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cs.DC2025
Straggler Tolerant and Resilient DL Training on Homogeneous GPUs
Zeyu Zhang, Haiying Shen
Despite the popularity of homogeneous GPU-based deep learning (DL) training, the prevalence, causes and impact of stragglers and the effectiveness of existing straggler mitigation…
cs.DC2025
MorphServe: Efficient and Workload-Aware LLM Serving via Runtime Quantized Layer Swapping and KV Cache Resizing
Zhaoyuan Su, Zeyu Zhang, Tingfeng Lan +4
Efficiently serving large language models (LLMs) under dynamic and bursty workloads remains a key challenge for real-world deployment. Existing serving frameworks and static model…
cs.DC2025
HACK: Homomorphic Acceleration via Compression of the Key-Value Cache for Disaggregated LLM Inference
Zeyu Zhang, Haiying Shen, Shay Vargaftik +3
Disaggregated Large Language Model (LLM) inference has gained popularity as it separates the computation-intensive prefill stage from the memory-intensive decode stage, avoiding th…