Compiler Optimizations Deep

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mohitmishra786

compiler-optimizations-deep

Deep compiler optimizations skill for RA, ISel, and PGO. Use when explaining register allocation, instruction selection, LICM, vectorization limits, or profile-guided optimization beyond -O3. Activates on queries about register allocation, instruction selection, LICM, auto-vectorization failure, PGO, or BOLT.

Overview

Publisher	mohitmishra786
Repository	`low-level-dev-skills`
Skill name	`compiler-optimizations-deep`
Stars	266
Forks	31
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by mohitmishra786 on GitHub. Read the source before you install it.

Installation

Install the Compiler Optimizations Deep AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/mohitmishra786/low-level-dev-skills/tree/main/skills/compiler-internals/compiler-optimizations-deep
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/mohitmishra786/low-level-dev-skills/tree/main/skills/compiler-internals/compiler-optimizations-deep

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/mohitmishra786/low-level-dev-skills.git /tmp/low-level-dev-skills
mkdir -p .claude/skills
cp -r /tmp/low-level-dev-skills/skills/compiler-internals/compiler-optimizations-deep .claude/skills/compiler-optimizations-deep

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Compiler Optimizations Deep in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Compiler Optimizations Deep on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Compiler Optimizations Deep is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Compiler Optimizations (Deep)

Purpose

Explain optimization phases beyond flags: mid-level IR opts, register allocation, instruction selection/scheduling, vectorization boundaries, PGO, and post-link BOLT — bridging skills/compilers/pgo and LLVM/GCC internals.

When to Use

-O3 did not vectorize a hot loop
Teaching why register pressure causes spills
Planning PGO or BOLT deployment
Understanding pass interaction (e.g., LICM before vectorize)

Workflow

1. Compiler pipeline map


Frontend → LLVM IR / GCC GIMPLE
├── Mid-level: DCE, GVN, LICM, inlining
├── Loop opts: unroll, vectorize
├── Codegen prep: legalize types
├── Instruction selection (DAG → machine ops)
├── Register allocation (greedy, linear scan)
└── Peephole / scheduling

2. Vectorization failure triage

bash
clang -O3 -Rpass=loop-vectorize -Rpass-missed=loop-vectorize foo.c

Miss reason	Typical fix
Unknown trip count	peel loop; assert count
Dependence	reorder / separate accumulators
Function call in loop	inline or outline
Alignment unknown	`__builtin_assume_aligned`

3. Register allocation intuition

When live ranges exceed physical registers, the allocator spills to stack slots — costly loads/stores. Reducing live ranges (splitting variables, rematerialization) helps.

GCC/LLVM both use graph coloring variants (LLVM "greedy regalloc").

4. PGO workflow (Clang)

bash
clang -fprofile-instr-generate -O2 -o app foo.c
./app   # training workload
llvm-profdata merge default.profraw -o default.profdata
clang -fprofile-instr-use=default.profdata -O2 -o app_pgo foo.c

Improves branch layout, inlining, and vectorization thresholds.

See skills/compilers/pgo for GCC and BOLT.

5. BOLT (post-link)

bash
llvm-bolt -instrument app -o app.inst
./app.inst
llvm-bolt -data=perf.fdata -reorder-blocks=+ -o app.bolt app

Optimizes layout after linker — needs relocations (-Wl,--emit-relocs).

6. LICM example

Loop-invariant code motion hoists x * scale out of inner loop when legal — reduces work per iteration.

7. Agent usage


/compiler-optimizations-deep Why did LLVM fail to vectorize this reduction loop?

Common Problems

Symptom	Cause	Fix
PGO no gain	Unrepresentative training	Match production input
BOLT crash	Stripped binary	Keep symbols + relocs
Spills in asm	Register pressure	Simplify live ranges
`-O3` slower	Code bloat / cache	Try `-O2` or PGO
Different GCC/Clang	Pass ordering differs	Compare IR + asm

Related Skills

skills/compilers/pgo — PGO and BOLT detail
skills/compiler-internals/llvm-ir-and-passes — IR-level opts
skills/compiler-internals/code-generation-and-backends — ISel and backends
skills/computer-architecture/cpu-pipelines-and-hazards — scheduling context
skills/low-level-programming/simd-intrinsics — manual vectorization

Frequently asked questions

What does the Compiler Optimizations Deep AI skill do?

Why use Compiler Optimizations Deep on TypingMind?

Because you install it once and use it with any model. Compiler Optimizations Deep is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Compiler Optimizations Deep in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mohitmishra786/low-level-dev-skills/tree/main/skills/compiler-internals/compiler-optimizations-deep. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Compiler Optimizations Deep?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Compiler Optimizations Deep?

As many as you like. As long as a model supports skills, you can use Compiler Optimizations Deep with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Compiler Optimizations Deep AI skill free?

Yes. It is published on GitHub by mohitmishra786 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Compiler Optimizations (Deep)

Purpose

When to Use

Workflow

1. Compiler pipeline map

2. Vectorization failure triage

3. Register allocation intuition

4. PGO workflow (Clang)

5. BOLT (post-link)

6. LICM example

7. Agent usage

Common Problems

Related Skills

Frequently asked questions

Related AI Skills

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