Advanced Optimization and Efficiency
Building on the previous chapter, we will dive deeper into the technical aspects of enhancing LLM performance. You will explore state-of-the-art hardware acceleration, and you will also learn how to manage data storage and representation for optimal efficiency and speed up inference without loss of quality. We will provide a balanced view of the trade-offs between cost and performance, a key consideration when deploying LLMs at scale.
In this chapter, we’re going to cover the following main topics:
- Advanced hardware acceleration techniques
- Efficient data representation and storage
- Speeding up inference without compromising quality
- Balancing cost and performance in LLM deployment
By the end of this chapter, you will have acquired a comprehensive understanding of the technical intricacies involved in enhancing LLM performance beyond what was covered in the previous chapter.
