Software systems and methods for advanced output-affecting linear pathways
View Patent ↗Unlike conventional or otherwise known decomposition methods like standard functional decomposition, time-affecting linear pathway (TALP) decomposition, or output-affecting linear pathways (OALPs) from the decomposition of TALPs, advanced output-affecting linear pathway (A-OALP) decomposition from algorithms separate the output variables of each execution pathway such that there is only one output variable per A-OALP, converting an algorithm into a set of process groups. A-OALPs extend parallelization by combining task-like parallelism with dynamic loop parallelism. The lightweight nature of A-OALPs allows for persistent thread and code management.
1 . A method for optimization of software or one or more algorithms, comprising:
receiving the software or the one or more algorithms, from an operator;
decomposing the software or the one or more algorithms into one or more executable and analyzable advanced output-affecting linear pathways (A-OALPs), wherein each of the one or more A-OALPs includes runtime information generation for one or more instances;
executing the one or more A-OALPs;
receiving one or more input variable attribute values in a source values table;
comparing the one or more input variable attribute values that correspond to a pathway selection entry in an A-OALP selection table, wherein the A-OALP selection table uses the one or more input variable attribute values;
selecting at least one A-OALP that corresponds to the pathway selection;
determining which of the one or more input variable attribute values vary a processing time of the selected at least one A-OALP;
determining which of the one or more input variable attribute values vary memory allocation of the selected at least one A-OALP;
determining a maximum number of processing elements usable by the selected at least one A-OALP for a current one or more input variable attribute values;
executing in parallel multiple A-OALPs on multiple separate servers while concurrently executing in parallel multiple instances of each of the multiple A-OALPs on multiple separate processing elements of a server; and
limiting A-OALP cross-communication to the multiple separate processing elements on the server and eliminating a need for the A-OALP cross-communication between the multiple separate servers.
2 . The method of claim 1 , further comprising automatically determining ranges of the one or more input variable attribute values needed to satisfy existing non-loop control conditional statements.
3 . The method of claim 1 , further comprising automatically determining ranges of the one or more input variable attribute values needed to satisfy existing synthesized non-loop control conditional statements.
4 . The method of claim 1 , further comprising automatically synthesizing false non-loop control conditional statements.
5 . The method of claim 1 , further comprising automatically using one or more pass-by-reference address values as variables for the A-OALP selection table.
6 . The method of claim 1 , further comprising automatically converting one or more indirect variables to one or more associated input variables for use with the selection of the at least one A-OALP.
7 . The method of claim 1 , further comprising automatically combining task-like parallelization with dynamic loop unrolling parallelization.
8 . The method of claim 1 , further comprising performing automatic runtime integration of one or more operator optimization goals and a number of the multiple separate processing elements used by multiple parallel instances of an A-OALP.
9 . The method of claim 1 , further comprising pre-loading one or more A-OALPs onto multiple threads across the multiple separate processing elements and associating multiple instances of an A-OALP with individual processing elements, thereby allowing for parallel A-OALP instance selection in a persistent thread and code management model.
10 . The method of claim 1 , further comprising automatically selecting:
one or more un-pooled threads;
one or more non-persistent threads;
a non-persistent thread pool with the one or more non-persistent threads;
a persistent thread pool with the one or more non-persistent threads; and/or
the persistent thread pool with one or more persistent threads.
11 . The method of claim 1 , further comprising extending a persistent thread and code management model to include processor socket usage.
12 . A system for optimization of software or one or more algorithms, comprising:
a memory; and
a processor operatively coupled with the memory, wherein the processor is configured to execute a program code to:
receive the software or the one or more algorithms, from an operator;
decompose the software or the one or more algorithms into one or more executable and analyzable advanced output-affecting linear pathways (A-OALPs), wherein each of the one or more A-OALPs includes runtime information generation for one or more instances;
execute the one or more A-OALPs;
receive one or more input variable attribute values in a source values table;
compare the one or more input variable attribute values that correspond to a pathway selection entry in an A-OALP selection table, wherein the A-OALP selection table uses the one or more input variable attribute values;
select at least one A-OALP that corresponds to the pathway selection;
determine which of the one or more input variable attribute values vary a processing time of the selected at least one A-OALP;
determine which of the one or more input variable attribute values vary memory allocation of the selected at least one A-OALP;
determine a maximum number of processing elements usable by the selected at least one A-OALP for a current one or more input variable attribute values;
execute in parallel multiple A-OALPs on multiple separate servers while concurrently executing in parallel multiple instances of each of the multiple A-OALPs on multiple separate processing elements of a server; and
limit A-OALP cross-communication to the multiple separate processing elements on the server and eliminating a need for the A-OALP cross-communication between the multiple separate servers.
13 . The system of claim 12 , wherein the processor is further configured to execute the program code to: automatically determine ranges of the one or more input variable attribute values needed to satisfy existing non-loop control conditional statements.
14 . The system of claim 12 , wherein the processor is further configured to execute the program code to: automatically determine ranges of the one or more input variable attribute values needed to satisfy existing synthesized non-loop control conditional statements.
15 . The system of claim 12 , wherein the processor is further configured to execute the program code to: automatically synthesize false non-loop control conditional statements.
16 . The system of claim 12 , wherein the processor is further configured to execute the program code to: automatically use one or more pass-by-reference address values as variables for the A-OALP selection table.
17 . The system of claim 12 , wherein the processor is further configured to execute the program code to: automatically convert one or more indirect variables to one or more associated input variables for use with the selection of the at least one A-OALP.
18 . The system of claim 12 , wherein the processor is further configured to execute the program code to: automatically combine task-like parallelization with dynamic loop unrolling parallelization.
19 . The system of claim 12 , wherein the processor is further configured to execute the program code to: perform automatic runtime integration of one or more operator optimization goals and a number of the multiple separate processing elements used by multiple parallel instances of an A-OALP.
20 . The system of claim 12 , wherein the processor is further configured to execute the program code to: pre-load one or more A-OALPs onto multiple threads across the multiple separate processing elements and associate multiple instances of an A-OALP with individual processing elements, thereby allowing for parallel A-OALP instance selection in a persistent thread and code management model.
21 . The system of claim 12 , wherein the processor is further configured to execute the program code to select:
one or more un-pooled threads;
one or more non-persistent threads;
a non-persistent thread pool with the one or more non-persistent threads;
a persistent thread pool with the one or more non-persistent threads; and/or
the persistent thread pool with one or more persistent threads.
22 . The system of claim 12 , wherein the processor is further configured to execute the program code to: extend a persistent thread and code management model to include processor socket usage.