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Optimizing the performance of sensor network programs through estimation-based code profiling., , и . Pervasive Mob. Comput., (2017)Multi-agent Policy Optimization with Approximatively Synchronous Advantage Estimation., , , и . CoRR, (2020)SECCEG: A Secure and Efficient Cryptographic Co-processor Based on Embedded GPU System., , , , , , и . WASA (2), том 12938 из Lecture Notes in Computer Science, стр. 107-122. Springer, (2021)Imagine, Initialize, and Explore: An Effective Exploration Method in Multi-Agent Reinforcement Learning., , , , , и . AAAI, стр. 17487-17495. AAAI Press, (2024)Accelerating Multigrid-based Hierarchical Scientific Data Refactoring on GPUs., , , , , , , , , и 2 other автор(ы). IPDPS, стр. 859-868. IEEE, (2021)Towards Instruction Level Record and Replay of Sensor Network Applications., и . MASCOTS, стр. 475-484. IEEE Computer Society, (2013)Comprehensive Measurement and Analysis of the User-Perceived I/O Performance in a Production Leadership-Class Storage System., , , , , и . ICDCS, стр. 1022-1031. IEEE Computer Society, (2017)Region-adaptive, Error-controlled Scientific Data Compression using Multilevel Decomposition., , , , , , , , , и 2 other автор(ы). SSDBM, стр. 5:1-5:12. ACM, (2022)Improving Progressive Retrieval for HPC Scientific Data using Deep Neural Network., , , , , , , , , и . ICDE, стр. 2727-2739. IEEE, (2023)Understanding the Impact of Data Staging for Coupled Scientific Workflows., , , , , , , , и . IEEE Trans. Parallel Distributed Syst., 33 (10): 4134-4147 (2022)