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Comparing Industry Frameworks with Deeply Quantized Neural Networks on Microcontrollers.

, , , , and . ICCE, page 1-6. IEEE, (2021)

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Performance modeling of embedded applications with zero architectural knowledge., and . CODES+ISSS, page 277-286. ACM, (2010)Architectural Design of Cloud Applications: A Performance-Aware Cost Minimization Approach., , , , , and . IEEE Trans. Cloud Comput., 10 (3): 1571-1591 (2022)Performance prediction of deep learning applications training in GPU as a service systems., , , and . Clust. Comput., 25 (2): 1279-1302 (2022)A methodology for performance estimation of heterogeneous multiprocessors embedded systems.. Polytechnic University of Milan, Italy, (2010)Code Transformations Based on Speculative SDC Scheduling., and . ICCAD, page 71-77. IEEE, (2015)High Level Synthesis of RDF Queries for Graph Analytics., , , , , and . ICCAD, page 323-330. IEEE, (2015)Fine grain analysis of simulators accuracy for calibrating performance models., and . International Symposium on Rapid System Prototyping, page 1-7. IEEE, (2010)Automatic Parallelization of Sequential Specifications for Symmetric MPSoCs., , , , , and . IESS, volume 231 of IFIP Advances in Information and Communication Technology, page 179-192. Springer, (2007)Optimizing on-demand GPUs in the Cloud for Deep Learning Applications Training., , , , , and . ICCCS, page 1-8. IEEE, (2019)Machine Learning for Performance Prediction of Spark Cloud Applications., , , , , , , and . CLOUD, page 99-106. IEEE, (2019)