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Enabling accurate power profiling of HPC applications on exascale systems.

, , , and . ROSS@ICS, page 4:1-4:8. ACM, (2013)

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Enabling accurate power profiling of HPC applications on exascale systems., , , and . ROSS@ICS, page 4:1-4:8. ACM, (2013)Enhancing the efficiency and practicality of software transactional memory on massively multithreaded systems.. Polytechnic University of Catalonia, Spain, (2013)Auto-HPCnet: An Automatic Framework to Build Neural Network-based Surrogate for High-Performance Computing Applications., , and . HPDC, page 31-44. ACM, (2023)Smart-PGSim: using neural network to accelerate AC-OPF power grid simulation., , , and . SC, page 63. IEEE/ACM, (2020)Comparative analysis of soft-error detection strategies: a case study with iterative methods., , , , , and . CF, page 173-182. ACM, (2018)Localized Fault Recovery for Nested Fork-Join Programs., , and . IPDPS, page 397-408. IEEE Computer Society, (2017)On the Application Task Granularity and the Interplay with the Scheduling Overhead in Many-Core Shared Memory Systems., , , , and . CLUSTER, page 428-437. IEEE Computer Society, (2015)Union: A Unified HW-SW Co-Design Ecosystem in MLIR for Evaluating Tensor Operations on Spatial Accelerators., , , , , , , and . PACT, page 30-44. IEEE, (2021)LAHypergraph: Parallel Hypergraph Analytics in the Language of Linear Algebra., , and . ACDA, page 147-158. SIAM, (2023)Understanding scale-Dependent soft-Error Behavior of Scientific Applications., , , and . CCGrid, page 482-491. IEEE Computer Society, (2018)