Master Thesis - Distributed memory parallelization of CubeLib library using MPI

 Cube, which is used as performance report explorer for Scalasca and Score-P, is a generic tool for displaying a multi-dimensional performance space consisting of following dimensions: performance metric, call path, and system resources. Each dimension can be represented as a tree, where the non-leaf nodes can be collapsed or expanded to achieve the desired level of granularity.

CubeLib, as a part of the Cube framework, is a general purpose library, which is used in the cube_server tool to access and process the Cube profile data. Currently the cube_server tool and the CubeGUI are using shared memory parallelization approach within the single compute node.
The goal of the master thesis is to develop a prototype of the CubeLib using distributed memory parallelization approach, incorporate it in the cube_server tool and conduct a performance analysis.

Your tasks will include:

• Development of the prototype of parallelization algorithm
  
• Its incorporation in the CubeLib and the cube_server tool
  
• Conducting performance measurements and comparisons using Score-p and other tools
  
• Investigation of theoretical maximal speedup and possible limitations of the algorithm

Your Profile:

• Bachelor’s degree (or equivalent) in computer science, mathematics or related field
  
• Advanced skills in parallel programming using C++
  
• Solid knowledge of the MPI
  
• Interest in the High Performance Computing field
  
• Ability to communicate with colleagues and discuss various problems in the field
  
• Well-structured and systematic research approach
  

Please feel free to apply for the position even if you do not have all the required skills and
knowledge. We may be able to teach you missing skills during your training.

Our Offer:

We work on the very latest issues that impact our society and are offering you the chance to actively help in shaping the change! We support you in your work with:

• An interesting and socially relevant topic for your thesis with future-oriented themes
  
• Ideal conditions for gaining practical experience alongside your studies
  
• Excellent technical equipment and the newest technology
  
• Qualified support through your scientific colleagues
  
• The chance to independently prepare and work on your tasks
  
• Flexible work (location) arrangements, e.g. remote work
  
• A large research campus with green spaces, offering the best possible means for networking with colleagues and pursuing sports alongside work
  

The position is for a fixed term of 6 months.

We welcome applications from people with diverse backgrounds, e.g. in terms of age, gender, disability, sexual orientation / identity, and social, ethnic and religious origin. A diverse and inclusive working environment with equal opportunities in which everyone can realize their potential is important to us.

We look forward to receiving your application. The job will be advertised until the position has been successfully filled. You should therefore submit your application as soon as possible.

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