Copyright (c) 1982, 1993
The Regents of the University of California. All rights reserved.
%sccs.include.redist.man%
@(#)profiling.me 8.1 (Berkeley) 06/08/93
.sh 1 "Types of Profiling" .pp There are several different uses for program profiles, and each may require different information from the profiles, or different presentation of the information. We distinguish two broad categories of profiles: those that present counts of statement or routine invocations, and those that display timing information about statements or routines. Counts are typically presented in tabular form, often in parallel with a listing of the source code. Timing information could be similarly presented; but more than one measure of time might be associated with each statement or routine. For example, in the framework used by gprof each profiled segment would display two times: one for the time used by the segment itself, and another for the time inherited from code segments it invokes. .pp Execution counts are used in many different contexts. The exact number of times a routine or statement is activated can be used to determine if an algorithm is performing as expected. Cursory inspection of such counters may show algorithms whose complexity is unsuited to the task at hand. Careful interpretation of counters can often suggest improvements to acceptable algorithms. Precise examination can uncover subtle errors in an algorithm. At this level, profiling counters are similar to debugging statements whose purpose is to show the number of times a piece of code is executed. Another view of such counters is as boolean values. One may be interested that a portion of code has executed at all, for exhaustive testing, or to check that one implementation of an abstraction completely replaces a previous one. .pp Execution counts are not necessarily proportional to the amount of time required to execute the routine or statement. Further, the execution time of a routine will not be the same for all calls on the routine. The criteria for establishing execution time must be decided. If a routine implements an abstraction by invoking other abstractions, the time spent in the routine will not accurately reflect the time required by the abstraction it implements. Similarly, if an abstraction is implemented by several routines the time required by the abstraction will be distributed across those routines. .pp Given the execution time of individual routines, gprof accounts to each routine the time spent for it by the routines it invokes. This accounting is done by assembling a call graph with nodes that are the routines of the program and directed arcs that represent calls from call sites to routines. We distinguish among three different call graphs for a program. The complete call graph incorporates all routines and all potential arcs, including arcs that represent calls to functional parameters or functional variables. This graph contains the other two graphs as subgraphs. The static call graph includes all routines and all possible arcs that are not calls to functional parameters or variables. The dynamic call graph includes only those routines and arcs traversed by the profiled execution of the program. This graph need not include all routines, nor need it include all potential arcs between the routines it covers. It may, however, include arcs to functional parameters or variables that the static call graph may omit. The static call graph can be determined from the (static) program text. The dynamic call graph is determined only by profiling an execution of the program. The complete call graph for a monolithic program could be determined by data flow analysis techniques. The complete call graph for programs that change during execution, by modifying themselves or dynamically loading or overlaying code, may never be determinable. Both the static call graph and the dynamic call graph are used by gprof, but it does not search for the complete call graph.
The Regents of the University of California. All rights reserved.
%sccs.include.redist.man%
@(#)profiling.me 8.1 (Berkeley) 06/08/93
.sh 1 "Types of Profiling" .pp There are several different uses for program profiles, and each may require different information from the profiles, or different presentation of the information. We distinguish two broad categories of profiles: those that present counts of statement or routine invocations, and those that display timing information about statements or routines. Counts are typically presented in tabular form, often in parallel with a listing of the source code. Timing information could be similarly presented; but more than one measure of time might be associated with each statement or routine. For example, in the framework used by gprof each profiled segment would display two times: one for the time used by the segment itself, and another for the time inherited from code segments it invokes. .pp Execution counts are used in many different contexts. The exact number of times a routine or statement is activated can be used to determine if an algorithm is performing as expected. Cursory inspection of such counters may show algorithms whose complexity is unsuited to the task at hand. Careful interpretation of counters can often suggest improvements to acceptable algorithms. Precise examination can uncover subtle errors in an algorithm. At this level, profiling counters are similar to debugging statements whose purpose is to show the number of times a piece of code is executed. Another view of such counters is as boolean values. One may be interested that a portion of code has executed at all, for exhaustive testing, or to check that one implementation of an abstraction completely replaces a previous one. .pp Execution counts are not necessarily proportional to the amount of time required to execute the routine or statement. Further, the execution time of a routine will not be the same for all calls on the routine. The criteria for establishing execution time must be decided. If a routine implements an abstraction by invoking other abstractions, the time spent in the routine will not accurately reflect the time required by the abstraction it implements. Similarly, if an abstraction is implemented by several routines the time required by the abstraction will be distributed across those routines. .pp Given the execution time of individual routines, gprof accounts to each routine the time spent for it by the routines it invokes. This accounting is done by assembling a call graph with nodes that are the routines of the program and directed arcs that represent calls from call sites to routines. We distinguish among three different call graphs for a program. The complete call graph incorporates all routines and all potential arcs, including arcs that represent calls to functional parameters or functional variables. This graph contains the other two graphs as subgraphs. The static call graph includes all routines and all possible arcs that are not calls to functional parameters or variables. The dynamic call graph includes only those routines and arcs traversed by the profiled execution of the program. This graph need not include all routines, nor need it include all potential arcs between the routines it covers. It may, however, include arcs to functional parameters or variables that the static call graph may omit. The static call graph can be determined from the (static) program text. The dynamic call graph is determined only by profiling an execution of the program. The complete call graph for a monolithic program could be determined by data flow analysis techniques. The complete call graph for programs that change during execution, by modifying themselves or dynamically loading or overlaying code, may never be determinable. Both the static call graph and the dynamic call graph are used by gprof, but it does not search for the complete call graph.