PerfMamba

PerfMamba analyzes Mamba-1 and Mamba-2 selective state space models for efficient AI inference, runtime performance, memory efficiency, long-sequence scaling, GPU resource utilization, and state pruning. The work studies Mamba optimization, SSM pruning, model compression, and acceleration for efficient sequence models and LLM systems.

PerfMamba analyzes the runtime behavior, resource utilization, memory access patterns, scaling properties, and pruning opportunities of Mamba-1 and Mamba-2 selective state space models.