2 papers
cs.LG2024
TurboAttention: Efficient Attention Approximation For High Throughputs LLMs
Hao Kang, Srikant Bharadwaj, James Hensman +3
Large language model (LLM) inference demands significant amount of computation and memory, especially in the key attention mechanism. While techniques, such as quantization and acc…
cs.DC2024
AI Metropolis: Scaling Large Language Model-based Multi-Agent Simulation with Out-of-order Execution
Zhiqiang Xie, Hao Kang, Ying Sheng +3
With more advanced natural language understanding and reasoning capabilities, large language model (LLM)-powered agents are increasingly developed in simulated environments to perf…