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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,112 @@ | ||
| # LLMs in TT-NN | ||
| Authors: | ||
| ## Contents | ||
| - [LLMs in TT-NN](#llms-in-tt-nn) | ||
| - [Contents](#contents) | ||
| - [1. Overview](#1-overview) | ||
| - [2. Modules](#2-modules) | ||
| - [2.1 Embedding](#21-embedding) | ||
| - [2.2 RoPE](#22-rope) | ||
| - [2.3 Norm](#23-norm) | ||
| - [2.4 Attention](#24-attention) | ||
| - [2.5 MLP](#25-mlp) | ||
| - [2.6 Decoder](#26-decoder) | ||
| - [2.7 LM Head](#27-lm-head) | ||
| - [3. Features](#3-features) | ||
| - [3.1 Generative Decoding](#31-generative-decoding) | ||
| - [3.2 Prefill and Decode](#32-prefill-and-decode) | ||
| - [3.3 Multi-Device](#33-multi-device) | ||
| - [3.4 Continuous Batching](#34-continuous-batching) | ||
| - [3.5 vLLM Integration](#34-vllm-integration) | ||
| - [4. Best Practices and Optimizations](#4-best-practices-and-optimizations) | ||
| - [4.1 Tracing](#41-tracing) | ||
| - [4.2 Async Mode](#42-async-mode) | ||
| - [4.3 Multiple CQs](#43-multiple-cqs) | ||
| - [4.4 Op Configs](#44-op-configs) | ||
| - [4.5 Accuracy](#45-accuracy) | ||
| - [4.6 Performance Analysis](#46-performance-analysis) | ||
| - [4.7 Misc. Performance Optimizations](#47-misc-performance-optimizations) | ||
| - [4.8 Module Tests](#48-module-tests) | ||
| - [4.9 Performance Testing](#49-performance-testing) | ||
| - [4.10 Common Pitfalls](#410-common-pitfalls) | ||
| - [4.10.1 Error Messages](#4101-error-messages) | ||
| - [4.10.2 Shard Spec Mismatches](#4102-shard-spec-mismatches) | ||
| - [4.10.3 Ethernet Dispatch Cores](#4103-ethernet-dispatch-cores) | ||
| - [4.10.4 Hangs](#4104-hangs) | ||
| - [4.10.4.1 Tracing](#41041-tracing) | ||
| - [4.10.4.2 Large Matmuls](#41042-large-matmuls) | ||
|
|
||
| ## 1. Overview | ||
| ## 2. Modules | ||
| ### 2.1 Embedding | ||
| ### 2.2 RoPE | ||
| - Iterative update system | ||
| - When to use our fused op | ||
| ### 2.3 Norm | ||
| - Replicated layernorm vs distributed layernorm | ||
| - Layernorm/rmsnorm weights in row major / wrapped around tile size trick | ||
| ### 2.4 Attention | ||
| - Flash Attention and Flash Decode | ||
| - general description | ||
| - limitations | ||
| - which dims are parallelized | ||
| ### 2.5 MLP | ||
| ### 2.6 Decoder | ||
| ### 2.7 LM Head | ||
| ## 3. Features | ||
| ### 3.1 Generative Decoding | ||
| ### 3.2 Prefill and Decode | ||
| - submodules, tests | ||
| - how to combine prefill and decode, | ||
| - slicing prefill to fit in L1 | ||
| ### 3.3 Multi-Device | ||
| - device mesh | ||
| - column parallel followed by row parallel | ||
| - sharding, CCL ops, reducing CCL overheads, etc. | ||
| ### 3.4 Continuous Batching | ||
| - quick intro and how it is implemented in demos. | ||
| ### 3.5 vLLM Integration | ||
| - Our vLLM repo and what's needed to integrate with it. | ||
| ## 4. Best Practices and Optimizations | ||
| ### 4.1 Tracing | ||
| - link to existing doc, why it helps decode more | ||
| ### 4.2 Async Mode | ||
| ### 4.3 Multiple CQs | ||
| - how to feed back output to input and read output asyncronously | ||
| ### 4.4 Op Configs | ||
| - Writing correct program configs and shard specs | ||
| - Deciding how many cores to run an op on | ||
| - Why did we use 16 cores for MLP | ||
| - Which matmul to use when @Colman Glagovich | ||
| - 1d, 2d, dram-sharded, ... | ||
| - Implicitly padding weights in program config for matmuls | ||
| ### 4.5 Accuracy | ||
| - How we measure it (PCC, perplexity, top-1/top-5, end-user tests, benchmarking) | ||
| - How much PCC is enough? Rules of thumb. | ||
| - Accuracy tests | ||
| - Debugging PCC issues | ||
| ### 4.6 Performance Analysis | ||
| - Performance tooling, tracy | ||
| ### 4.7 Misc. Performance Optimizations | ||
| - Which dim to shard matmuls on | ||
| - DRAM-sharding | ||
| - Avoiding sharded to interleaved calls | ||
| ### 4.8 Module Tests | ||
| ### 4.9 Performance Testing | ||
| ### 4.10 Common Pitfalls | ||
| #### 4.10.1 Error Messages | ||
| - Running out of L1 | ||
| - Shard spec and program config mismatches | ||
| - For some TTNN ops (e.g. ttnn.all_gather) it's not supported to pass -1 in the dim argument. | ||
| - You'll see an error related to op invocation where the arguments don't match | ||
| #### 4.10.2 Shard Spec Mismatches | ||
| #### 4.10.3 Ethernet Dispatch Cores | ||
| - link to any other description, and mention it is needed for N300 and T3K | ||
| #### 4.10.4 Hangs | ||
| ##### 4.10.4.1 Tracing | ||
| - Host communications cause tracing to hang | ||
| - Running without async mode enabled causes tracing to hang | ||
| - Careful with print in tracing | ||
| ##### 4.10.4.2 Large Matmuls | ||
| - Large matmuls hanging? Link to appropriate ticket with workaround | ||
| - Issue is being investigated with a workaround of setting the output subblock to 1,1 and grid size to 8x7 |
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