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Scalable Tracing of MPI Events and Performance Metrics., , , , и . IPDPS Workshops, стр. 714-723. IEEE, (2023)EC-SpMM: Efficient Compilation of SpMM Kernel on GPUs., , , , , , и . ICPP, стр. 21-30. ACM, (2023)FedBPT: Efficient Federated Black-box Prompt Tuning for Large Language Models., , , , , , и . CoRR, (2023)Performance Analysis of Graph Neural Network Frameworks., , , и . ISPASS, стр. 118-127. IEEE, (2021)AdaSAM: Boosting Sharpness-Aware Minimization with Adaptive Learning Rate and Momentum for Training Deep Neural Networks., , , , , , , , и . CoRR, (2023)FedLALR: Client-Specific Adaptive Learning Rates Achieve Linear Speedup for Non-IID Data., , , , , , и . CoRR, (2023)Global-in-time energy stability: a powerful analysis tool for the gradient flow problem without maximum principle or Lipschitz assumption., , , , и . CoRR, (2024)FedBPT: Efficient Federated Black-box Prompt Tuning for Large Language Models., , , , , , , , и . ICML, OpenReview.net, (2024)Fed-CBS: A Heterogeneity-Aware Client Sampling Mechanism for Federated Learning via Class-Imbalance Reduction., , , , , , , , и . CoRR, (2022)FedMask: Joint Computation and Communication-Efficient Personalized Federated Learning via Heterogeneous Masking., , , , , и . SenSys, стр. 42-55. ACM, (2021)