TY - JOUR
T1 - Highly-Parallel FPGA Accelerator for Simulated Quantum Annealing
AU - Waidyasooriya, Hasitha Muthumala
AU - Hariyama, Masanori
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2021
Y1 - 2021
N2 - Quantum annealing (QA) is a method to find the global optimum of a combinatorial optimization problem by using quantum fluctuations. Quantum annealers such as D-wave are efficient to solve small problems with less than 2048 variables. Simulated quantum annealing on digital computers allows us to solve large real-world problems. However, the processing time increases exponentially with the number of variables. This article proposes a highly-parallel accelerator for simulated quantum annealing exploiting spatial and temporal parallelism. The accelerator is implemented using 'open computing language (OpenCL)' on FPGA. For 8,192 spin models, we achieve 145 times speed using 32 Trotters in one FPGA and 290 times speed-up using 64 Trotters in two FPGAs, compared to single-core CPU implementation.
AB - Quantum annealing (QA) is a method to find the global optimum of a combinatorial optimization problem by using quantum fluctuations. Quantum annealers such as D-wave are efficient to solve small problems with less than 2048 variables. Simulated quantum annealing on digital computers allows us to solve large real-world problems. However, the processing time increases exponentially with the number of variables. This article proposes a highly-parallel accelerator for simulated quantum annealing exploiting spatial and temporal parallelism. The accelerator is implemented using 'open computing language (OpenCL)' on FPGA. For 8,192 spin models, we achieve 145 times speed using 32 Trotters in one FPGA and 290 times speed-up using 64 Trotters in two FPGAs, compared to single-core CPU implementation.
KW - high performance computing
KW - multi-FPGA acceleration
KW - OpenCL for FPGA
KW - optimization problems
KW - Simulated quantum annealing
UR - http://www.scopus.com/inward/record.url?scp=85075933888&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85075933888&partnerID=8YFLogxK
U2 - 10.1109/TETC.2019.2957177
DO - 10.1109/TETC.2019.2957177
M3 - Article
AN - SCOPUS:85075933888
SN - 2168-6750
VL - 9
SP - 2019
EP - 2029
JO - IEEE Transactions on Emerging Topics in Computing
JF - IEEE Transactions on Emerging Topics in Computing
IS - 4
ER -