hotpath 0.3.8

Profile vLLM inference under RL-style rollout workloads.

hotpath

Profiler for LLM inference.

hotpath profiles live vLLM and SGLang servers, analyzes request and GPU behavior, and recommends when to split prefill and decode.

What it does

• Profile a live endpoint with real traffic
• Analyze queueing, prefill, decode, cache, and batching
• Recommend disaggregation and generate deployment configs

Install

uv tool install hotpath

Quick start

Profile a live vLLM server:

hotpath serve-profile \
  --endpoint http://localhost:8000 \
  --traffic prompts.jsonl \
  --concurrency 4 \
  --duration 60 \
  --output .hotpath/run

View the report:

hotpath serve-report .hotpath/run/serve_profile.db

Generate deployment configs:

hotpath disagg-config .hotpath/run/serve_profile.db --format all

If you want server-side request timing, start vLLM with debug logs and pass the log file:

VLLM_LOGGING_LEVEL=DEBUG vllm serve <model> 2>vllm.log &

hotpath serve-profile \
  --endpoint http://localhost:8000 \
  --traffic prompts.jsonl \
  --server-log vllm.log \
  --concurrency 4 \
  --duration 60

If you want kernel-level GPU traces, add --nsys:

hotpath serve-profile \
  --endpoint http://localhost:8000 \
  --traffic prompts.jsonl \
  --nsys

Traffic format

JSONL, one request per line:

{"prompt": "Explain KV cache eviction policy.", "max_tokens": 256}
{"prompt": "Write a Python retry decorator with exponential backoff.", "max_tokens": 400}

ShareGPT format is also supported.

Commands

Command	Description
serve-profile	Profile a live vLLM or SGLang server
serve-report	Print a serving analysis report
disagg-config	Generate deployment configs for disaggregated serving
profile	Run GPU kernel profiling under RL-style traffic
report	View a saved kernel profile
diff	Compare two kernel profiles
bench	Benchmark individual GPU kernel implementations
export	Export profile data to JSON, CSV, or OTLP
doctor	Check local profiling environment
lock-clocks	Lock GPU clocks for reproducible measurements

System requirements

• Linux
• NVIDIA GPU with CUDA driver
• nsys for kernel profiling
• vLLM or SGLang for serving analysis

Build from source

cmake -S . -B build -DCMAKE_BUILD_TYPE=Release
cmake --build build --parallel
ctest --test-dir build --output-on-failure

Install from source:

uv tool install .

Requirements: CMake 3.28+, C++20 compiler, SQLite3.

How it works

hotpath stores results in SQLite and combines three data sources:

1. Kernel traces from nsys
2. Server metrics from /metrics
3. Request lifecycle timing from client traces and vLLM debug logs

The report turns those signals into latency breakdowns, cache analysis, prefix-sharing analysis, and a disaggregation recommendation.

Release notes

See CHANGELOG.md.