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Predicting Heterogeneity and Serverless Principles of Converged High-Performance Computing, Artificial Intelligence, and Workflows.

, , , , , , , , , and . Computer, 57 (1): 136-144 (January 2024)

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Fine-Grained Heterogeneous Execution Framework with Energy Aware Scheduling., , , , , , , and . CLOUD, page 35-44. IEEE, (2023)The Distribution Is the Performance., , , , and . Computer, 57 (4): 143-149 (April 2024)Predicting Heterogeneity and Serverless Principles of Converged High-Performance Computing, Artificial Intelligence, and Workflows., , , , , , , , , and . Computer, 57 (1): 136-144 (January 2024)A Protocol for creating Multiagent Systems in Ensemble with Pure Data., and . ICMC, Michigan Publishing, (2014)Adaptive Stopping Rule for Performance Measurements., , , and . SC Workshops, page 1288-1297. ACM, (2023)X-TIME: An in-memory engine for accelerating machine learning on tabular data with CAMs., , , , , , , , , and 2 other author(s). CoRR, (2023)Toward transparent and parsimonious methods for automatic performance tuning. (Vers des méthodes transparentes et parcimonieuses pour l'optimisation automatique des performances).. University of Sao Paulo, Brazil, (2021)Mixed Precision Quantization for ReRAM-based DNN Inference Accelerators., , , , , , , , , and 8 other author(s). ASP-DAC, page 372-377. ACM, (2021)Autotuning Under Tight Budget Constraints: A Transparent Design of Experiments Approach., , , , , and . CCGRID, page 147-156. IEEE, (2019)OpenMP is Not as Easy as It Appears., , , , and . HICSS, page 5742-5751. IEEE Computer Society, (2016)