations generates first profile data for the code region. The multi-pass profiler identifies, from the first profile data, the code region as a delinquent code region. The multi-pass profiler determines second annotations based, at least in part, on the first profile data and the at least one of the first annotations that defines the delinquent code region. The multi-pass profiler instruments, based on the first profile data, a code sub-region of the delinquent code region with the second annotations for generating profile data. The application is executed with second annotations, wherein executing the application with the second annotations generates second profile data for the code sub-region.

Abstract: Embodiments are directed to a computer implemented method of accessing a data frame, wherein a first portion of the data frame is in a first memory block, and wherein a second portion of the data frame is in a second memory block. The method includes initiating, by a processor, an access of the data frame. The method further includes accessing, by the processor, the first portion of the data frame. The method further includes, based at least in part on a determination that the processor does not have access to the second memory block, accessing at least one default character as a replacement for accessing the second portion of the data frame.

Abstract: A computer identifies one or more pairs of scalar statements and performs a cost analysis of operations of each of the one or more pairs of scalar statements to determine both a benefit and a cost of operations. The computer determines, based, at least in part, on the cost analysis, a gain for each of the one or more pairs of scalar statements. The computer creates based, at least in part, on the gain, a sorted list of each of the one or more pairs of scalar statements and selects a first pair from the sorted list. The computer issues a query to a hash table using a statement of the first pair and selects from results received from the query, a second pair. The computer then extends, based, at least in part, on the second pair, the first pair to create a pack.

Abstract: Embodiments are directed to a method of accessing a data frame. The method includes, based at least in part on a determination that the data frame spans first and second memory blocks, and further based at least in part on a determination that the processor has access to the first and second memory blocks, accessing the data frame. The method includes, based at least in part on a determination that the data frame spans the first and second memory blocks, and based at least in part on a determination that the processor has access to the first memory block but does not have access to the second memory block, accessing a first portion of the data frame that is in the first memory block, and accessing at least one default character as a replacement for accessing a second portion of the data frame that is in the second memory block.

Abstract: A computer identifies one or more pairs of scalar statements and performs a cost analysis of operations of each of the one or more pairs of scalar statements to determine both a benefit and a cost of operations. The computer determines, based, at least in part, on the cost analysis, a gain for each of the one or more pairs of scalar statements. The computer creates based, at least in part, on the gain, a sorted list of each of the one or more pairs of scalar statements and selects a first pair from the sorted list. The computer issues a query to a hash table using a statement of the first pair and selects from results received from the query, a second pair. The computer then extends, based, at least in part, on the second pair, the first pair to create a pack.

Abstract: Embodiments are directed to a computer implemented method of accessing a data frame, wherein a first portion of the data frame is in a first memory block, and wherein a second portion of the data frame is in a second memory block. The method includes initiating, by a processor, an access of the data frame. The method further includes accessing, by the processor, the first portion of the data frame. The method further includes, based at least in part on a determination that the processor does not have access to the second memory block, accessing at least one default character as a replacement for accessing the second portion of the data frame.

Abstract: Embodiments are directed to a method of accessing a data frame. The method includes, based at least in part on a determination that the data frame spans first and second memory blocks, and further based at least in part on a determination that the processor has access to the first and second memory blocks, accessing the data frame. The method includes, based at least in part on a determination that the data frame spans the first and second memory blocks, and based at least in part on a determination that the processor has access to the first memory block but does not have access to the second memory block, accessing a first portion of the data frame that is in the first memory block, and accessing at least one default character as a replacement for accessing a second portion of the data frame that is in the second memory block.

Abstract: A computer processor collects information for a dominant data access loop and reference code patterns based on data reference pattern analysis, and for pointer aliasing and data shape based on pointer escape analysis. The computer processor selects a candidate array for data splitting wherein the candidate array is referenced by a dominant data access loop. The computer processor determines a data splitting mode by which to split the data of the candidate array, based on the reference code patterns, the pointer aliasing, and the data shape information, and splits the data into two or more split arrays. The computer processor creates a software cache that includes a portion of the data of the two or more split arrays in a transposed format, and maintains the portion of the transposed data within the software cache and consults the software cache during an access of the split arrays.

Abstract: A method for rolling back speculative threads in symmetric-multiprocessing (SMP) environments is disclosed. In one embodiment, such a method includes detecting an aborted thread at runtime and determining whether the aborted thread is an oldest aborted thread. In the event the aborted thread is the oldest aborted thread, the method sets a high-priority request for allocation to an absolute thread number associated with the oldest aborted thread. The method further detects that the high-priority request is set and, in response, clears the high-priority request and sets an allocation token to the absolute thread number associated with the oldest aborted thread, thereby allowing the oldest aborted thread to retry a work unit associated with the absolute thread number. A corresponding apparatus and computer program product are also disclosed.

Abstract: A method for rolling back speculative threads in symmetric-multiprocessing (SMP) environments is disclosed. In one embodiment, such a method includes detecting an aborted thread at runtime and determining whether the aborted thread is an oldest aborted thread. In the event the aborted thread is the oldest aborted thread, the method sets a high-priority request for allocation to an absolute thread number associated with the oldest aborted thread. The method further detects that the high-priority request is set and, in response, modifies a local allocation token of the oldest aborted thread. The modification prompts the oldest aborted thread to retry a work unit associated with its absolute thread number. The oldest aborted thread subsequently initiates the retry of a successor thread by updating the successor thread's local allocation token. A corresponding apparatus and computer program product are also disclosed.

Abstract: A computer-implemented method for creating a threaded package of computer executable instructions from software compiler generated code includes allocating, through a computer processor, the computer executable instructions into a plurality of stacks, differentiating between different types of computer executable instructions for each computer executable instruction allocated to each stack of the plurality of stacks, creating switch points for each stack of the plurality of stacks based upon the differentiating, and inserting the switch points within each stack of the plurality of stacks.

Abstract: Embodiments of the present invention provide a method, system and computer program product for the data splitting of recursive data structures. In one embodiment of the invention, a method for data splitting recursive data structures can be provided. The method can include identifying data objects of a recursive data structure type, such as a linked list, within source code, the recursive data structure type defining multiple different data fields. The method further can include grouping the data objects into some memory pool units, each of which can contain the same number of data objects. Each memory pool unit can be seen as an array of data objects. The method can include data splitting, which could be maximal array splitting in each different memory pool unit. Finally, the method can include three different approaches, including field padding, field padding and field splitting, to handle irregular field sizes in the data structure.

Abstract: A method for rolling back speculative threads in symmetric-multiprocessing (SMP) environments is disclosed. In one embodiment, such a method includes detecting an aborted thread at runtime and determining whether the aborted thread is an oldest aborted thread. In the event the aborted thread is the oldest aborted thread, the method sets a high-priority request for allocation to an absolute thread number associated with the oldest aborted thread. The method further detects that the high-priority request is set and, in response, clears the high-priority request and sets an allocation token to the absolute thread number associated with the oldest aborted thread, thereby allowing the oldest aborted thread to retry a work unit associated with the absolute thread number. A corresponding apparatus and computer program product are also disclosed.

Abstract: A computer identifies one or more pairs of scalar statements and performs a cost analysis of operations of each of the one or more pairs of scalar statements to determine both a benefit and a cost of operations. The computer determines, based, at least in part, on the cost analysis, a gain for each of the one or more pairs of scalar statements. The computer creates based, at least in part, on the gain, a sorted list of each of the one or more pairs of scalar statements and selects a first pair from the sorted list. The computer issues a query to a hash table using a statement of the first pair and selects from results received from the query, a second pair. The computer then extends, based, at least in part, on the second pair, the first pair to create a pack.

Abstract: A computer identifies one or more pairs of scalar statements and performs a cost analysis of operations of each of the one or more pairs of scalar statements to determine both a benefit and a cost of operations. The computer determines, based, at least in part, on the cost analysis, a gain for each of the one or more pairs of scalar statements. The computer creates based, at least in part, on the gain, a sorted list of each of the one or more pairs of scalar statements and selects a first pair from the sorted list. The computer issues a query to a hash table using a statement of the first pair and selects from results received from the query, a second pair. The computer then extends, based, at least in part, on the second pair, the first pair to create a pack.

Abstract: Embodiments of the present invention provide a method, system and computer program product for the data splitting of recursive data structures. In one embodiment of the invention, a method for data splitting recursive data structures can be provided. The method can include identifying data objects of a recursive data structure type, such as a linked list, within source code, the recursive data structure type defining multiple different data fields. The method further can include grouping the data objects into some memory pool units, each of which can contain the same number of data objects. Each memory pool unit can be seen as an array of data objects. The method can include data splitting, which could be maximal array splitting in each different memory pool unit. Finally, the method can include three different approaches, including field padding, field padding and field splitting, to handle irregular field sizes in the data structure.