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Optimizing LLM Inference Requests
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Optimizing LLM Inference Requests

16 May Online

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About this event

Introduction to LLM Inference
Optimizing LLM Inference Requests

NOTE: May 16 will only be online with Zoom

Our new book club series is about LLM Inference. Ted has done a deep dive on how LLM inference works and what are the techniques for optimizing performance. This week we will discuss chapter 6 about optimizing individual requests, including prefix caching and speculative decoding.

A free copy of the LLM Inference Illustrated book is available at https://tedkyi.github.io/llm-inference/

Come join us in person or online. Please make sure to read the instructions for joining the event below.

Agenda:

  • 12:00 - 1:15 pm -- Presentation and discussion
  • Time permitting -- Additional Q&A, networking

Links to notes/slides and videos of prior meetups are available on the SDML GitHub repo https://github.com/SanDiegoMachineLearning/bookclub

Location:
Due to conflicts, this session will be Zoom-only

Please Note: There are two steps required to join the online meetup:

  • You must go to our Slack community and ask for the password for the meeting. Link to join is below.
  • You must have a Zoom login in order to join the event. A free Zoom account will work. If you get an error message joining the Zoom, please login to your account on the Zoom website then try again.
  • Use this Zoom link: https://us06web.zoom.us/j/82891977558

Community:
Join our slack channel for questions and discussion about what's new in ML:
https://join.slack.com/t/sdmachinelearning/shared_invite/zt-33z4811de-F_YKuCsQH1ev3TLSnQQfgQ

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