Abstract
In this work we present a comparative study of several GPU accelerated elements of a Genetic Algorithm (GA) for the synthesis of quantum circuits on the level of Electro-Magnetic (EM) pulses. The novelty in our approach is in the implementation: a) a completely GPU accelerated quantum simulator, b) GPU accelerated genetic operators and fitness evaluation and finally c) a set of GPU implemented optimizations for GPU accelerated evolutionary search optimization for the synthesis of quantum circuits. The reason for using EM pulses model for synthesis is the observation that this model requires the largest amount of elementary rotations to implement quantumlogic gates and thus provides a good measure to evaluate the efficiency of the acceleration by the GPU processor. The reason to use a GA is the advantage of pseudo evolutionary search in very large problem space such as the one defined by the Ising model where the EM realized quantum circuits are evolved. As a result of the several GPU optimizations several new circuits implementations are presented and their cost is compared to thecurrently known Ising model implementations.
Original language | English |
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Title of host publication | Proceedings - 2017 IEEE 47th International Symposium on Multiple-Valued Logic, ISMVL 2017 |
Publisher | IEEE Computer Society |
Pages | 213-218 |
Number of pages | 6 |
ISBN (Electronic) | 9781509054954 |
DOIs | |
Publication status | Published - Jun 30 2017 |
Event | 47th IEEE International Symposium on Multiple-Valued Logic, ISMVL 2017 - Novi Sad, Serbia Duration: May 22 2017 → May 24 2017 |
Conference
Conference | 47th IEEE International Symposium on Multiple-Valued Logic, ISMVL 2017 |
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Country | Serbia |
City | Novi Sad |
Period | 5/22/17 → 5/24/17 |
Fingerprint
Keywords
- Evolutionary computation
- GPU
- Optimization
- Quantum Circuits
ASJC Scopus subject areas
- Computer Science(all)
- Mathematics(all)
Cite this
Study of GPU Acceleration in Genetic Algorithms for Quantum Circuit Synthesis. / Lukac, Martin; Krylov, Georgiy.
Proceedings - 2017 IEEE 47th International Symposium on Multiple-Valued Logic, ISMVL 2017. IEEE Computer Society, 2017. p. 213-218 7964993.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Study of GPU Acceleration in Genetic Algorithms for Quantum Circuit Synthesis
AU - Lukac, Martin
AU - Krylov, Georgiy
PY - 2017/6/30
Y1 - 2017/6/30
N2 - In this work we present a comparative study of several GPU accelerated elements of a Genetic Algorithm (GA) for the synthesis of quantum circuits on the level of Electro-Magnetic (EM) pulses. The novelty in our approach is in the implementation: a) a completely GPU accelerated quantum simulator, b) GPU accelerated genetic operators and fitness evaluation and finally c) a set of GPU implemented optimizations for GPU accelerated evolutionary search optimization for the synthesis of quantum circuits. The reason for using EM pulses model for synthesis is the observation that this model requires the largest amount of elementary rotations to implement quantumlogic gates and thus provides a good measure to evaluate the efficiency of the acceleration by the GPU processor. The reason to use a GA is the advantage of pseudo evolutionary search in very large problem space such as the one defined by the Ising model where the EM realized quantum circuits are evolved. As a result of the several GPU optimizations several new circuits implementations are presented and their cost is compared to thecurrently known Ising model implementations.
AB - In this work we present a comparative study of several GPU accelerated elements of a Genetic Algorithm (GA) for the synthesis of quantum circuits on the level of Electro-Magnetic (EM) pulses. The novelty in our approach is in the implementation: a) a completely GPU accelerated quantum simulator, b) GPU accelerated genetic operators and fitness evaluation and finally c) a set of GPU implemented optimizations for GPU accelerated evolutionary search optimization for the synthesis of quantum circuits. The reason for using EM pulses model for synthesis is the observation that this model requires the largest amount of elementary rotations to implement quantumlogic gates and thus provides a good measure to evaluate the efficiency of the acceleration by the GPU processor. The reason to use a GA is the advantage of pseudo evolutionary search in very large problem space such as the one defined by the Ising model where the EM realized quantum circuits are evolved. As a result of the several GPU optimizations several new circuits implementations are presented and their cost is compared to thecurrently known Ising model implementations.
KW - Evolutionary computation
KW - GPU
KW - Optimization
KW - Quantum Circuits
UR - http://www.scopus.com/inward/record.url?scp=85026787129&partnerID=8YFLogxK
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U2 - 10.1109/ISMVL.2017.24
DO - 10.1109/ISMVL.2017.24
M3 - Conference contribution
AN - SCOPUS:85026787129
SP - 213
EP - 218
BT - Proceedings - 2017 IEEE 47th International Symposium on Multiple-Valued Logic, ISMVL 2017
PB - IEEE Computer Society
ER -