@pallavishekhar_: Learn LLM Inference Engineering - Prefill vs Decode - KV Cache - PagedAttention - Flash Attention - Continuous Batching…
Summary
An educational overview of key concepts in LLM inference engineering, covering techniques like KV cache, PagedAttention, Flash Attention, and continuous batching to optimize inference performance.
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Learn LLM Inference Engineering
- Prefill vs Decode
- KV Cache
- PagedAttention
- Flash Attention
- Continuous Batching
- Speculative Decoding
- Token Streaming
- Prompt Caching
- Grouped Query Attention
- Mixture of Experts
- How does vLLM work?
- How does SGLang work?
- LLM Routing
- GPU, TPU
Amit Shekhar (@amitiitbhu): LLM Inference Engineering - Problem and Solution
Problem: LLMs are slow Solution: KV Cache - Avoid recomputing previous tokens.
Problem: KV Cache consumes huge memory Solution: PagedAttention - Manage KV memory efficiently.
Problem: GPU is underutilized Solution: Continuous
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