1 citations · 1 across the 3 of their papers we have counts for
4 papers
Serving Masked Diffusion LLMs: Characterization and Design Principles from Real Hardware
Farhana Amin, Sabiha Afroz, Mona Moghadampanah +1
Masked diffusion language models (dLLMs) can in principle generate text faster than autoregressive (AR) models, since they denoise many tokens at once. Recent systems have begun bu…
CAI-DLLM: Convergence Aware Inference for Diffusion Language Models
Farhana Amin, Sabiha Afroz, Dimitrios S. Nikolopoulos
Diffusion language models can generate many tokens in parallel, but they still require repeated denoising steps during inference. This makes generation costly, especially when the…
10Cache: Heterogeneous Resource-Aware Tensor Caching and Migration for LLM Training
Sabiha Afroz, Redwan Ibne Seraj Khan, Hadeel Albahar +2
Training large language models (LLMs) in the cloud faces growing memory bottlenecks due to the limited capacity and high cost of GPUs. While GPU memory offloading to CPU and NVMe h…
DiffPro: Joint Timestep and Layer-Wise Precision Optimization for Efficient Diffusion Inference
Farhana Amin, Sabiha Afroz, Kanchon Gharami +2
Diffusion models produce high quality images but inference is costly due to many denoising steps and heavy matrix operations. We present DiffPro, a post-training, hardware-faithful…