PowerInfer: High-Speed LLM Inference on Consumer GPUs via CPU-GPU Hybrid Design
Running large language models locally has always been constrained by a hard wall: GPU memory. A 175-billion parameter model in FP16 requires …
Running large language models locally has always been constrained by a hard wall: GPU memory. A 175-billion parameter model in FP16 requires …
Deploying large language models in production requires more than just loading weights onto a GPU. To achieve acceptable throughput and latency, …
Large language models are powerful, but their size makes them expensive to deploy. A 70-billion-parameter model in 16-bit precision requires …
The Transformer architecture has dominated deep learning for years, but a new challenger has emerged: state space models (SSMs). At the heart of …