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The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

, , , , , , , , , и . (2024)

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Lingxiao Wang

Lingxiao Zhou

Yuzhao Ma

Characterization of higher order modes in optical fibers. Uni Erlangen-Nürnberg, (2009)

Jingxiang Ma

Tsie Ma

 

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CoopStreaming: A Novel Peer-to-Peer System for Fast Live Media Streaming., , , и . WAIM, том 3739 из Lecture Notes in Computer Science, стр. 882-887. Springer, (2005)Towards Efficient Large-Scale Graph Neural Network Computing., , , , , , и . CoRR, (2018)Accelerating GNN training with locality-aware partial execution., , , , , , , и . APSys, стр. 34-41. ACM, (2021)BitNet: Scaling 1-bit Transformers for Large Language Models., , , , , , , , , и . CoRR, (2023)PIT: Optimization of Dynamic Sparse Deep Learning Models via Permutation Invariant Transformation., , , , , , , , , и 1 other автор(ы). SOSP, стр. 331-347. ACM, (2023)Garaph: Efficient GPU-accelerated Graph Processing on a Single Machine with Balanced Replication., , , , и . USENIX Annual Technical Conference, стр. 195-207. USENIX Association, (2017)ConvStencil: Transform Stencil Computation to Matrix Multiplication on Tensor Cores., , , , , , , , , и . PPoPP, стр. 333-347. ACM, (2024)CuWide: Towards Efficient Flow-Based Training for Sparse Wide Models on GPUs., , , , , , и . IEEE Trans. Knowl. Data Eng., 34 (9): 4119-4132 (2022)SparDA: Accelerating Dynamic Sparse Deep Neural Networks via Sparse-Dense Transformation., , , , , , , , , и . CoRR, (2023)Architectural Implications of Graph Neural Networks., , , , , и . IEEE Comput. Archit. Lett., 19 (1): 59-62 (2020)