3 papers
cs.DC2025
Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters
Shruti Dongare, Redwan Ibne Seraj Khan, Hadeel Albahar +3
Modern cloud platforms increasingly host large-scale deep learning (DL) workloads, demanding high-throughput, low-latency GPU scheduling. However, the growing heterogeneity of GPU…
cs.DC2025
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…
cs.LG2024
Ensuring Fair LLM Serving Amid Diverse Applications
Redwan Ibne Seraj Khan, Kunal Jain, Haiying Shen +12
In a multi-tenant large language model (LLM) serving platform hosting diverse applications, some users may submit an excessive number of requests, causing the service to become una…