Optimizing Quantum Computer Simulations With Data Compression & GPU Acceleration
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Typ
Examensarbete på kandidatnivå
Bachelor Thesis
Bachelor Thesis
Program
Publicerad
2022
Författare
Ljung, Erik
Petrov, Darko
Bråberg, Felix
Forssén, Björn
Ringmar, Beata
Hedlund, Jonas
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
Simulating quantum computers involves high memory usage and often long execution
times. For that reason the purpose of this project was to analyze whether data
compression and GPU acceleration can be used to run simulations with more qubits
than previously allowed. Ultimately this project sheds some light on how GPU acceleration
and data compression algorithms, ZFP and FPZIP, impact the amount
of qubits that are able to be simulated. The simulator tested in this project was
a modified version of the Quantum Exact Simulation Toolkit (QuEST). From the
results of this project it was found that data compression shows good potential in
decreasing the total memory usage per qubit size. However, the use of data compression
negatively impacted the execution time, but by using GPU acceleration the
impact was reduced.