Runtime call graph profilers, like gprof [16], are widely used as debugging tools to identify performance bottlenecks. However, the intrusive nature of existing call graph profilers prevents them from being used continuously on production systems. This thesis presents approf , a non-intrusive tool that is capable of reconstructing an approximate runtime call hierarchy of method calls solely from existing application logs. At its core, it determines the call hierarchy by using a model that contains only classto-method invocation relationships extracted from the headers of the application’s compiled bytecode classes, avoiding the expensive static analysis required to extract a more rigorous method-to-method invocation model. The key property ...
This thesis contributes to the field of performance analysis in High Performance Computing with new ...
A program profile attributes run-time costs to portions of a program's execution. Most profiling sys...
Calling context trees (CCTs) associate performance metrics with paths through a program's call graph...
Runtime call graph profilers, like gprof [16], are widely used as debugging tools to identify perfor...
Existing methods of for call graph profiling, such as that used by gprof, deal badly with programs ...
Identifying performance bottlenecks and their associated calling contexts is critical for tuning hig...
Call graph profiling reports measurements of resource utilization along with information about the c...
There are few runtime tools for modestly sized computing systems, with 10^3 processors, and above th...
The correlation of performance bottlenecks and their associated source code has become a cornerstone...
Applications implementing cloud services, such as HDFS, Hadoop YARN, Cassandra, and HBase, are mostl...
The majority of existing application profiling techniques ag-gregate and report performance costs by...
The majority of existing application profiling techniques ag- gregate and report performance costs b...
Applications implementing cloud services, such as HDFS, Hadoop YARN, Cassandra, and HBase, are mostl...
Abstract—Applications must scale well to make efficient use of today’s class of petascale computers,...
Calling context profiling fulfills programmers’ information needs to obtain a complete picture of a ...
This thesis contributes to the field of performance analysis in High Performance Computing with new ...
A program profile attributes run-time costs to portions of a program's execution. Most profiling sys...
Calling context trees (CCTs) associate performance metrics with paths through a program's call graph...
Runtime call graph profilers, like gprof [16], are widely used as debugging tools to identify perfor...
Existing methods of for call graph profiling, such as that used by gprof, deal badly with programs ...
Identifying performance bottlenecks and their associated calling contexts is critical for tuning hig...
Call graph profiling reports measurements of resource utilization along with information about the c...
There are few runtime tools for modestly sized computing systems, with 10^3 processors, and above th...
The correlation of performance bottlenecks and their associated source code has become a cornerstone...
Applications implementing cloud services, such as HDFS, Hadoop YARN, Cassandra, and HBase, are mostl...
The majority of existing application profiling techniques ag-gregate and report performance costs by...
The majority of existing application profiling techniques ag- gregate and report performance costs b...
Applications implementing cloud services, such as HDFS, Hadoop YARN, Cassandra, and HBase, are mostl...
Abstract—Applications must scale well to make efficient use of today’s class of petascale computers,...
Calling context profiling fulfills programmers’ information needs to obtain a complete picture of a ...
This thesis contributes to the field of performance analysis in High Performance Computing with new ...
A program profile attributes run-time costs to portions of a program's execution. Most profiling sys...
Calling context trees (CCTs) associate performance metrics with paths through a program's call graph...