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TSPLIT: Fine-grained GPU Memory Management for Efficient DNN Training via Tensor Splitting., , , и . ICDE, стр. 2615-2628. IEEE, (2022)HET-GMP: A Graph-based System Approach to Scaling Large Embedding Model Training., , , , , , и . SIGMOD Conference, стр. 470-480. ACM, (2022)Efficiently Training 7B LLM with 1 Million Sequence Length on 8 GPUs., , , , , , , , , и 2 other автор(ы). CoRR, (2024)DataSculpt: Crafting Data Landscapes for LLM Post-Training through Multi-objective Partitioning., , , , , , , , , и 1 other автор(ы). CoRR, (2024)Hetu: a highly efficient automatic parallel distributed deep learning system., , , , и . Sci. China Inf. Sci., (января 2023)Angel-PTM: A Scalable and Economical Large-scale Pre-training System in Tencent., , , , , , , и . Proc. VLDB Endow., 16 (12): 3781-3794 (2023)Clover: Regressive Lightweight Speculative Decoding with Sequential Knowledge., , , , , , , и . CoRR, (2024)Heterogeneity-Aware Distributed Machine Learning Training via Partial Reduce., , , , , , и . SIGMOD Conference, стр. 2262-2270. ACM, (2021)PQCache: Product Quantization-based KVCache for Long Context LLM Inference., , , , , , , и . CoRR, (2024)BaichuanSEED: Sharing the Potential of ExtensivE Data Collection and Deduplication by Introducing a Competitive Large Language Model Baseline., , , , , , , , , и 10 other автор(ы). CoRR, (2024)