Nexus: HSA Packet Source Code Extractor

Intercepts HSA packets from a running process and extracts, per kernel, assembly and HIP source into a structured trace (e.g. JSON). Use for kernel-level inspection and assembly/source correlation.

When to Use

• User needs to see which kernels ran and their assembly or HIP source
• Debugging or analyzing GPU dispatch and code generation
• Inspecting assembly-to-source mapping for a HIP (or ROCm) application

Instructions

1. Ensure the target runs on AMD ROCm and uses HSA (e.g. HIP application or ROCm runtime).
2. Choose execution path:
   • If a Nexus MCP server is available, use its tools: list_kernels to enumerate kernels in a trace, and extract_kernel_code to get assembly and HIP/source mapping (signature, files, lines). See nexus/nexus/mcp/server.py for tool parameters and schemas.
   • Otherwise use the Python API from the environment where Nexus is installed.

Python API (recommended when no MCP)

from nexus import Nexus

nexus = Nexus(log_level=1)
trace = nexus.run(["python", "my_gpu_script.py"])

# Or run a binary:
# trace = nexus.run(["./my_hip_app"])

for kernel in trace:
    print(kernel.name, len(kernel.assembly), "instructions")
    for i, asm_line in enumerate(kernel.assembly, 1):
        print(f"  {i}. {asm_line}")
    for line_no, hip_line in zip(kernel.lines or range(1, len(kernel.hip)+1), kernel.hip):
        print(f"  {line_no}: {hip_line}")

# Access by kernel name
k = trace["vector_add(float const*, float const*, float*, int)"]
print(k.assembly, k.hip, k.signature, k.files, k.lines)

# Save/load trace
trace.save("trace.json")
loaded = Nexus.load("trace.json")

Set log_level (0–4) to control verbosity. Use relative paths for the run command and output file so the skill is portable.

Environment-based usage (no Python API)

When the process cannot be launched via nexus.run():

1. Set HSA_TOOLS_LIB to the Nexus shared library path (e.g. build/lib/libnexus.so or the installed path).
2. Set NEXUS_OUTPUT_FILE to the output JSON path.
3. Set NEXUS_LOG_LEVEL (0–4) if needed.
4. Run the application as usual; it will be traced and the output file will contain the kernel data.

Optional: NEXUS_EXTRA_SEARCH_PREFIX (colon-separated) for HIP source search; TRITON_DISABLE_LINE_INFO=0 for Triton kernel line info.

Workflow

1. Identify the command that runs the GPU workload (e.g. python script.py or ./app).
2. If using the Python API: create Nexus(log_level=...), call nexus.run([...]), then iterate trace and optionally trace.save(...).
3. If using the env method: set HSA_TOOLS_LIB and NEXUS_OUTPUT_FILE, then run the app; open the JSON and parse the kernels structure.
4. Use kernel signature, assembly, hip, files, and lines to analyze what ran and map assembly back to source.
5. Use relative paths for commands and output files.

Notes

• Nexus is intended for research/analysis; ensure the target environment has the Nexus library and compatible ROCm/HSA stack.
• For Triton kernels, enable line info via TRITON_DISABLE_LINE_INFO=0 when using the Python API.