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GPU-Accelerated Real-Time Path Planning and the Predictable Execution Model.

, , , and . ICCS, volume 108 of Procedia Computer Science, page 2428-2432. Elsevier, (2017)

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GPUguard: Towards supporting a predictable execution model for heterogeneous SoC., , and . DATE, page 318-321. IEEE, (2017)HePREM: A Predictable Execution Model for GPU-based Heterogeneous SoCs., , and . IEEE Trans. Computers, 70 (1): 17-29 (2021)A Data-Driven Approach to Lightweight DVFS-Aware Counter-Based Power Modeling for Heterogeneous Platforms., , , and . SAMOS, volume 13511 of Lecture Notes in Computer Science, page 346-361. Springer, (2022)An Online Overclocking Scheme for Bursty Real-time Tasks and an Evaluation of its Thermal Impact., , and . ESTIMedia, page 104-113. ACM, (2016)Data-Driven Power Modeling and Monitoring via Hardware Performance Counters Tracking., , , , , and . CoRR, (2024)Combining PREM compilation and static scheduling for high-performance and predictable MPSoC execution., , , , , , and . Parallel Comput., (2019)GPU-Accelerated Real-Time Path Planning and the Predictable Execution Model., , , and . ICCS, volume 108 of Procedia Computer Science, page 2428-2432. Elsevier, (2017)HEROv2 Software Development Kit (SDK) Docker Image., , and . (May 2022)The AMPERE Project: : A Model-driven development framework for highly Parallel and EneRgy-Efficient computation supporting multi-criteria optimization., , , , , , , , , and 7 other author(s). ISORC, page 201-206. IEEE, (2020)HePREM: Enabling predictable GPU execution on heterogeneous SoC., , and . DATE, page 539-544. IEEE, (2018)