SQ-DM: Accelerating Diffusion Models with Aggressive Quantization and Temporal Sparsity

Documenti analoghi

• FGMP: Fine-Grained Mixed-Precision Weight and Activation Quantization for Hardware-Accelerated LLM Inference
  di: Hooper, Coleman, et al.
  Pubblicazione: (2025)
• Vision Transformer Computation and Resilience for Dynamic Inference
  di: Sreedhar, Kavya, et al.
  Pubblicazione: (2022)
• CDM-QTA: Quantized Training Acceleration for Efficient LoRA Fine-Tuning of Diffusion Model
  di: Lu, Jinming, et al.
  Pubblicazione: (2025)
• GauRast: Enhancing GPU Triangle Rasterizers to Accelerate 3D Gaussian Splatting
  di: Li, Sixu, et al.
  Pubblicazione: (2025)
• FG-Attn: Leveraging Fine-Grained Sparsity In Diffusion Transformers
  di: Durvasula, Sankeerth, et al.
  Pubblicazione: (2025)