Starscream: Reimagining LLM Sharding on AMD Instinct GPUs with GPU Partitioning

arXiv:2611.15951v1 Announce Type: cross Abstract: As GPU accelerators grow larger to meet rising compute demands, they exhibit increasingly pronounced non-uniform memory access (NUMA) characteristics that challenge existing LLM frameworks. Chiplet-based architectures provide a practical path to larger GPUs while mitigating manufacturing yield constraints. Modern GPUs such as AMD Instinct MI300X employs such a multi-die design, and further offer GPU partitioning capabilities, partitioning a single physical GPU into multiple logical devices with NUMA-aware memory domains, promising faster kernel launches, and reduced memory access latencies with improved locality.