[Optimization 7/n] Add Knowledge Database to Kernel optimization #85
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Jack-Khuu
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Jan 28, 2026
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Looks good, is it hard to add the integration code using the RAG into this PR too?
Remember to cite for the code_samples/docs
- Drop
[Optimization 7/n]from the title just to avoid confusion
| self.opt_children.remove(child) | ||
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| def add_parents(self, parent_nodes): | ||
| """Adds a child node to the current node.""" |
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The comment on this is the same as add_children
Let's also add type hints to the args
| """Adds a child node to the current node.""" | ||
| self.opt_parents.extend(parent_nodes) | ||
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| def remove_parents(self, parent_nodes): |
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Do we need this for any reason?
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| level_1_opts = [optnode_latency, optnode_memory, optnode_utilization] | ||
| self.root.add_children(level_1_opts) | ||
| optnode_latency.add_parents([self.root]) | ||
| optnode_memory.add_parents([self.root]) | ||
| optnode_utilization.add_parents([self.root]) |
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nit: For legibility can we add a helper like add_relation or something that updates the child+parent symmetrically
It's easy to parse here, but level3 is a harder to parse
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This PR Introduces a hierarchical optimization database that stores GPU kernel optimization techniques and code examples for the RAG-based optimization.
Key components:
Optimization techniques covered:
This database enables the agent to retrieve relevant optimization strategies and reference implementations based on diagnosed performance bottlenecks.