On the Impact of Heterogeneous NoC Bandwidth Allocation in the WCET of Applications

This thesis analyzes the potential of a Flexible Bandwidth Allocation (FBA) method for networks-on-chip (NoCs), which provides heterogeneous bandwidth distribution to improve the worst-case execution time (WCET) of parallel and sequential applications in NoC-based multi- and many-core processors

NoCo: ILP-based worst-case contention estimation for mesh real-time manycores

Manycores are capable of providing the computational demands required by functionally-advanced critical applications in domains such as automotive and avionics. In manycores a network-on-chip (NoC) provides access to shared caches and memories and hence concentrates most of the contention that tasks suffer, with effects on the worst-case contention delay (WCD) of packets and tasks' WCET. While several proposals minimize the impact of individual NoC parameters on WCD, e.g. mapping and routing, there are strong dependences among these NoC parameters. Hence, finding the optimal NoC configurations requires optimizing all parameters simultaneously, which represents a multidimensional optimization problem. In this paper we propose NoCo, a novel approach that combines ILP and stochastic optimization to find NoC configurations in terms of packet routing, application mapping, and arbitration weight allocation. Our results show that NoCo improves other techniques that optimize a subset of NoC parameters.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness under grant TIN2015- 65316-P and the HiPEAC Network of Excellence. It also received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (agreement No. 772773). Carles Hernández is jointly supported by the MINECO and FEDER funds through grant TIN2014-60404-JIN. Jaume Abella has been partially supported by the Spanish Ministry of Economy and Competitiveness under Ramon y Cajal postdoctoral fellowship number RYC-2013-14717. Enrico Mezzetti has been partially supported by the Spanish Ministry of Economy and Competitiveness under Juan de la Cierva-Incorporaci´on postdoctoral fellowship number IJCI-2016-27396.Peer ReviewedPostprint (author's final draft

On the Impact of Heterogeneous NoC Bandwidth Allocation in the WCET of Applications

This thesis analyzes the potential of a Flexible Bandwidth Allocation (FBA) method for networks-on-chip (NoCs), which provides heterogeneous bandwidth distribution to improve the worst-case execution time (WCET) of parallel and sequential applications in NoC-based multi- and many-core processors

On the Impact of Heterogeneous NoC Bandwidth Allocation in the WCET of Applications

This thesis analyzes the potential of a Flexible Bandwidth Allocation (FBA) method for networks-on-chip (NoCs), which provides heterogeneous bandwidth distribution to improve the worst-case execution time (WCET) of parallel and sequential applications in NoC-based multi- and many-core processors

EOmesh: combined flow balancing and deterministic routing for reduced WCET estimates in embedded real-time systems

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The increasing performance needs in critical real-time embedded systems (CRTES) can only be satisfied with the use of high-performance manycore processors. While NoC-based manycore systems are popular in the high-performance domain due to their high average performance, they challenge deriving tight Worst-Case Execution Time (WCET) estimates, as needed in CRTES. Weighted meshes have been proposed to alleviate NoCs pathological behavior – caused by large bandwidth imbalance – by making locally unbalanced arbitration decisions to reach globally balanced bandwidth. In this paper we show that existing weighted mesh solutions do not completely remove unwanted imbalance, in particular for nodes subject to high congestion. We propose EOmesh, an approach that combines heterogeneous predictable routing and weight allocations that delivers near-optimal bandwidth allocation across cores without increasing NoC complexity. EOmesh, which can be implemented either by hardware means or by software means on top of regular weighted meshes, improves the average performance and WCET results of the reference weighted mesh design.This work has been partially supported by the SpanishMinistry of Economy and Competitiveness (MINECO) un-der grant TIN2015-65316-P and the HiPEAC Network ofExcellence. Jaume Abella has been partially supported bythe MINECO under Ramon y Cajal postdoctoral fellowshipnumber RYC-2013-14717. Carles Hern ́andez is jointly fundedby the MINECO and FEDER funds through grant TIN2014-60404-JIN. Francisco J. Cazorla is partially funded by theEuropean Research Council (ERC) under EU’s H2020 research/innovation programme (grant No. 772773)Peer Reviewe

EOmesh: combined flow balancing and deterministic routing for reduced WCET estimates in embedded real-time systems

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The increasing performance needs in critical real-time embedded systems (CRTES) can only be satisfied with the use of high-performance manycore processors. While NoC-based manycore systems are popular in the high-performance domain due to their high average performance, they challenge deriving tight Worst-Case Execution Time (WCET) estimates, as needed in CRTES. Weighted meshes have been proposed to alleviate NoCs pathological behavior – caused by large bandwidth imbalance – by making locally unbalanced arbitration decisions to reach globally balanced bandwidth. In this paper we show that existing weighted mesh solutions do not completely remove unwanted imbalance, in particular for nodes subject to high congestion. We propose EOmesh, an approach that combines heterogeneous predictable routing and weight allocations that delivers near-optimal bandwidth allocation across cores without increasing NoC complexity. EOmesh, which can be implemented either by hardware means or by software means on top of regular weighted meshes, improves the average performance and WCET results of the reference weighted mesh design.Peer Reviewe