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cs.LG2025
MegaScale-MoE: Large-Scale Communication-Efficient Training of Mixture-of-Experts Models in Production
Chao Jin, Ziheng Jiang, Zhihao Bai +16
We present MegaScale-MoE, a production system tailored for the efficient training of large-scale mixture-of-experts (MoE) models. MoE emerges as a promising architecture to scale l…
cs.LG2024★ 1 cited
ShadowKV: KV Cache in Shadows for High-Throughput Long-Context LLM Inference
Hanshi Sun, Li-Wen Chang, Wenlei Bao +6
With the widespread deployment of long-context large language models (LLMs), there has been a growing demand for efficient support of high-throughput inference. However, as the key…
cs.LG2024★ 5 cited
FLUX: Fast Software-based Communication Overlap On GPUs Through Kernel Fusion
Li-Wen Chang, Wenlei Bao, Qi Hou +10
Large deep learning models have demonstrated strong ability to solve many tasks across a wide range of applications. Those large models typically require training and inference to…