TY - GEN
T1 - Parallelising matrix operations on clusters for an optimal control-based quantum compiler
AU - Gradl, T.
AU - Spörl, A.
AU - Huckle, T.
AU - Glaser, S. J.
AU - Schulte-Herbrüggen, T.
PY - 2006
Y1 - 2006
N2 - Quantum control plays a key role in quantum technology, e.g. for steering quantum hardware systems, spectrometers or superconducting solid-state devices. In terms of computation, quantum systems provide a unique potential for coherent parallelisation that may exponentially speed up algorithms as in Shor's prime factorisation. Translating quantum software into a sequence of classical controls steering the quantum hardware, viz. the quantum compilation task, lends itself to be tackled by optimal control. It is computationally demanding since the classical resources needed grow exponentially with the size of the quantum system. Here we show concepts of parallelisation tailored to run on high-end computer clusters speeding up matrix multiplication, exponentials, and trace evaluations used in numerical quantum control. In systems of 10 spin qubits, the time gain is beyond a factor of 500 on a 128-CPU cluster as compared to standard techniques on a single CPU.
AB - Quantum control plays a key role in quantum technology, e.g. for steering quantum hardware systems, spectrometers or superconducting solid-state devices. In terms of computation, quantum systems provide a unique potential for coherent parallelisation that may exponentially speed up algorithms as in Shor's prime factorisation. Translating quantum software into a sequence of classical controls steering the quantum hardware, viz. the quantum compilation task, lends itself to be tackled by optimal control. It is computationally demanding since the classical resources needed grow exponentially with the size of the quantum system. Here we show concepts of parallelisation tailored to run on high-end computer clusters speeding up matrix multiplication, exponentials, and trace evaluations used in numerical quantum control. In systems of 10 spin qubits, the time gain is beyond a factor of 500 on a 128-CPU cluster as compared to standard techniques on a single CPU.
UR - http://www.scopus.com/inward/record.url?scp=33749985192&partnerID=8YFLogxK
U2 - 10.1007/11823285_78
DO - 10.1007/11823285_78
M3 - Conference contribution
AN - SCOPUS:33749985192
SN - 3540377832
SN - 9783540377832
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 751
EP - 762
BT - Euro-Par 2006 Parallel Processing - 12th International Euro-Par Conference, Proceedings
PB - Springer Verlag
T2 - 12th International Euro-Par Conference 2006
Y2 - 28 August 2006 through 1 September 2006
ER -