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Breaking master-slave model between host and FPGAs

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Bosch Pons, JaumeMés informació
Vidal, MiquelMés informació
Filgueras Izquierdo, AntonioMés informació
Álvarez Martínez, CarlosMés informacióMés informacióMés informació
Jiménez González, DanielMés informacióMés informacióMés informació
Martorell Bofill, XavierMés informacióMés informacióMés informació
Ayguadé Parra, EduardMés informacióMés informacióMés informació
Document typeConference lecture
Defense date2020
PublisherAssociation for Computing Machinery (ACM)
Rights accessOpen Access
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder
ProjectEPEEC - European joint Effort toward a Highly Productive Programming Environment for Heterogeneous Exascale Computing (EPEEC) (EC-H2020-801051)
COMPUTACION DE ALTAS PRESTACIONES VII (MINECO-TIN2015-65316-P)
Abstract
This paper proposes to enhance current task-based programming models by breaking their current master-slave approach between the main processor and its hardware accelerators. As a proof-of-concept, it presents an extension of the OmpSs@FPGA toolchain that allows the tasks offloaded into the FPGA to create and synchronize nested tasks on their own without involving the host. Those FPGA spawned tasks may target the host to execute code not suitable for the FPGA, like system calls or I/O operations; or target other kernel accelerators inside the same FPGA. In addition to the programmability benefits of this new feature, the proposed system presents significant performance improvements and a better productivity over the classical master-slave approach.
CitationBosch, J. [et al.]. Breaking master-slave model between host and FPGAs. A: ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. "PPoPP'20: Proceedings of the 2020 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming: San Diego, CA, USA: 22-26 February 2020". New York: Association for Computing Machinery (ACM), 2020, p. 419-420. ISBN 978-1-4503-6818-6. DOI 10.1145/3332466.3374545. 
URIhttp://hdl.handle.net/2117/329410
DOI10.1145/3332466.3374545
ISBN978-1-4503-6818-6
Publisher versionhttps://dl.acm.org/doi/10.1145/3332466.3374545
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