ZipCCL: Efficient Lossless Data Compression of Communication Collectives for Accelerating LLM Training

Documenti analoghi

• ZipServ: Fast and Memory-Efficient LLM Inference with Hardware-Aware Lossless Compression
  di: Fan, Ruibo, et al.
  Pubblicazione: (2026)
• HierMoE: Accelerating MoE Training with Hierarchical Token Deduplication and Expert Swap
  di: Lin, Wenxiang, et al.
  Pubblicazione: (2025)
• Parm: Efficient Training of Large Sparsely-Activated Models with Dedicated Schedules
  di: Pan, Xinglin, et al.
  Pubblicazione: (2024)
• DreamDDP: Accelerating Data Parallel Distributed LLM Training with Layer-wise Scheduled Partial Synchronization
  di: Tang, Zhenheng, et al.
  Pubblicazione: (2025)
• Efficient MoE Inference with Fine-Grained Scheduling of Disaggregated Expert Parallelism
  di: Pan, Xinglin, et al.
  Pubblicazione: (2025)