Highlighting recent advances in multi-GPU and tensor parallel support in llama.cpp
Over the last few months llama.cpp maintainers and engineers from NVIDIA collaborated to improve the multi-GPU performance in ggml. This resulted in significant performance gains on RTX systems and laid the groundwork for hardware-agnostic tensor parallelism in ggml.
For more information on this and other advancements in the low-level inference engine of llama.cpp, check the technical blog by @NVIDIARTXSpark below
Build on-device personal AI agents on Windows PCs with new tools from NVIDIA and Microsoft, including secure sandboxing, faster local inference, multi-GPU support, and RTX acceleration for Windows AI APIs.
Read the technical blog: https://nvda.ws/4e0rLDN