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Prof. Dr. M. Jarke
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Prof. Dr. M. Jarke
RWTH Aachen
Informatik 5
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Accelerating Graph Embedding using GPUs and Distributed Computing

Thesis type
  • Bachelor
  • Master
Status Running
Supervisor(s)
Advisor(s)

Lately several methods for embedding graphs nodes into a vector space have been proposed. These embeddings can then used to train other machine learning models. Learning these embeddings is typically done using CPUs. In this thesis the student would look into the use of other hardware, like GPUs and distributed computation options to speed up the learning process. The challenge is that algorithms working on graphs have typically a bad memory locality. Hence, existing algorithms might need profound modification in order to use them on GPUs or in a distributed fashion.

Prerequisites

The student need knowledge of algorithms and data structures. Experience programming GPUs is beneficial.

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