Scalable Parallel Debugging with

Dieter Kranzlmüller, Christof Klauseckerkranzlmueller@ifi.lmu.de

Access the Power of Computing Infrastructures

3rd Parallel Tools Workshop

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Facts about g-Eclipse

•integrated workbench framework to access the power of existing computing infrastructures

•European Commission (EC) funded project(from 07/2006 until 12/2008)

http://www.geclipse.eu/

•built on top of the Eclipse framework•released under Eclipse Public License (EPL)•continues as an Eclipse Technology Project

http://www.eclipse.org/geclipse/

•version 1.0 available for download

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•provides tools for grid, cloud and high performance computing

•Users•job submission, data management, …

•Operators•job and site management, …

•Developers•remote compiling and debugging, …

Functional Overview of g-Eclipse

Dieter Kranzlmüller Scalable Parallel Debugging with g-Eclipse

Debugging Parallel Programs

•parallel debugging differs from sequential debugging

- increased complexity

- amount of debugging - data

- additional anomalous - effects

•hard to find errors by relying only on textual debugging information

•program analysis tools

•do today’s tools scale with the increasing number of processors?

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Trace Viewer

•tool to visualize and analyze communication of parallel message passing programs

•parallel debugging and development activities centered around Trace Viewer

•integrated into g-Eclipse•can be used asstandalone application

•platform independent

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Extensions to Trace Viewer

•functionality can be easily extended•well defined extension points for

- Visualizations visualize traces

- Data Providers provide the visualizations with data

- Markers mark events of interest

- Actions perform actions on events

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Visualizations

logical clocks

physical clocks

statistics

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Data Providers

•prepare information collected using tracing tools during program run

•Trace Viewer includes support for

- Nondeterministic - Program Evaluator Trace - Format (NOPE)

- Open Trace Format - (OTF)

Dieter Kranzlmüller Scalable Parallel Debugging with g-Eclipse

Event Graph

•serves program understanding and error detection•graphs get complex, even for few processes

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Dieter Kranzlmüller Scalable Parallel Debugging with g-Eclipse

Scalability

•abstraction techniques are necessary•based on Actions and Markers extension points

-reorder, group or hide processes-mark interesting events

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Debugging using the Event Graph

1. apply abstraction mechanisms provided by Trace Viewer and identify events of interest

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Mark Events of Interest

•potential errors sources-accepted and expected message size mismatch-racing messages

•highlight events by MPI event or data type

Dieter Kranzlmüller Scalable Parallel Debugging with g-Eclipse

•by manually selecting the processes•automatically by criteria

Reorder, Group or Hide Processes

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Dieter Kranzlmüller Scalable Parallel Debugging with g-Eclipse

Connecting Graph and Source Code

•events on same source line can be marked•goto source action can be used to jump to source line•# of MPI function calls is shown in source editor

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Dieter Kranzlmüller Scalable Parallel Debugging with g-Eclipse

Cause Effect Marker

•selected event•events leading to the selected event

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•independent events•events depending on the current event

Dieter Kranzlmüller Scalable Parallel Debugging with g-Eclipse

•search for patterns defined using a description language-serves program understanding

-helps to detect errors and inefficient communication

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Communication Patterns

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Debugging using the Event Graph

1. apply abstraction mechanisms provided by Trace Viewer and identify events of interest

2. set breakpoints on events in the event graph using Trace Viewer

Dieter Kranzlmüller Scalable Parallel Debugging with g-Eclipse

Breakpointing

•line breakpoints are highlighted in the graph•local as well as global breakpoints can be set on events in the graph

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Debugging using the Event Graph

1. apply abstraction mechanisms provided by Trace Viewer and identify events of interest

2. set breakpoints on events in the event graph using Trace Viewer

3. launch applications remotely with debuggers attached to the individual processes using Application Launcher

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Application Launcher

•specific launcher to launch applications remotely

•support for debugging multiple processes per launch

•offers interactive consolefor the remote running application

•no need for native local debugger

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Debugging using the Event Graph

1. apply abstraction mechanisms provided by Trace Viewer and identify events of interest

2. set breakpoints on events in the event graph using Trace Viewer

3. launch applications remotely with debuggers attached to the individual processes using Application Launcher

4. use Eclipse’s standard debugging features to debug remotely running parallel applications

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The Components Combined

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Debugging using the Event Graph

1. apply abstraction mechanisms provided by Trace Viewer and identify events of interest

2. set breakpoints on events in the event graph using Trace Viewer

3. launch applications remotely with debuggers attached to the individual processes using Application Launcher

4. use Eclipse’s standard debugging features to debug remotely running parallel applications

5. rebuild the program on a remote host using the Remote Builder

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Remote Builder

•offers possibility to compile and link C/C++ Makefile applications remotely

•uses remote compiler’s output to mark errors in the source code

•no need for cross compiling or special libraries on the local side

•switch easily between different remote hosts

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Summary

•number of processors will increase even more in the future

•debugging and analysis software tools need to be-flexible-extensible-scalable

•abstraction and automation techniques supporting the developer are a basic necessity

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Dieter Kranzlmüller Scalable Parallel Debugging with g-Eclipse 27

Dieter Kranzlmüllerkranzlmueller@ifi.lmu.de

thank you for your attention