Tag: Efficiency
All the articles with the tag "Efficiency".
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Exploring the Role of Diversity in Example Selection for In-Context Learning
本文提出基于多样性的上下文学习(DICL)方法,通过最大边际相关性(MMR)算法重新排序示例以平衡相关性和多样性,在多个数据集和大型语言模型上实现了约70%的下游任务性能提升或维持。
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MegaScale-Infer: Serving Mixture-of-Experts at Scale with Disaggregated Expert Parallelism
本文提出MegaScale-Infer系统,通过分离注意力模块和FFN模块的并行策略以及高效M2N通信库,优化大规模MoE模型的推理效率,实现高达1.90倍的吞吐量提升。
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TeLLMe: An Energy-Efficient Ternary LLM Accelerator for Prefilling and Decoding on Edge FPGAs
本文提出TeLLMe,一种能量高效的三元LLM FPGA加速器,通过表查找矩阵引擎和反向注意力优化,支持预填充和解码阶段,在7W功率下实现高达9.51 tokens/s吞吐量和低预填充延迟。
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Splitwiser: Efficient LM inference with constrained resources
Splitwiser introduces a method to split LLM inference phases on a single GPU using multiprocessing and NVIDIA MPS, achieving modest latency reductions (up to 18.2%) and throughput improvements (up to 1.42x) on Huggingface and vLLM pipelines, though constrained by overheads and scalability issues.
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Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing
本文提出Mixture of Sparse Attention (MoSA)方法,通过专家选择路由实现基于内容的稀疏注意力,显著提高了Transformer模型在相同计算预算下的语言建模性能,并优化了资源使用。