Profile llama.cpp performance with Arm Streamline and KleidiAI LLM kernels
Introduction
Overview
Explore llama.cpp architecture and the inference workflow
Integrate Streamline Annotations into llama.cpp
Analyze token generation performance with Streamline profiling
Implement operator-level performance analysis with Annotation Channels
Examine multi-threaded performance patterns in llama.cpp
Next Steps
Profile llama.cpp performance with Arm Streamline and KleidiAI LLM kernels
Introduction
Overview
Explore llama.cpp architecture and the inference workflow
Integrate Streamline Annotations into llama.cpp
Analyze token generation performance with Streamline profiling
Implement operator-level performance analysis with Annotation Channels
Examine multi-threaded performance patterns in llama.cpp
Next Steps
Share
Bring your insights to the conversation.
Give Feedback
How would you rate this Learning Path?
What is the primary reason for your feedback ?
Thank you! We're grateful for your feedback.
- Have more feedback? Log an issue on GitHub.
- Want to collaborate? Join our Discord server.
Continue Learning
Read related resources
Find more information about the topics in this Learning Path:
Join the Arm Developer Program
Connect, upskill, and build with the Arm Developer Community. Join today for hands-on technical resources and education materials, along with the support of Arm engineers and the broader ecosystem.