Llama.cpp, a lightweight LLM framework, is growing. A community of developers, scholars, and enthusiasts has built around its performance and customisability
GitHub has over 600 contributors, 52,000 stars, 1,500 releases, and 7,400 forks (since its founding). Llama now supports Intel GPUs in server and consumer products thanks to code merges.cpp
GPUs from other vendors and CPUs (x86 and ARM) now work with Intel GPUs. Georgi Gerganov created the first version
The project is largely instructive and tests new capabilities for the ggml library, a machine learning tensor library
Recent Intel releases enable inference on more devices, making AI more accessible. C-based Llama.cpp is quick and has other benefits
Intel used SYCL and oneMKL, their direct programming language and high-performance BLAS library, to construct the SYCL backend. oneAPI supports GPUs
SYCL programming boosts hardware accelerator productivity. The domain-focused, embedded, single-source language is built fully on C++17
Millions of consumer devices can infer Llama.cpp supports Intel GPUs. Intel GPUs perform better with SYCL than OpenCL (CLBlast)