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Scaling the semidefinite program solver SDPB

Landry, Walter and Simmons-Duffin, David (2019) Scaling the semidefinite program solver SDPB. . (Unpublished)

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We present enhancements to SDPB, an open source, parallelized, arbitrary precision semidefinite program solver designed for the conformal bootstrap. The main enhancement is significantly improved performance and scalability using the Elemental library and MPI. The result is a new version of SDPB that runs on multiple nodes with hundreds of cores with excellent scaling, making it practical to solve larger problems. We demonstrate performance on a moderate-size problem in the 3d Ising CFT and a much larger problem in the O(2) Model.

Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription Paper
Simmons-Duffin, David0000-0002-2937-9515
Additional Information:We thank Ning Bao, Connor Behan, Shai Chester, Rajeev Erramilli, Tom Hartman, Luca Iliesiu, Filip Kos, Junyu Liu, Petr Kravchuk, David Poland, Ning Su, and Alessandro Vichi for discussions. We also thank the participants in the Simons Bootstrap Collaboration kickoff meeting at Yale in 2016 and the bootstrap “hackathon” at Caltech in summer 2018. DSD and WL are supported by Simons Foundation grant 488657 (Simons Collaboration on the Nonperturbative Bootstrap). DSD also acknowledges support from a Sloan Research Fellowship, and a DOE Early Career Award under grant No. DE-SC0019085.
Group:Walter Burke Institute for Theoretical Physics
Funding AgencyGrant Number
Simons Foundation488657
Alfred P. Sloan FoundationUNSPECIFIED
Department of Energy (DOE)DE-SC0019085
Record Number:CaltechAUTHORS:20201118-081637808
Persistent URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:106719
Deposited By: Tony Diaz
Deposited On:18 Nov 2020 18:21
Last Modified:18 Nov 2020 18:21

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